We have proposed a new network management mechanism for Wireless LAN on which applications on many terminals can run in high quality even in congested frequency bands such as 2.4 GHz. The system is designed by taking users' Quality of Experience (QoE) as a key metric for network management. In this paper, we present the experimental evaluation of the proposed QoE-oriented wireless LAN, as well as the concept and the design of our prototype of the proposed system. The QoE-oriented wireless LAN consists of three major functional elements: smart multi-layer sensing; prediction of achievable application quality; and radio channel access management. The smart multi-layer sensing measures available radio resources and estimates radio systems (WiFi, Bluetooth, ZigBee, etc) and their traffic types. Using those sensed and estimated results, amount of achievable traffic considering required application quality is calculated by the prediction function. The radio channel access management function decides and allows channel access for applications depending on those priorities. We will show the evaluation results of the proposed QoE-oriented wireless LAN through experiments and simulations. In realistic scenarios with mixed types of applications, traffic types, and data rates, the proposed system significantly improves QoE satisfied throughput.

Cognitive radio engines (CEs) are the brains behind the intelligent adaptations for cognitive radios (CRs). A CE is an intelligent agent which observes the radio environment and chooses the best communication settings that best meet the application's goal. In this process, providing reliable performance is one of the major tasks in designing CEs for wireless communication systems. In our previous publication, we have proposed a meta-CE that is able to evaluate various CE algorithms performance automatically. A meta-CE is generally considered to be comprised by a set of CE algorithms and meta-cognition module that provides the meta-abilities of the CE. We have identified that in order to enable meta-cognition we need to perform the following functions: first, characterizing the performance of each individual CE algorithm on a given operating scenario and second, distinguishing between different operating scenarios. An operating scenario is defined as the set of the operating objective, channel availability, and channel quality metrics. Meta-CE is able to provide much higher performance than each individual CE algorithm due to its flexibility and ultimately predictability of the Cognitive Radio Systems (CRS). Providing predictable performance at all times is of paramount importance in different CE techniques. In this work, we extend our meta-CE design to learn the intelligence level of various individual CE algorithms in distinct operating scenarios and optimize defined objectives of CRS. The new design presented in this paper aims to enable a meta-CE to predict the performance level of different CE algorithms and the performance level of the meta-CE itself. To this end, in the first step, meta-CE characterizes the performance of different CE algorithms based on the operating channel scenarios and measures the confidence level of each CE algorithm with lower and upper bounds of their expected performance by available experience database. Then, meta-CE predicts the training speed and expected performance of individual CE algorithms for ongoing operating channel scenarios based on the information of previous step. Finally, meta-CE chooses a set of available algorithms to provide the needed performance level of CRS. This approach allows a powerful estimation of the performance level of CEs and helps a radio to provide a deterministic output. To begin with, in this paper we propose a meta-CE design based on an online classification technique for optimizing the resource usage of CRS regards to its objective. A classification technique discriminates between difference groups of data sets according to its similarities, on the basis of a training set of data containing observations. In our meta-CE, the different classes are the appropriate CE to be used based on the operating conditions. The online classification means that the classifier updates its rules as new information are made available vs. waiting to have all the data available (offline classification). Online classification allows our meta-CE to gradually improve its selection accuracy as it collects more data about the performance of the individual CEs. Secondly, meta-CE is facilitated by coefficient of variation as an index to approximate the expected performance level of each individual CE algorithm. The main purpose of this step is providing predictable performance based on the available CE's experience database. Meta-CE also uses confidence interval approximation for standard normal distribution to calculate the lower and upper bounds of CE's expected performance. Finally, meta-CE predicts performance level of a CE algorithm for an operating scenario by usage of learning curve's slope, coefficient of variation, and confidence interval approximation. To sum up, in this paper we continue our work in meta-CE design by presenting our work on online classification and the development and definition of a variation index that allows to predict the performance of our meta-CE. Predictable performance is of paramount importance for a cognitive radio system.

The National Aeronautics and Space Administration's (NASA) Space Communications and Navigation (SCaN) Program is investigating the space communication methods of the future with the SCaN Testbed. The SCaN Testbed, developed by the program at the NASA Glenn Research Center, is a discrete communications component residing on the ISS that employs Software-Defined Radio (SDR) technologies to allow research into new communications techniques between ground stations, the ISS, and deep space communications. The hardware can be reconfigured to support multiple waveforms that operate in the S, L and Ka bands. The Space Telecommunications Radio System (STRS) Architecture was developed concurrently with the SCaN Testbed to define a standardized method for defining waveforms. The specifications enable new technologies to be added at either the software or hardware layers. We propose the use of a reconfigurable communication scheme that adjusts its modulation and channel coding dynamically based on transmission statistics. The reconfigurability will be controlled by a meta-cognitive engine that collates the transmission statistics in real time and makes decisions based on the current statistics and the past experiences of different modulation schemes. The metacognitive engine will reside at the ground stations and notifies the ISS receiving waveform of any adjustments being made to the current communication scheme. We also propose a lightweight meta-cognitive engine reside at the receiver, whose main purpose is to ensure that the transmitting and receiving waveforms remain synchronized, and revert to a common waveform should they become unsynchronized. To demonstrate our system we implemented our metacognitive engine in Python and used Ettus Research Universal Software Radio Peripherals (USRPs) with the GNU Radio (GR) SDR Framework as the radio platform. Our reconfigurable waveform included BPSK, QPSK, 8PSK, and QAM16 modulation schemes, along with various channel coding schemes. In a lab environment, we demonstrated that data throughput can be significantly increased if the channel can support a higher modulation scheme. We now propose that our system be adapted to use the STRS Architecture for testing on the SCaN Testbed.

The use of highly dense heterogeneous networks (HetNet) to increase capacity per area unit is a research topic for future 5G communication systems. Due to an increased probability of handover failures and handover ping-pongs in a HetNet, the handover procedure is particularly important to achieve seamless mobility. To reduce the probability of handover ping-pongs without increasing the probability of handover failures, in this work we propose a novel method to adapt the time to trigger and the handover margin based on the signal to interference plus noise ratio reduction rate. Numerical evaluations of the proposed method show lower overall handover failures and handover ping-pongs as compared to a handover procedure that uses fixed parameters.

Workshop 1B: Big RF

Software-Defined Radio (SDR) is often seen as a valuable tool for low-cost and rapid prototyping and research through testbed-based experimentation. GUI tools like GNURadio Companion, OSSIE or MATLAB's Simulink enable one to create a full communications system in a few minutes. Signal visualization is extremely useful not only throughout the developing process, but also as an educational tool: students see the effects of hardware or channel impairments and learn how to deal with them through real-time experimentation. However, the communications systems created in these experiments are often too simplistic versions of modern communications systems. A simple OFDM waveform, for instance, is very useful to teach or experiment with channel estimation, frequency offsets and synchronization. However, it is not a representative model of a commercial LTE system. LTE has very particular synchronization and reference signals, multi-cell interference patterns, modulation/coding or multi-antenna schemes. Assembling a testbed for teaching or investigating any of these features is too challenging, expensive and time-consuming. A simulator is not useful if we want to deal with real signals in real-time. A commercial product is good for end-to-end system verification, but lacks the flexibility to modify or create new features. Thus, resorting to a simplistic communications system is often the best solution. LibLTE is an open source library of DSP blocks for the 3GPP LTE Release 8 standard. It is highly modular and very flexible and is specifically designed for experimentation-based learning, testbed-based research and low-cost prototyping of new systems. Simple GUI tools allow students to visualize over-the-air LTE signals (coming from commercial LTE networks), see the constellation, learn and play with the different synchronization algorithms, see what happens when we move the receiver to the cell edge, learn how to deal with neighbour cells interference, etc. LibLTE is a perfect tool to create small lab experiments for specific LTE features in just a few minutes. Its modular structure allows replacing or adding components and quickly seeing the effect to the complete system. Inter-module dependencies are kept to a minimal, so that replacing the Turbo or Viterbi decoders by another implementation, for instance, is as simple as renaming a function call. This makes libLTE an ideal platform for testbed-based research and creation of new advanced UE or eNodeB implementations that take LTE as the basis on top of which extended functionalities or features are added. This tutorial will be highly interactive. We will create and run a simple LTE lab experiment that will receive real signals coming from commercial LTE networks, to show the potential of libLTE as an educational tool. We will explain how libLTE is organized by looking at the code. Then, we will modify an existing LTE UE implementation and visualize the impact on the final end-to-end performance again using real-time LTE signals.

