Spectrum sensing by cognitive radios at very low SNR

Spectrum sensing is one of the enabling functionalities for cognitive radio (CR) systems to operate in the spectrum white space. To protect the primary incumbent users from interference, the CR is required to detect incumbent signals at very low signal-to-noise ratio (SNR). In this paper, we present a spectrum sensing technique based on correlating spectra for detection of television (TV) broadcasting signals. The basic strategy is to correlate the periodogram of the received signal with the a priori known spectral features of the primary signal. We show that according to the Neyman-Pearson criterion, this spectral correlation-based sensing technique is asymptotically optimal at very low SNR and with a large sensing time. From the system design perspective, we analyze the effect of the spectral features on the spectrum sensing performance. Through the optimization analysis, we obtain useful insights on how to choose effective spectral features to achieve reliable sensing. Simulation results show that the proposed sensing technique can reliably detect analog and digital TV signals at SNR as low as -20 dB.Comment: IEEE Global Communications Conference 200

Removing non-stationary noise in spectrum sensing using matrix factorization

Spectrum sensing is key to many applications like dynamicspectrum access (DSA) systems or telecom regulators who need to measure utilization of frequency bands. The International Telecommunication Union (ITU) recommends a 10 dB threshold above the noise to decide whether a channel is occupied or not. However, radio frequency (RF) receiver front-ends are non-ideal. This means that the obtained data is distorted with noise and imperfections from the analog front-end. As part of the front-end the automatic gain control (AGC) circuitry mainly affects the sensing performance as strong adjacent signals lift the noise level. To enhance the performance of spectrum sensing significantly we focus in this article on techniques to remove the noise caused by the AGC from the sensing data. In order to do this we have applied matrix factorization techniques, i.e., SVD (singular value decomposition) and NMF (non-negative matrix factorization), which enables signal space analysis. In addition, we use live measurement results to verify the performance and to remove the effects of the AGC from the sensing data using above mentioned techniques, i.e., applied on block-wise available spectrum data. In this article it is shown that the occupancy in the industrial, scientific and medical (ISM) band, obtained by using energy detection (ITU recommended threshold), can be an overestimation of spectrum usage by 60%

A Comparative Study Of Spectrum Sensing Methods For Cognitive Radio Systems

With the increase of portable devices utilization and ever-growing demand for greater data rates in wireless transmission, an increasing demand for spectrum channels was observed since last decade. Conventionally, licensed spectrum channels are assigned for comparatively long time spans to the license holders who may not over time continuously use these channels, which creates an under-utilized spectrum. The inefficient utilization of inadequate wireless spectrum resources has motivated researchers to look for advanced and innovative technologies that enable an efficient use of the spectrum resources in a smart and efficient manner. The notion of Cognitive Radio technology was proposed to address the problem of spectrum inefficiency by using underutilized frequency bands in an opportunistic method. A cognitive radio system (CRS) is aware of its operational and geographical surroundings and is capable of dynamically and independently adjust its functioning. Thus, CRS functionality has to be addressed with smart sensing and intelligent decision making techniques. Therefore, spectrum sensing is one of the most essential CRS components. The few sensing techniques that have been proposed are complicated and come with the price of false detection under heavy noise and jamming scenarios. Other techniques that ensure better detection performance are very sophisticated and costly in terms of both processing and hardware. The objective of the thesis is to study and understand the three of the most basic spectrum sensing techniques i.e. energy detection, correlation based sensing, and matched filter sensing. Simulation platforms were developed for each of the three methods using GNU radio and python interpreted language. The simulated performances of the three methods have been analyzed through several test matrices and also were compared to observe and understand the corresponding strengths and weaknesses. These simulation results provide the understanding and base for the hardware implementation of spectrum sensing techniques and work towards a combined sensing approach with improved sensing performance with less complexity

