Cluster-based cooperative subcarrier sensing using antenna diversity-based weighted data fusion

Cooperative spectrum sensing (CSS) is used in cognitive radio (CR) networks to improve the spectrum sensing performance in shadow fading environments. Moreover, clustering in CR networks is used to reduce reporting time and bandwidth overhead during CSS. Thus, cluster-based cooperative spectrum sensing (CBCSS) has manifested satisfactory spectrum sensing results in harsh environments under processing constraints. On the other hand, the antenna diversity of multiple input multiple output CR systems can be exploited to further improve the spectrum sensing performance. This paper presents the CBCSS performance in a CR network which is comprised of single- as well as multiple-antenna CR systems. We give theoretical analysis of CBCSS for orthogonal frequency division multiplexing signal sensing and propose a novel fusion scheme at the fusion center which takes into account the receiver antenna diversity of the CRs present in the network. We introduce the concept of weighted data fusion in which the sensing results of different CRs are weighted proportional to the number of receiving antennas they are equipped with. Thus, the receiver diversity is used to the advantage of improving spectrum sensing performance in a CR cluster. Simulation results show that the proposed scheme outperforms the conventional CBCSS scheme

Sensing-Throughput Tradeoff for Interweave Cognitive Radio System: A Deployment-Centric Viewpoint

Secondary access to the licensed spectrum is viable only if interference is avoided at the primary system. In this regard, different paradigms have been conceptualized in the existing literature. Of these, Interweave Systems (ISs) that employ spectrum sensing have been widely investigated. Baseline models investigated in the literature characterize the performance of IS in terms of a sensing-throughput tradeoff, however, this characterization assumes the knowledge of the involved channels at the secondary transmitter, which is unavailable in practice. Motivated by this fact, we establish a novel approach that incorporates channel estimation in the system model, and consequently investigate the impact of imperfect channel estimation on the performance of the IS. More particularly, the variation induced in the detection probability affects the detector's performance at the secondary transmitter, which may result in severe interference at the primary users. In this view, we propose to employ average and outage constraints on the detection probability, in order to capture the performance of the IS. Our analysis reveals that with an appropriate choice of the estimation time determined by the proposed model, the degradation in performance of the IS can be effectively controlled, and subsequently the achievable secondary throughput can be significantly enhanced.Comment: 13 pages, 10 figures, Accepted to be published in IEEE Transactions on Wireless Communication

SRML: Space Radio Machine Learning

Space-based communications systems to be employed by future artificial satellites, or spacecraft during exploration missions, can potentially benefit from software-defined radio adaptation capabilities. Multiple communication requirements could potentially compete for radio resources, whose availability of which may vary during the spacecraft\u27s operational life span. Electronic components are prone to failure, and new instructions will eventually be received through software updates. Consequently, these changes may require a whole new set of near-optimal combination of parameters to be derived on-the-fly without instantaneous human interaction or even without a human in-the-loop. Thus, achieving a sufficiently set of radio parameters can be challenging, especially when the communication channels change dynamically due to orbital dynamics as well as atmospheric and space weather-related impairments. This dissertation presents an analysis and discussion regarding novel algorithms proposed in order to enable a cognition control layer for adaptive communication systems operating in space using an architecture that merges machine learning techniques employing wireless communication principles. The proposed cognitive engine proof-of-concept reasons over time through an efficient accumulated learning process. An implementation of the conceptual design is expected to be delivered to the SDR system located on the International Space Station as part of an experimental program. To support the proposed cognitive engine algorithm development, more realistic satellite-based communications channels are proposed along with rain attenuation synthesizers for LEO orbits, channel state detection algorithms, and multipath coefficients function of the reflector\u27s electrical characteristics. The achieved performance of the proposed solutions are compared with the state-of-the-art, and novel performance benchmarks are provided for future research to reference