Maintaining reliable communications, whether in the face of conditions caused by natural environmental factors, or intentionally malicious activities, is a continuous challenge for wireless systems. The growing demand for data by users of smartphones, tablets and laptops has only exacerbated the problem, by adding additional interference to wireless networks as well as constricting already overstretched spectrum assets. The latest approach to dealing with such interference challenges has been Dynamic Spectrum Access (DSA), which is essentially an attempt to avoid interference. By contrast, there are now available "layered" cognitive radio approaches in which intelligent and active interference mitigation plays a dominant role. The addition of advanced interference mitigation algorithms to DSA capabilities allows for a substantial increase in the carrying capacity of both existing private and unlicensed spectrum. This delivers key benefits to wireless planners in a number of sectors that deal with limited spectrum resources, such as government agencies, public safety and emergency management. This paper will discuss the components and applications of these advanced interference mitigation techniques.

The use of millimeter waves (mmWave) frequencies, along with network densification through cell-size reduction and the use of large scale antenna arrays (aka Massive MIMO), are the three fundamental strategies that will concur to the anticipated 1000x data-rate increase of 5G cellular networks with respect to existing 4G LTE systems. Among these three, mmWave is by no doubt the strategy that is expected to bring the largest advantages in terms of data-rate, due to the availability of much larger frequency bands than in today's conventional microwave systems. Contradicting classical common consensus that mmWave could be used just for indoor short-range communications due to their strong attenuation, low penetration capabilities through obstacles, low diffraction properties, etc., recent research has shown that thanks to the possibility of packing many antennas in a limited space, array gain can overcome path loss and ranges in the order of 200m are certainly feasible with plenty of available bandwidth and attendant large data-rates. This paper provides an up-to-date overview of recent research results in the area of mmWave frequencies for cellular 5G, along with a survey of the most urgent research challenges that are to be tackled in order to make mmWave cellular systems really working. Industry and academia are indeed intensively working on mmWave systems and initial results are already available, mainly concerning (a) the characterization of the propagation channel also through experimental measurements campaigns; (b) the theoretical study of the system capacity through the use of stochastic geometry theory; (c) the design of resource allocation schemes able to take advantage of the narrow beams that can be created, in order to fully exploit the spatial diversity gain; and (d) the design of low-cost electronic circuitry suited for the mass-market. Despite relevant progress, however, several open problems and challenges are still on the table and are to be tackled in the near future. Some of these challenges that we will review in our paper include the following: - Backhaul bottleneck and cost: mmWave Base Stations (BSs) will be capable to offer large data-rates to mobile users over small areas, and this will lead to a sharp increase of the amount of data that is to be exchanged with the core network. Many high-capacity backhaul links will be needed, and this may be a serious bottleneck. Some researchers have started considering the use of in-band wireless backhauling, and this seems a promising strategy. - Blockage effects are to be properly taken into account, since they result in abrupt transitions from good propagation conditions to very bad ones, and countermeasures are to be studied. Spatial diversity and BSs cooperation seems to be here a viable solution. - Transceiver complexity and its energy-efficiency is another challenge; indeed, due to the necessity of using large antenna arrays, several independent RF chains are needed, and their impact on the transceiver complexity/cost/energy-consumption is to be investigated, also in the light of a possible mass-market production of mmWave transceivers. - Need for fast and reliable link acquisition and tracking algorithms: mmwave are envisioned to be used through very narrow directional beams, and this, although being a very attractive feature when it comes to transmitting at large data-rates with almost no interference, is a curse when performing user discovery and link acquisition. - Definition of the modulation format: will OFDM used also at mmwave frequencies? Or alternative simpler formats, even noncoherent ones, will be preferred in order to simplify the transceiver architecture? Some researchers have also been proposing the use of single-carrier modulation with cyclic prefix and frequency-domain equalization. This will be a hot topic to be considered. The final paper will include a comprehensive bibliographical review on the subject of mmWave communications for 5G cellular systems.

Radio frequency spectrum management plays a critical role in various domains, including government, military, industrial and personal communications. Current methodology of achieving greater utilization of spectrum is to give priority of spectrum use to a small number of primary stakeholders who can then optimize the use of their spectrum for their customers. This approach, however, leads to both the underutilization of the spectrum in some locations at some time, as well as unsatisfied demands. To address this issue, Model-Based Spectrum Management (MBSM), a new approach based on creation and exchange of spectrum consumption models (SCMs), has been proposed. This approach provides computational methods for assessing compatibility among models, serves as a loose coupler for spectrum management systems and enables further extensions of spectrum use and sharing. Spectrum consumption models are expressed in Spectrum Consumption Modeling Markup Language (SCMML) based on the eXtensible Markup Language (XML) schema definition. While expressing SCMs in SCMML is a step towards the formalization of data models, providing a formal syntax for such models, the models cannot be processed by automatic inference engines due to the lack of formal semantics. Instead, SCMs can only be processed by procedural code written for a specific XSD schema. Any updates to XSD would require new code for interpreting the newly introduced tags. In order to avoid such a kind of situation we are advocating the use of a language with formal, computer processable semantics, the Web Ontology Language (OWL). More specifically, we map SCMML to the Cognitive Radio Ontology (CRO) developed at the Wireless Innovation Forum. The paper firstly discusses the concept of Model Based Spectrum Management and Spectrum Consumption Model, and then illustrates the structure of SCM in detail. The method and the procedure of mapping from communicating system models and collections written in XSD to CRO are shown. After that, two use cases are demonstrated in order to show the strength of OWL in terms of automatic inference. The first use case is related to querying reported antenna movements based on location - whether they are acceptable in the area defined by the policy. The second use case shows how an inference engine can infer whether the receiver can tolerate the interfering signal from a remote transmitter. In both cases the BaseVISor inference engine is used to define rules, query the results and infer implicit facts.

This paper presents the performance analyses and rate optimizations of multi-antenna relay-assisted cognitive radio networks. The proposed model consists of a pair of primary users equipped with a single antenna, a number of secondary users with multiple antennas, and a relay station equipped with multiple antennas. In the cognitive radio network, all secondary users communicate with each other through the relay station to achieve a longer range of communication. The relay station uses physical layer network coding to precode the messages and forward the signals to all of the secondary users without causing harmful interference to primary communications. The weighted sum rate is used as the objective criterion under the primary rate constraint. A novel beamforming scheme is proposed for the secondary users and the relay station, which optimizes the rate between them while suppressing the interference to the primary users to an acceptable level. T Simulations were carried out under two different scenarios to compare the performances: one with the channel state information (CSI) and the other without the CSI. It was observed that the secondary rate increases with increases in the number of antennas used at the secondary users and the relay stations. However, the rate increase is bounded by the smallest number of antennas in this cognitive radio system.

In this paper we consider comb-based decimation structure in which the decimation factor can be presented as a power of x, where x is a prime number. Additionally we consider the case where the decimation factor can be presented as a combination of x.

A common signal processing task is to generate a narrow noise time series of a specified bandwidth centered at a selected center frequency. One method generates a wide bandwidth noise series at the output sample rate appropriate for the selected center frequency and then limits the bandwidth around that center frequency with a band pass filter. A second method forms a narrow band base-band noise series at a low sample rate, interpolates up to the required sample rate and then heterodynes the base band sequence to the desired center frequency. In a third method we embed the heterodyne operation in the interpolator by replacing the weights of the low-pass prototype filter with the weights of a band-pass prototype filter. When the center frequency of the band shifted filter is a multiple of the input sample rate, the heterodyne weights factors out of the polyphase arms as a complex rotator per path and the filter operates as a single channel synthesis channelizer. Here the channelizer performs the frequency shift as an alias operation to the channel center frequency during the up-sampling process. Here we include a pre-process frequency offset applied at base band prior to the up-sampling channelizer. We can think of the preprocessor as the fine resolution component of the frequency shift and the alias offset as the course resolution component.

Modulation Classification (MC) is a difficult task that can increase awareness in Cognitive Radio (CR) applications. Much of the research in MC has been for single antenna and single user scenarios. For multiple users, multiple receivers must be used to first separate the incoming signals before MC can be done. For non-cooperative communications blind source separation (BSS) techniques can readily separate a linear mixture of signals, but it is not clear which technique is best suited for MC. In this work, we compare three BSS algorithms as candidates for multi-receiver MC while examining both single and multiple user MC. In our simulations, the fastICA algorithm achieves the best performance of the three. At 0 dB SNR for a single user, the fastICA algorithm achieves 96% correct classification and 92 % for multiple users with three receivers. This work also reveals that the combination of phase correction, fastICA, and support vector machines (SVMs) can achieve near optimal performance.

Among the modulation classification methods, spectral correlation density (SCD) is particularly an attractive solution as it operates effectively under low SNR conditions and is able to classify numerous types of signals. However, computation complexity of the SCD, makes it an impractical solution for real time signal classification. In this study we map the entire SCD flow onto high-end (Tesla-K20) GPU, mobile (Tegra-K1) GPU, and hybrid architecture that couples Tegra-K1 with the Zynq-7000 FPGA as a single lane. The Matlab code running on Intel I5 processor (2.8GHz, 8GB RAM) on average takes 3.2 seconds to process one signal. We show that on the Tesla-K20, execution time is 8.9ms (110 signals/second) with a power consumption of 51W. On the Tegra-K1, we achieve 9 signals/second with a power consumption of 3.5W. The hybrid architecture delivers 19 signals/second with an estimated power consumption of 5W. We then present the model of an eight-lane architecture with a dual ring bus interconnect (scalable to 50 lanes), and show that the throughput is 150 signals/second with an estimated power consumption of around 50W.

In the 3550 MHz band, the FCC proposed the use of Spectrum Access Systems (SAS) to manage interference between commercial and federal systems and between secondary systems. To guide the interference management, the SAS will have to gather significant amounts of real-time data across these networks to detect and analyze potential interference issues as well as possibly determine the presence of mobile incumbent systems and to make appropriate exclusion zone adjustments. Turning this large set of highly dynamic data into actionable information will require the use of sophisticated analysis techniques, such as those proposed in Big Data. Big RF is a term coined by the Wireless Innovation Forum's Cognitive Radio Work Group to refer to the application of Big Data tools and concepts to RF domain problems. The data analysis problem posed by the 3550 MHz band is one example of the kinds of spectrum sharing scenarios where Big RF could help to improve performance. In this paper, we will review Big RF with respect to available tools and their applicability to various spectrum sharing scenarios, including the 3550 MHz band, the 5 GHz band, the proposed Space Ground Link System band (1755 MHz), and other scenarios such as those considered by the DARPA Shared Spectrum Access for Radar and Communications program. The feasibility of performing these real-time analyses will be assessed and privacy issues explored. The paper will conclude with recommendations for deploying Big RF techniques to manage spectrum sharing scenarios.

Radio wave propagation phenomena in a dense urban environment can be simulated using publicly available mapping data and 2-D ray tracing techniques when the receivers and transmitters can be found to be near co-planar. This paper outlines and attempts to validate such a simulation model. Validation is presented in the form of experimental results for a set of trials along with a statistical comparison to simulation results. A significant positive correlation between the experimental and simulation results is found and detailed.

An ontology defines the basic terms in a domain and the relationships among them. It is used to share information in order to facilitate analysis of domain knowledge. In the cognitive radio (CR) domain, two radios an achieve interoperability by exchanging the knowledge about their communication protocols and various parameters. Cognitive Ra- dio Ontology(CRO) was developed to model CR domain using a formative declarative language, the web ontology language (OWL). CRO2 is an updated version of the regular CRO. The updates were made to the top level structure, properties and to the relationships between the classes and objects. Basically, an ontology can be evaluated in terms of 1) coverage of knowledge, 2) inference ability and 3) extendibility. This paper will present an ontology that satisfies these metrics. We will discuss using examples how having a foundational ontology will lead to 1) better inference ability, 2) precision in defining classes and 3) extendibility without violating consistency.

The focus of the tutorial is the design of intelligent agents (IAs) for cognitive radio (CR), also known as cognitive engines (CEs). A CE is an IA that enables the radio to have the desired learning and adaptation abilities. This IA senses its environment (the wireless channel), acts by using a communication method based on its past experience, and observes its own performance to learn its capabilities, adding to its experience base. Our tutorial will explain to the audience the concept of an IA, the factors that need to be considered for developing an IA, and outline the different methods for artificial intelligence and machine learning that can be used to develop an IA for CR. Emphasis will be given to present the IA irrespectively to the specific application and methods used in order for the audience to understand the concept without any bias. This is a limitation of most of the CE designs that are focused on a one or two dominant methods for the development of their IA (CE) such as the genetic algorithm (GA), the case-based-reasoning (CBR) framework, and Bayesian methods. This has the effect of implicitly communicating to the audience that an IA needs to use those methods. Therefore, in our tutorial we want the audience to be clear on its choices for developing an IA by presenting the merits of all the most prominent methods along with examples and simulation tips using that will be presented throughout the tutorial. Finally, the tutorial will present a brief introduction to meta-cognitive agents or CEs which are able to learn the performance of individual IAs under different operating scenarios. This learning allows the meta-cognitive agent to select the appropriate IA or CE for current operating scenarios.

A major shortcoming of current deployed systems is the limitation to operate as half duplex systems employing either a time-division or frequency-division approach to bidirectional communication. This requires dividing the temporal and/or spectral resources into orthogonal resources and thus enforces an artificial limitation on the possible potential of the system. The problem gets compounded in cognitive systems where nodes are constantly scanning and sensing for opportunistic spectrum availability to augment their operating potential. Traditionally, system designers assumed that full duplex systems are infeasible due to the large self-interference imposed by the transmitting antenna on the receive path (within the same transceiver) which in effect, will lead to a saturation of the dynamic range sampled by the analog to digital converter, as well as a reduction in the achievable sensitivity of the receiver. However, we have proven via experimental results that this is not true. In fact, by utilizing a combination of reconfigurable antennas, coupled with new transceiver architectures that benefit from analog and digital cancellation techniques, a reduction of up to 95 dB of the self-interfering signal is achievable, thus allowing for full duplex communication. The experimental platform was used to show a 190% rate improvement over half duplex systems operating under the same conditions.