Cognitive Radio Connectivity for Railway Transportation Networks

Reliable wireless networks for high speed trains require a significant amount of data communications for enabling safety features such as train collision avoidance and railway management. Cognitive radio integrates heterogeneous wireless networks that will be deployed in order to achieve intelligent communications in future railway systems. One of the primary technical challenges in achieving reliable communications for railways is the handling of high mobility environments involving trains, which includes significant Doppler shifts in the transmission as well as severe fading scenarios that makes it difficult to estimate wireless spectrum utilization. This thesis has two primary contributions: (1) The creation of a Heterogeneous Cooperative Spectrum Sensing (CSS) prototype system, and (2) the derivation of a Long Term Evolution for Railways (LTE-R) system performance analysis. The Heterogeneous CSS prototype system was implemented using Software-Defined Radios (SDRs) possessing different radio configurations. Both soft and hard-data fusion schemes were used in order to compare the signal source detection performance in real-time fading scenarios. For future smart railways, one proposed solution for enabling greater connectivity is to access underutilized spectrum as a secondary user via the dynamic spectrum access (DSA) paradigm. Since it will be challenging to obtain an accurate estimate of incumbent users via a single-sensor system within a real-world fading environment, the proposed cooperative spectrum sensing approach is employed instead since it can mitigate the effects of multipath and shadowing by utilizing the spatial and temporal diversity of a multiple radio network. Regarding the LTE-R contribution of this thesis, the performance analysis of high speed trains (HSTs) in tunnel environments would provide valuable insights with respect to the smart railway systems operating in high mobility scenarios in drastically impaired channels

On robust and secure wireless communication system design using software-defined radios

This dissertation is composed of three parts: airborne multi input multi output (MIMO) communications, physical layer authentication, and software radio design for DARPA Spectrum Challenge. A common theme for the three distinct problems is the system perspective that we have adopted throughout this dissertation. Instead of considering isolated issues within these problems, we have provided a holistic design approach to the three problems and have implemented all three systems using the GNU Radio/USRP (Universal Software Radio Peripheral) platform. In the first part, we develop a MIMO communication system for airborne platforms. MIMO communication has long been considered to be suitable only for environment that is rich in scatterers. This, unfortunately is not the case for airborne platforms. However, this lack of scattering can be compensated by the large aperture of the airborne MIMO platform; this is corroborated by our careful analysis using real measurement data. Our analysis of the airborne MIMO channels leads to the development of a variable rate MIMO transceiver architecture. This architecture is numerically shown to improve the bit error rate (BER) over conventional transceiver architectures that are developed for rich scattering environments. A software radio based MIMO system is then implemented to demonstrate experimentally the efficacy of the developed architecture. In the second part, we develop a physical layer authentication scheme as a counter measure to primary user emulation attack (PUEA) in cognitive radio (CR) networks. In this attack, a malicious user emulates the signal characteristics of the primary user (PU) when it is silent which prevents unsuspecting secondary user (SU) from utilizing the network. The developed physical layer authentication is based on embedding cryptographic hash signatures, referred to as authentication tags, within PU\u27s signal constellations. The embedding is performed such that the legacy receivers are not affected. We analyze the scheme using the fast fading Rayleigh channel model and present an optimal scheme to embed signals in PU\u27s constellations which minimizes the tag BER. Experimental results are obtained that corroborate our theoretical claims, thereby establish that reliable authentication can be achieved without sacrificing signal quality at the primary receivers. In the final part, we describe in detail our design of software radios developed as part of the DARPA Spectrum Challenge (DSC), a year long competition that started in January 2013 and concluded in March 2014 with the final tournament held in Arlington, VA at the DARPA headquarter. DSC was comprised of two tournaments, competitive and cooperative. In the competitive mode two radio pairs, each composed of a transmitter and a receiver, are pitted against each other to transmit the most amount of data error-free while operating concurrently in the same frequency band. In the cooperative mode, three radio pairs have to share a frequency band in a cooperative manner wherein the goal is to maximize the throughput of all the three pairs. We describe the design of our software radio system that integrates some key technologies crucial in operating in an environment that does not allow user coordination and spectrum pre-planning, including: spectrum sensing, adaptive transmission both in spectrum utilization and transmission rate, opportunistic jamming, and sliding window feedback. The developed radio is robust in the presence of unknown interference and achieves the desired balance between throughput and reliability in an uncoordinated transmission environment