It is easily demonstrated that the square-root cosine taper is not sufficiently smooth to support low levels of in-band ripple needed to suppress residual ISI and to support high levels of out-of band attenuation needed to meet spectral mask requirements. This paper presents a design technique replacing the cosine Taper with a smoother spectral shape to realize Square-Root Tapered Nyquist shaping filters with significantly reduced levels of spectral in-band ripple and improved out-of band attenuation levels.

The flexible spectrum access and arrangement is a key requirement for future software defined radio (SDR). The capability in spectrum planning not only allows the efficient usage of the white space but can also enhance the system performance. This proposal presents the example of using spectrum fragmenting and defragmenting technique to cope with multipath channels for a wideband single carrier signal. It is well known that the deep channel notches will fail the forward linear equalizer, since any attempt of channel inversion will amplify the additive noise. The decision feedback equalizer (DFE) is a non-linear equalizer that can directly subtract the inter symbol interference (ISI) from the corrupted symbols. However, implementing DFE requires significant hardware resources and accurate prior channel knowledge. Moreover the wrong symbol decisions made by DFE will cause error propagation and likely the failure of the DFE. This paper proposes novel spectrum fragmenting technique that allows spectrum re-planning based on prior channel gain knowledge. For instance, the transmitter can rearrange the shaped signal spectrum to by-pass the channel nulls. The receiver can then re-assemble the fragmented signal back to its demodulatable state. By using the proposed spectrum re-planning technique, the system throughput can be enhanced; the need of DFE is diminished; the spectrum efficiency is enhanced in a flexible manner.

A prototype for an omnidirectional multi-port antenna was developed. This antenna consists of two collinear helical elements that are fed from transceivers having a common local oscillator for phase control. The helical elements are orthogonal. One helix generates a right-hand circular wave, while the other generates a left-hand circularly polarized wave. From these elements, any polarization can be transmitted or received in an omnidirectional pattern by controlling the phase and magnitude of the signals feeding the two elements. Measured results from the prototype show reasonable agreement with the simulated results. The prototypes have a center frequency of 900MHz, and a gain of 1.5dBi. They are cylindrical in overall shape, having a 2¼" diameter and a 2¾" length. This scalable design is suitable for mobile and fixed multiport transceiver deployments.

This presentation will cover the porting experiences of Harris's effort to port the MUOS WF from the JTNC IR to the 117G product. This will go over the use of tool, both COTS and custom made, to assist in the porting efforts. It will also cover some of the key areas of the WF design that could be improved up to ease porting efforts in the future.

There have been noteworthy advances in military tactical communications systems, products and operations over recent years that have moved the so-enabled forces towards a battlefield environment of information dominance. Even with the continually increasing velocity of technological innovation associated with military tactical communications, there are significant challenges at hand, that when solved will not only provide high value and benefit to the users of these systems and a path to information dominance, but have the potential to be extremely disruptive to today's military tactical communications markets. This presentation will explore three critical areas of challenges that require significant industry attention and technical innovation to achieve the opportunity for true information dominance on the battlefield. Potential areas of study and technology development will be identified for each area. 1. Increasing Data Demands "All the Way to the Edge" The growing demand for information flow between various levels of decision making authorities and deployed assets all the way to the edge of the network, including: individual Soldiers, un-manned vehicles, and unattended sensors can greatly overburden spectrum availability and increase the probability of "friendly interference". 2. Information Sharing and Coalition Operations The deployment and utilization of more cooperating multi-national coalition forces across the globe has resulted in an escalating conflict between the need for secure information sharing while at the same time preserving the sovereignty of specific national interests, including the safety and well-being of the Warfighters. 3. Network Reliability State-of the-Art military tactical communications networks continue to be challenged by dynamically changing topologies and connectivity, in conjunction with increasing traffic demands. Significantly increasing the density of deployed network nodes could potentially provide considerably higher overall network reliability (i.e., alternate paths to overcome RF signaling obstructions and traffic flow) and throughput.

Checking the conformance of a SDR equipment to SCA specification is very challenging. We propose in this paper to deal with the issue of providing a toolchain for code certification to SCA 2.2.2 standard. First of all, static and dynamic checking should be considered for waverform and platform certification. Operating environment and board support package will be targeted also. Finally a logical architecture of a certification test bench will be presented as well as its global functional set of requirements.

SCA is around now for some time and is moving forward through updates of the SCA standard. Other standard organizations are also moving forward and have efforts that could help SCA in modernizing further. This presentation will give an overview how new and upcoming standards from the Object Management Group (OMG) can lead to a more modernized SCA standard and implementations. For the standard side we will present about IDL4 and the upcoming Unified Component Model (UCM) and how both upcoming OMG standards can lead to a more modern and simplified SCA standard leading to reduced maintenance efforts of the SCA standard. Related to implementation side (vendors and users) we will give some background and insight in the new OMG IDL to C++11 language mapping. This new language mapping will greatly simplify the development of SCA based systems by using modern constructs like the Standard Template Library (STL). Together with the new language features of C++11 an implementation can provide a safe, but also a better performing implementation. All together this leads to lower development costs and faster time to market for SCA based systems.

An efficient enforcement mechanism is one of the fundamental requirements of a spectrum sharing system. The principal function of an enforcement system includes verification of user access information, subsequent localization of non-compliant users and prompt punitive action to ensure compliance. Fast response time, low computational overhead, and low false alarm rate are some of the desirable characteristics of an enforcement system. For rapid deployment of such an enforcement mechanism it is also desirable from an economic point of view that the localization technique employed by the system is independent of any parameters which require specialized equipment for measurement. Taking these factors into consideration, we outline a localization method and test our results on measured data. Range based techniques for localization that exploit Received Signal Strength (RSS) provide an economic solution to the problem at hand. Because RSS can be measured easily on the receiver side and its measurement does not require any information from the transmitter this approach is suitable for our problem domain, i.e. non-cooperative localization. We particularly concentrate on methods using Differential RSS (DRSS) and Weighted DRSS – both of these methods are independent of the calibration parameter required for techniques exploiting RSS. The performance of WDRSS and DRSS is then compared when they are used on measured data. The measurement campaign was done in Blacksburg, VA, with a transmit antenna emitting a continuous wave tone at 3.395 GHz as a transmit signal. A receiver consisting of an antenna and a mobile spectrum analyzer with a built-in GPS – mounted on a bicycle or a car – was used to measure the signal strength at different locations across Blacksburg. In addition a path loss model is proposed which has a single parameter defined as the link loss parameter. The link loss parameter takes into consideration attenuation due to path loss as well as shadowing. The proposed model is motivated by showing the promise of improved location estimation accuracy provided we have sufficiently accurate estimates of the link loss parameters. A joint optimization problem is formulated which simultaneously estimates the location and the link loss parameters. Finally, some initial results of the joint estimation approach are provided, which highlight the challenges of the link loss model approach to localization, and some avenues for further improvement are proposed.

The coexistence of femtocell and WiFi networks in a heterogeneous spectrum environment with licensed and unlicensed bands will support multi-mode femtocell users (FUs) to simultaneously transmit on both licensed and unlicensed bands. The efficient integration of both femtocell and WiFi technologies is considered crucial for supporting the offload of femtocell traffic to WiFi networks. Therefore, we proposed cognitive-based resource allocations for femtocell networks in case of integrated femtocell-WiFi networks (IFWN)to improve the performance of FUs in terms of the throughput and losing probability. A simulation model using structure MatLab was presented and investigated to evaluate the performance of femtocell networks operate under a mixed spectrum environment of licensed and unlicensed bands. The loss probability and the throughput of FUs as the main performance measures of femtocell networks were obtained. The simulation results show that the retrial phenomenon of FUs together with using the unutilized unlicensed band in an opportunistic manner impact the loss probability and throughput of femtocell networks in IFWN under a mixed spectrum environment of licensed and unlicensed channels. In addition, the proposed scheme shows significant improvements in terms of the throughput of FUs and the probability of loss compared to traditional femtocell operations.

In this paper we propose and simulate an energy efficient protocol for object-tracking over Wireless Sensor Networks. The proposed algorithm aims to use virtual clustering among the observation region to initiate duty-cycle across the border nodes and the nodes in the inside region. The mean idea is to keep the outer nodes active and the interior nodes sleep for energy saving until an object is detected by the outer nodes. Castalia 3.2 wireless sensor network simulator is used to simulate the proposed protocol. Results indicate that an improvement of 42% is achieved in terms of energy consumption. Furthermore, it is demonstrated that S-MAC protocol is a better choice in high load traffic applications in terms of energy consumption.

Note this is for a DEMO presentation A co-primary spectrum sharing trial is presenting a flexible way to share resources between multiple operators in order to increase spectral efficiency. In this trial the differences in traffic patterns of the mobile network operators are exploited to ease up the peak traffic demands of particular operator. This shared recourse is also usable for inter-operator D2D communication, when two users of different operators want to communicate and operators need to negotiate resource allocation for this communication link. We will also introduce Wireless Open Access Research Platform as our choice for the implementation of this trial.

A receiver signal processing methodology and architecture is presented, which achieves conversion of an entire RF band directly to the digital signal domain, converting a digitally selectable RF bandwidth of signals centered at a digitally selectable center frequency. Conversion is realized for the raw input signal band, prior to execution of frequency translation, filtering, or mixing. The converted band is thereby made available within DSP blocks for Post Conversion Mixing, further down-conversion, mixing, and/or channel selective or rejective DSP based filtering. This conversion technique is uniquely flexible, format and protocol ambivalent, equally effective for all forms of modulation, and uniformly applicable for any frequency within the wide-band response capability of whichever fabrication process node it is implemented into. Theoretical performance characteristics and limits are mathematically developed. Comparative analysis for this technique relative to other and more traditional receiver techniques is explored, with consideration given to this technique as the missing link for Software Defined Radio.

In our contribution we will analyze a set of system configurations for BICM-ID receivers (bit interleaved coded modulation with iterative decoding). While the effective number of data bits per modulation symbol is the same for all configurations, the division into code rate and modulation order shall be different. For instance, one configuration might use a rate 1/2 channel code in combination with QPSK-modulation, while in another configuration a rate 1/6 code with 64-QAM might be considered. It can be anticipated that all configurations differ in complexity and performance. In a second step, the originally independently designed configurations shall converge into a single jointly optimized configuration. That means, a common transmitter is designed whose output symbol sequence can be decoded by any of the above mentioned receiver configurations. For that purpose, it is proposed to apply the concepts of Incremental Redundancy to offer different code rates as well as of Hierarchical Modulation for the signal constellation sets of different modulation order. Thanks to these concepts, it is possible to design a transmitter using a rate 1/6 code with 64-QAM and a receiver with a different configuration like rate 1/2 and QPSK.

Digital down conversion to base band consumes considerable power in software defined radio receivers. In this paper, we present and compare the workload of standard down converter architectures: one based on a cascaded integrator-comb (CIC) filter, one based on a cascade of half band filters, one based on polyphase down-samplers, and one based on a polyphase filter bank (PFB). Separate comparisons are made for applications requiring down conversion of a single channel and for multiple channels. Workload analysis is expressed as the number of operations per input sample required to deliver output samples due to the sample rate reduction accompanying the bandwidth reduction process. Workload performance for the dual process, digital up conversion is the same as for digital down conversion and thus is not separately performed.

The Fifth Generation Communication (5G) system is has the several unique feature like: Massive MIMO, Device Centric Communication, Smarter Device-to-Smarter Deice, Native support for Machine-to-Machine Communication and Millimeter wave communication. The expected target for 5G network to achieve the 1000 times more system capacity, 10 times higher spectral efficiency, 100 time more energy efficiency than current network technologies, high data rate (i.e., peak data rate of 10 Gb/s for low mobility and peak data rate of 1 Gb/s for high mobility), and 25 times more average cell throughput with peak consideration of the cost and reliability of the system. The users mobility leads to the handover of device in the neighbor area, it cause the poor connection reliability and high communication cost with risk of connection loss. To address these challenges we are proposing a base station centric Device-to-device communication system, for overlapping area in 5G networks. The multiple signals from Base Station refers to overlapping coverage area, and user must be handover to next location area. For the same we are suggesting the user centric communication (without Base Station interface) to handover the device in adjacent area, until the users finalize the communication. The suggested method will reduce the signaling cost and overheads for the communication.

Industry and academia have started discussions on 5G cellular communications which is being projected as the next generation of cellular communications. Millimeter wave communication technology is a strong potential candidate for 5G communications given the vast attention that it has received by industry and academic research, and given the vast potential for expanded spectrum spaces. Millimeter wave system design, although viewed as novel in the cellular world, has been commonly used in satellite communications, radar, commercial and biomedical applications. Meteorological satellites, such as the MTSAT, operate in ka band (uplink of 27 – 31 GHz). Popular commercial applications include body scanners used by airport security which operates in mm wave frequencies. Airplane navigation support radars operate in the 31 – 36 GHz band. Broadly speaking, the literature discusses the application of heterodyne, superheterodyne, and direct conversion architectures for millimeter wave RF front end design. This paper has three objectives: (a) to survey existing approaches for millimeter wave RF design with focus on system level design aspects of RF signal reception and transmission; (b) evaluate their suitability for 5G communications; and (c) discuss the drawbacks of employing existing cellular RF design approaches for 5G millimeter wave communications. In 5G cellular communications, the RF design is expected to be power efficient and robust (low phase noise), and there is relatively less emphasis on spectral efficiency.

Massive MIMO have been introduced to improve the spectral efficiency. With massive MIMO, the systems having a much larger number of antennas per site than today are considered. Massive MIMO has several benefits which makes this technology an active research area for next generation wireless systems such as 5G. Perfect channel estimation becomes a big challenge since the maximum number of orthogonal training sequences for channel estimation are upper bounded by either the channel coherence time or the interference from the users in neighboring cells. This paper presents the problem of spectrum sharing between a communication system with a massive MIMO capability and MIMO radar. If the interference channels are assumed to be perfectly estimated by the communication users and fed back to the radar without an error, the interference at the communication receivers can be eliminated. We study how the results would change in spectrum sharing between the massive MIMO system and MIMO radar when the interference channels are estimated with linear squares (LS) and linear minimum mean squared error (LMMSE) channel estimation techniques. According to our simulation results, we get worse performance with LMMSE but nearly same performance with LS compared with using the perfect channel. Therefore, we can eliminate interference from MIMO radar even if the channel is not perfectly estimated.

This work discusses some issues related to the implementation of the Future Multiband Multiwaveform Modular Tactical Radio (FM3TR) waveform in two different SCA platforms with similar hardware but different SCA development and deployment environments. Our experimental results showed that a SCA standardization based on XML standard is not enough to ensure the portability of the waveform. Indeed, the files generated by certified SCA 2.2.2 environments may often use specific non-standard IDL interface to generate software components. To corroborate our conclusion, some specific examples of SCA components are discussed. It has also been shown that the real time problem coupled platform degrades the portability of waveform components. Finally, a non-optimal solution called "device" or "black box" software component platform is presented and discussed

Jerry Bickle, Raytheon Vince Kovarik, PrismTech This paper and demonstration describes a component technology neutral implementation approach that is based upon the Joint Tactical Networking Center (JTNC) Software Communications Architecture (SCA). SCA defines specific technologies profiles (e.g., Common Object Request Broker Architect (CORBA), Portable Operating System Interface (POSIX), etc.) that provide the features for portability and reuse of a component technology implementation. SCA allows other middleware communication technologies besides CORBA such as Data Distributions Service (DDS) and POSIX Inter-Process Communications (IPC) (e.g., shared memory, queue, etc.). The direct usage of middleware communication and component frameworks (e.g., SCA 2.2.2 versus SCA 4.X) technologies in a component's implementation makes the implementation portable and reusable only for those technologies. The paper and demonstration will describe the component technology neutral implementation design patterns for middleware communication and component frameworks.

This paper addresses Most Wanted Innovation #2: Certification Process for Third Party Waveform Software. In this paper, we explore the potential for combining model-based development environments supporting automatic code generation with novel static testing technology to accelerate the SCA compliance testing process. Model-based development and automated testing yield higher regularity and predictability, reducing testing complexity and sidestepping some issues for software intended for deployment on multiple hardware platforms. Further, integrating test tools into the development environment can provide immediate feedback on compliance issues during the development process. As testing moves upstream, the load on certification entities is reduced, and correction of issues becomes more straightforward. Pushing the testing upstream also opens the door to increased customization. We introduce Pitchfork, a language technology that allows users to define specifications as sequences of patterns that can be identified in source code. With Pitchfork, it becomes possible to encapsulate both SCA and API properties in a precise, automatically checkable way and distribute them across the SDR community for immediate integration. A natural evolution of this concept is self-certification, in which a robust set of test tools provides a capability for a developer to offer strong evidence of compliance without a formal certification process. Conclusions in this paper are supported with experiences from the use of the NordiaSoft SCA Architect IDE and Reservoir Labs' R-Check SCA compliance test tool.

NASA's Space Communication and Navigation Testbed is becoming a proving ground for adaptive and cognitive space software defined radio applications. As a first step, a variable coding and modulation (VCM) experiment is being conducted on-orbit using the existing launch waveforms. An optional CCSDS AOS framing trailer operational control field is used to send messages about VCM changes to the receiver. A predicted link margin governs the test profile, improving overall throughput by approximately 50% when compared to performance without VCM. In development are adaptive waveforms that will use real-time telemetry, such as received signal-to-noise measurements, to adjust waveform parameters. These adaptive waveforms will not only improve capabilities and performance, but also become the physical layer for future cognitive applications to control and optimize.

The National Institute of Justice is funding the integration of research products from previous, independently derived, NIJ prototypes (or equivalent capabilities) into a single standards-based hardware and software platform which can be used to facilitate further federal research and/or demonstration of new capabilities and in a real-world environment. This platform will allow NIJ to leverage and/or extended software defined/cognitive radio (SDR/CR) and related antenna technology research products into the future, through use of new, standards based, software/hardware architectural features. This integrated platform will be extensible and will allow the introduction of new technologies as standards-compliant products evolve and made commercially available. The architecture chosen for this application utilizes a stackable, physical form factor containing a single board computer, SDR radio, and support for PCIe daughterboards to accommodate COTS radio cards designed for small form factor applications (laptops/tablets etc…), cards which are compatible with standards-based interfaces between system components (currently PC-104 based). The chosen architecture also contains an integrated power supply that will support DC powered operation for demonstration from an automobile. The chosen architecture will also accommodate a number of additional standard interfaces (Ethernet, USB) allowing researchers to interface the system with additional commercial off the shelf equipment, and components that are complementary to this integrated platform. Another goal of this integration process is to provide a hardened field evaluation/demonstration platform for future NIJ research products. This entire assembly will reside in a hardened form factor suitable for field demonstration of newly developed concepts using fragile laboratory prototypes may be prohibited. For example; a primary NIJ goal is to demonstrate SDR/CR based emerging research prototypes and applications in the field. For example new operational and technical capabilities may be demonstrated in an shared public/private wireless public safety broadband network using the integrated platform to demonstrate capabilities derived from previous NIJ research to bond radio channels operating in licensed 4.9GHz public safety spectrum and unlicensed 2.4 GHz Wi-Fi and/or wide area cellular 3G/4G LTE capabilities. Another component of this NIJ funded research is the development of a steerable antenna technology as part of the integration effort, derived from concepts embodied in previous NIJ research. The goal for this task is to provide a tool upon which future cognitive algorithms can be developed to exploit the benefits of evolving antenna technology in a manner that is beneficial to public safety users. This effort includes the development of a steerable antenna assembly with a fully compliant interface allowing control of a directional antenna, in the form of a 4.9 GHz Butler array and the development of basic control software to facilitate demonstrate steering capabilities that may support NIJ's interest in public safety applications. The initial implementation of this antenna array will be designed to specifically support operations at 4.9 GHz, but the expectation overall design will be adaptable, or extended to facilitate operations in other bands. The resulting architecture can provide flexible tool for integrating and evaluating software defined radio and cognitive radio hardware and software technology.

Various prototype/laboratory friendly RF front-end hardware such as the Ettus Research Universal Software Radio Peripheral (USRP) devices, in combination with software interfaces such as GNU Radio, can be used to design and implement a Software Defined Radio (SDR) system. One major limitation on use of these devices is that they are un-calibrated in terms of power or voltage and hence give the results in relative terms/counts. This poses a disadvantage in many scenarios where parameters such as power measured in mW or dBm, and voltage measured in mVolts are used to design, implement, and test devices and systems and to collect and interpret experimental results. Connectivity with these metrics is needed to ensure that the USRP devices are not confined to proof of concept implementation and demonstrations, and to realize more fully their potential utility for experimentation. In this research an attempt has been made to calibrate the USRPN210 (with WBX daughter board) in order to make the result-set clearer and easily understandable. Several experiments were conducted to understand and characterize the performance of the USRP under different conditions. Experiments such as determination of 1-dB compression point, Third order intercept point helped understand the linearity range of the device under transmitter and receiver operations. Variation of transmitted power with respect to gain helped derive a reference table for transmitted power, which could be used for future experiments. Conducting these experiments over a sample of 10 USRPs helped in obtaining standardized values and benchmarking them. The factors obtained were also used in some experiments like path loss modeling, position location estimation in order to determine their effectiveness and impact on such applications. A decrement in the received power as the frequency increased was observed in the USRP. The 3rd order input intercept point for USRPN210 device with WBX board obtained without the applied correction factor showed almost a 30 dB deviation from the expected value while the IIP3 value with the correction factor applied showed a deviation of around 1~2 dB. The calibration factors obtained through the experiments were used on practical applications like multi-floor path loss exponent determination and position location. It was evident that with calibration, the results obtained were closer to the expected values, reducing the position location mean square error factor from 0.72 to 0.66. Though much research is ongoing in the field of software-defined radios, low and moderate-cost RF front-end devices and quantitative measurements obtained when using popular SDR software with these devices are not fully characterized. Calibration is a step closer to enabling these devices to support a wider range of real-world applications. Much potentially valuable documentation in terms of useful reference metrics is lacking and experiments that explore the performance abilities of RF front-end devices help provide a useful reference for researchers.

Platform for signal collection, storage, and processing based on a Windows computer. Signals are processed by an original joint detection algorithm that increases simultaneous dynamic range of detection of OFDM signals to 40 dB. The paper describes the JD algorithm and the system that includes an integrated USRP SDR, GIS-enabled database -- postgresQL/postgis -- and tool for displaying results on a map. Representative results are provided and discussed. The system is intended for use as a high-dynamic range, inexpensive signal collection and processing platform for wireless networks T&M and R&D.

Spectrum sharing has become an area of great interest in future communications. It has been accelerated in the US by the President's directive to the US Government to share portions of its spectrum with the commercial world. The foundation for this was laid in the US by the PCAST (President's Council of Advisors on Science and Technology) report. Similar efforts are being undertaken in Europe as well. An important understanding that has been developing recently is the idea that wireless is now an integral part of Critical Infrastructure (CI) and therefore, Critical Infrastructure Protection (CIP) by necessity requires the protection of vulnerabilities in Wireless Communications as well, especially those that can be used to disable key sectors in CI, such as nuclear, oil and gas power plants, refineries, Bridges, and dams. SCADA networks and more advanced forms of M2M communications are now integral to the operation and safety of CI. Spectrum sharing throws another twist into the mix. When some major incident happens, and hence, traffic volume goes up, congestion and delay could have deleterious consequences on the safe and stable operation or at least the optimum operation of the CI. In cases where there is significant damage to some element of CI, rerouting of functions (or power in the case of the smart grid) requires reliable and well understood traffic paths to execute protection and disconnection strategies. Spectrum sharing adds several unknowns and also vulnerabilities to this scenario. It could also provide additional ways in which someone wishing to do harm could magnify the effects of the incident by additional cyber-attacks via the links that provide the spectrum sharing. The paper examines some of these scenarios and discusses opportunities from and challenges to this approach. It should help heighten awareness of potential real world consequences which need to be taken into account as these systems are designed and deployed. Plans for implementing the concepts in a safe test bed are also discussed.

In military, unmanned aerial systems (UAS) already outnumber traditional manned aircraft systems. The physical aircraft is referred to as unmanned aerial vehicle (UAV) or, simply, unmanned aircraft (UA). UAVs tend to be small and light and UAV technology is fairly well-developed and development as well as maintenance costs are significantly lower than that of traditional manned aircraft systems. Not only are UAVs cost-efficient, but their application for the governmental as well as for the commercial sector are versatile: transportation, communication infrastructure for commercial industries and humanitarian and public security for national governments, amongst others. For instance, as part of Google Project Loon, high altitude and large-scale UAV eNodeBs are proposed as alternatives for terrestrial eNodeBs. Small and Micro UAVs (SUAV/MAV) are a more cost-efficient, low-altitude approach to small dense scenarios of mobile relaying. Aerovironment is using SUAVs to examine the applicability of UAVs to re-establish communication after natural or man-made disaster. Recent predictions, conducted by the US National Transportation Center, reveal that the number of UAVs for commercial and national purposes in the near future will outnumber UAVs owned by DoD by at least a factor of 10 in 2035. In very high quantities micro and small UAVs will be deployed due to economics of scale with sizes of less then 10 feet and weights below 55 pounds. Their communication links will predominately be based on LOS mode as their range is limited. The overall goal is to safely integrate these types of UAVs into the existing airspace, in particular Class E and G of controlled and uncontrolled airspace. It is expected that the advancement in UAS technology and benefits of UAS for commercial and governmental operations will bring along new challenges: safety of operation and real-time exchange of throughput-intensive data. Both challenges reduce to the fundamental problem in wireless communications: spectrum management. UAV spectrum in the 1755 MHz band is considered for relocation in the US and worldwide spectrum allocation for future UASs will be disucssed in the next upcoming World Radiocommunications Conference (WRC). The exchange of rich contents data, streaming (HD) video require a significant amount of spectrum proportional to the desired throughput/quality. When the air becomes more crowded, more bandwidth will be needed to accommodate communication needs to share the data captured by the sensors in real time. Bandwidth calculations done by ITU are rather pessimistic as they only account for time-sparse video data exchange for S&A applications in environments with relatively low UAV densities. Enough dedicated spectrum to support throughput-intensive UAV communications over the horizon will not be available. Spectrum sharing is an efficient concept to satisfy bandwidth demand in an opportunistic manner, when and where needed. Very little research on UAS spectrum sharing has been done so far. This paper will analyze to what extent spectrum sharing can be applied to UAV LOS applications for commercial and governmental purposes. This includes an analysis of the extent of UAV-GCS (ground control station) link interference with existing ground communication networks. Interference analysis will be the main reference to evaluate whether sensing or database spectrum access systems or a mix of both are realizable. Efficient 3D network topologies, such as for terrestrial networks, may be deployable to allow for frequency reuse and minimal UAV to UAV interference as well as minimal UAV to ground interference. In order to obtain potential topologies, the mutual influence of ground and aerial-based network is determined. Factors that are taken into account are: 3D antenna patterns, existing ground network topologies, Master slave vs. regular UAV network topology for data transmission, transmit powers, appropriate path loss models and frequency-selectivity of communication channels.

The use of unmanned aerial systems (UAS) for military ISR (intelligence, surveillance and reconnaissance) applications is already of standard practice. Applicability of UAS, however, is not limited to military ISR only, but also deployable on a broad basis in various civilian scenarios: crop monitoring and spraying in agriculture, land survey and pipeline security in gas and oil supply companies, survey and disaster control by local authorities, atmosphere sampling and analysis for meteorological services as well as research work to be conducted in the aeronautical field (Austin, 2011). The integration of the physical aircraft component in a UAS, a so-called unmanned aerial vehicle (UAV) in non-segregated airspace heavily relies on command and control communication links. Ideally, the design of UAS communications links accounts for challenges in aircraft speed as well as range in a spectrum-efficient and reliable manner. Orthogonal Frequency Division Multiplexing (OFDM) is considered to be superior to single-carrier modulation. Recent work by Jain et al. analyzes L-Band Digital Aeronautical Communication Systems of Type 1 and Type 2 (L-DACS1 and L-DACS2) for wireless links in UAS. L-DACS1 uses multi-carrier modulation similar to WiMAX and L-DACS2 is related to GSM. The authors conclude L-DACS1 enhanced performance over L-DACS2 identified by spectrum flexibility and efficiency as well as interference avoidance and coexistence properties. An OFDM transceiver waveform (https://github.com/fr3lm0) has been created to facilitate wireless communications education and research with focus spectrum sharing and UAV communications. The open-source waveform is capable of transmitting and receiving simultaneously, using frequency-division duplexing (FDD) to accomplish this. The waveform employs automatic repeat request (ARQ), using ACKs and NACKs along with configurable timeouts to guarantee payload delivery from a stationary base station node to a UAV node. Written in C++ using the liquid-dsp library, the waveform provides as a flexible platform for research on novel communications systems and spectrum management for UAVs. It provides a large number of parameters, allowing for a wide variety of configurations. It can make use of Ettus USRPs for the RF hardware and runs on the Ubuntu operating system. A live-usb system was created that includes the waveform and has been used to perform experiments by mounting the system on a remote-controlled unmanned ground vehicle (UGV). This paper will show how the waveform can be used in education to understand the components and features of OFDM wireless communications systems: cyclic prefix extension, OFDM modulator, coding and rate matching, ARQ, and so forth. We will show how this waveform can be used for supporting research on new spectrum management approaches for UASs. This includes emerging spectrum management principles towards a more flexible and dynamic resource allocation. The testing will use CORNET testbed facilities and mobile nodes. Other promising DoD and civilian applications of OFDM-based wireless communication systems will also be discussed.

Autonomous Vehicles can benefit greatly from the use of cellular infrastructure. Consequently, it may be desirable at times to consider the availability of this infrastructure when planning autonomous vehicle routes. In order to make such decisions it is necessary to have up-to-date knowledge of signal strength in surrounding areas. We consider the quality of routing possible when using incomplete knowledge of signal strength along a route. As our motivation for how signal strength information would be constrained we consider Vehicle to Vehicle communications. Such communications offer great promise in creating real-time signal maps through a decentralized data collection and aggregation process. One might envision such a process involving the transfer of signal reception information between cars within an area. Such a process, while low-latency and low-cost, could suffer from limited data availability beyond relatively short ranges. In order to route based on signal strength we employ a weighting formula to combine distance and signal strength into a single cost quantity. Then, we apply this formula to a city grid map with signal strength information. We replace the distance values with the formula's aggregate cost values. The cost values are then presented to a shortest path routing algorithm to determine the lowest cost path. Finally, we simulate a vehicle which regularly updates a signal map of its surroundings and continuously updates its route in response. The costs of its chosen path and the cost of the ideal path are then recorded. In order to rigorously test our routing formula's performance with varying degrees of information we employ a Matlab program that randomly generates thousands of city signal maps to run the routing formula and algorithms on. The routing algorithms are run with route signal knowledge between 0% and 100%. We chart the average ratio between partial knowledge and full knowledge path costs. We consider the performance of a variety of algorithms and conclude that using Dijkstra we may produce routes that are 95% optimal using a signal knowledge window only 1/10 of our total route size. These results indicate the potential for excellent routing even when V2V communication can only offer highly constrained data sets. However, the use of random maps potentially weakens our results as real world signal maps tend to be patterned and non-random. Such patterns are extremely problematic as there is great potential for scenarios that do not occur frequently in a randomly generated map and that require extensive map knowledge. For example, the need to find an exit to a signal dead-zone One might view our randomized maps as presenting the signal knowledge limited algorithm a series of local minima optimization problems. In a random map with extremely high signal value variance there is likely to be a variety of immediately visible signal dead-zones and strong signal zones that all have small sizes and are consistently intermixed. As a result, a knowledge limited algorithm can easily avoid a high cost path by moving between small strong signal zones while avoiding the interspersed dead zones with little advanced knowledge. We expect that the most relevant metric for signal formula routing performance may be the ratio between the median size of extreme signal zones and the size of the signal knowledge window. This ratio directly determines the ability of the path cost minimization algorithm to solve path cost as a series of local minima. In order to test the potential value of this metric we tweak our random map generation algorithm to assign a random signal values to increasing numbers of intersections. For example, we might assign each random value to 4x4 intersection grids. Then, we would apply that single value to 8x8 grids. This modification allows us to directly alter the size of extreme signal zones and test the performance of the routing algorithm as extreme signal zones outsize the size of the signal knowledge window.

Advancements in wireless communication systems are giving rise to newer technologies of communication not only between multiple mobile devices, but also between mobile devices and any kinds of machines. Moreover, frequency bands that are higher than the Ultra high frequency (UHF), range of 300 MHz to 3 GHZ, will be used for the next generation of communication systems. Vehicular communications is one of the advancing areas, with numerous potential applications such as safety, reduction of traffic congestion, and entertainment. Dedicated Short Range Communications (DSRC), centered at the 5.9 GHZ band, is currently used as the propagation standard for Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication systems. The IEEE 802.11p standard has been formulated specifically for describing the PHY and MAC layer parameters of DSRC-based vehicular communication. However, despite of a growing interest in this area, there are very few simulations of the PHY Layer of DSRC available. Performance analysis of DSRC that uses high frequency is needed and has potential to support current and new policies and regulations. Our paper mainly focuses on a Simulink-based design of the 802.11p PHY layer, and a study of the performance of this simulated model in different kinds of realistic noise, interference, and fading environments. This DSRC PHY simulator consists of a transmitter and receiver, both created based on IEEE 802.11p standards, and a user-configurable multipath/noise channel.

In this work, we show how a distributed sensing network consisting of very low-cost nodes can also be used to locate radio transmitters without prior knowledge of which waveform is used. This information can aid in increasing location awareness among cognitive radios, as well as provide assistance in locating offending transmitters. The low accuracy of the internal clocks of these low-cost receivers as well as the geographical distribution of the nodes result in significant challenges regarding the synchronization of the receivers in order to position the source with adequate accuracy. In this paper, we synchronize the nodes to an arbitrary modulated RF signal, after which we calculate estimated time differences of arrival (TDOAs) to an unknown transmitter. We describe the implementation as well as give results on measurement accuracy in various scenarios using a prototype network of nodes spread out in the city of Turku, Finland.

The continuing need for Radio Frequency spectrum has led to an increasing interest in spectrum sharing between radar and communications systems. Sharing has been attempted in C-band (between radar and WiFi access points) and is proposed for S-Band. Meanwhile, DARPA's SSPARC program is developing new communications-radar spectrum sharing technologies. The presentation and paper present a taxonomy of the three classes of radar-communications spectrum sharing techniques; Avoid, Accept and Amalgamate – the three 'A's. The various schemes that have been proposed and/or are under development are mapped into the three classes. The three A's formulation is used to discuss the current status of radar-communications spectrum sharing, potential directions for future research, and provide context for radar-communications spectrum sharing business cases. It is shown that there are different business cases associated with each of the three 'A's.

A (new method) is proposed to control the generated interference between coexistent MIMO radar and MIMO cellular base-station. This new method is based on a subspace expansion using the polynomial method. The polynomial method is more flexible in controlling generated interference compared to the previous methods mentioned in literature. This method, with some modifications can be used as a general control method in any MIMO based system. It is a useful tool to improve the ratio of generated interference to radar performance.

Our paper deals with a Dynamic Spectrum Access (DSA) and its implementation on a Software Defined Radio (SDR) for the IEEE 802.15.4e Networks. The network nodes select the carrier frequency after Energy-Detection based Spectrum Sensing (SS). To ensure frequency hoping between two nodes in IEEE 802.15.4e Network, we propose a synchronization algorithm. We consider that the IEEE 802.15.4e Network is Secondary User (SU), and all other networks are Primary Users (PUs) in unlicensed 868/915 MHz and 2450 MHz bands of a Cognitive Radio (CR). The algorithm and the energy-sensor are implemented over GNU Radio and Universal Software Radio Peripheral (USRP) SDR. In addition, real packet transmissions is performed in two cases. In the first case, SU communicates with a static carrier-frequency, while in the second case with the implemented DSA. For each case, PU transmitter disturbs SU, which calculates Packet Success Rate (PSR) to measure the robustness of a used DSA. The obtained PSR is improved by 80% when the SU accomplished DSA rather than a static access.