Resource Management in Multicarrier Based Cognitive Radio Systems

The ever-increasing growth of the wireless application and services affirms the importance of the effective usage of the limited radio spectrum. Existing spectrum management policies have led to significant spectrum under-utilization. Recent measurements showed that large range of the spectrum is sparsely used in both temporal and spatial manner. This conflict between the inefficient usage of the spectrum and the continuous evolution in the wireless communication calls upon the development of more flexible management policies. Cognitive radio (CR) with the dynamic spectrum access (DSA) is considered to be a key technology in making the best solution of this conflict by allowing a group of secondary users (SUs) to share the radio spectrum originally allocated to the primary user (PUs). The operation of CR should not negatively alter the performance of the PUs. Therefore, the interference control along with the highly dynamic nature of PUs activities open up new resource allocation problems in CR systems. The resource allocation algorithms should ensure an effective share of the temporarily available frequency bands and deliver the solutions in timely fashion to cope with quick changes in the network. In this dissertation, the resource management problem in multicarrier based CR systems is considered. The dissertation focuses on three main issues: 1) design of efficient resource allocation algorithms to allocate subcarriers and powers between SUs such that no harmful interference is introduced to PUs, 2) compare the spectral efficiency of using different multicarrier schemes in the CR physical layer, specifically, orthogonal frequency division multiplexing (OFDM) and filter bank multicarrier (FBMC) schemes, 3) investigate the impact of the different constraints values on the overall performance of the CR system. Three different scenarios are considered in this dissertation, namely downlink transmission, uplink transmission, and relayed transmission. For every scenario, the optimal solution is examined and efficient sub-optimal algorithms are proposed to reduce the computational burden of obtaining the optimal solution. The suboptimal algorithms are developed by separate the subcarrier and power allocation into two steps in downlink and uplink scenarios. In the relayed scenario, dual decomposition technique is used to obtain an asymptotically optimal solution, and a joint heuristic algorithm is proposed to find the suboptimal solution. Numerical simulations show that the proposed suboptimal algorithms achieve a near optimal performance and perform better than the existing algorithms designed for cognitive and non-cognitive systems. Eventually, the ability of FBMC to overcome the OFDM drawbacks and achieve more spectral efficiency is verified which recommends the consideration of FBMC in the future CR systems.El crecimiento continuo de las aplicaciones y servicios en sistemas inal´ambricos, indica la importancia y necesidad de una utilizaci´on eficaz del espectro radio. Las pol´ıticas actuales de gesti´on del espectro han conducido a una infrautilizaci´on del propio espectro radioel´ectrico. Recientes mediciones en diferentes entornos han mostrado que gran parte del espectro queda poco utilizado en sus ambas vertientes, la temporal, y la espacial. El permanente conflicto entre el uso ineficiente del espectro y la evoluci´on continua de los sistemas de comunicaci´on inal´ambrica, hace que sea urgente y necesario el desarrollo de esquemas de gesti´on del espectro m´as flexibles. Se considera el acceso din´amico (DSA) al espectro en los sistemas cognitivos como una tecnolog´ıa clave para resolver este conflicto al permitir que un grupo de usuarios secundarios (SUs) puedan compartir y acceder al espectro asignado inicialmente a uno o varios usuarios primarios (PUs). Las operaciones de comunicaci´on llevadas a cabo por los sistemas radio cognitivos no deben en ning´un caso alterar (interferir) los sistemas primarios. Por tanto, el control de la interferencia junto al gran dinamismo de los sistemas primarios implica nuevos retos en el control y asignaci´on de los recursos radio en los sistemas de comunicaci´on CR. Los algoritmos de gesti´on y asignaci´on de recursos (Radio Resource Management-RRM) deben garantizar una participaci´on efectiva de las bandas con frecuencias disponibles temporalmente, y ofrecer en cada momento oportunas soluciones para hacer frente a los distintos cambios r´apidos que influyen en la misma red. En esta tesis doctoral, se analiza el problema de la gesti´on de los recursos radio en sistemas multiportadoras CR, proponiendo varias soluciones para su uso eficaz y coexistencia con los PUs. La tesis en s´ı, se centra en tres l´ıneas principales: 1) el dise˜no de algoritmos eficientes de gesti´on de recursos para la asignaci´on de sub-portadoras y distribuci´on de la potencia en sistemas segundarios, evitando asi cualquier interferencia que pueda ser perjudicial para el funcionamiento normal de los usuarios de la red primaria, 2) analizar y comparar la eficiencia espectral alcanzada a la hora de utilizar diferentes esquema de transmisi´on multiportadora en la capa f´ısica del sistema CR, espec´ıficamente en sistemas basados en OFDM y los basados en banco de filtros multiportadoras (Filter bank Multicarrier-FBMC), 3) investigar el impacto de las diferentes limitaciones en el rendimiento total del sistema de CR. Los escenarios considerados en esta tesis son tres, es decir; modo de transmisi´on descendente (downlink), modo de transmisi´on ascendente (uplink), y el modo de transmisi´on ”Relay”. En cada escenario, la soluci´on ´optima es examinada y comparada con algoritmos sub- ´optimos que tienen como objetivo principal reducir la carga computacional. Los algoritmos sub-´optimos son llevados a cabo en dos fases mediante la separaci´on del propio proceso de distribuci´on de subportadoras y la asignaci´on de la potencia en los modos de comunicaci´on descendente (downlink), y ascendente (uplink). Para los entornos de tipo ”Relay”, se ha utilizado la t´ecnica de doble descomposici´on (dual decomposition) para obtener una soluci´on asint´oticamente ´optima. Adem´as, se ha desarrollado un algoritmo heur´ıstico para poder obtener la soluci´on ´optima con un reducido coste computacional. Los resultados obtenidos mediante simulaciones num´ericas muestran que los algoritmos sub-´optimos desarrollados logran acercarse a la soluci´on ´optima en cada uno de los entornos analizados, logrando as´ı un mayor rendimiento que los ya existentes y utilizados tanto en entornos cognitivos como no-cognitivos. Se puede comprobar en varios resultados obtenidos en la tesis la superioridad del esquema multiportadora FBMC sobre los sistemas basados en OFDM para los entornos cognitivos, causando una menor interferencia que el OFDM en los sistemas primarios, y logrando una mayor eficiencia espectral. Finalmente, en base a lo analizado en esta tesis, podemos recomendar al esquema multiportadora FBMC como una id´onea y potente forma de comunicaci´on para las futuras redes cognitivas

COGNITIVE RADIO SOLUTION FOR IEEE 802.22

Current wireless systems suffer severe radio spectrum underutilization due to a number of problematic issues, including wasteful static spectrum allocations; fixed radio functionalities and architectures; and limited cooperation between network nodes. A significant number of research efforts aim to find alternative solutions to improve spectrum utilization. Cognitive radio based on software radio technology is one such novel approach, and the impending IEEE 802.22 air interface standard is the first based on such an approach. This standard aims to provide wireless services in wireless regional area network using TV spectrum white spaces. The cognitive radio devices employed feature two fundamental capabilities, namely supporting multiple modulations and data-rates based on wireless channel conditions and sensing a wireless spectrum. Spectrum sensing is a critical functionality with high computational complexity. Although the standard does not specify a spectrum sensing method, the sensing operation has inherent timing and accuracy constraints.This work proposes a framework for developing a cognitive radio system based on a small form factor software radio platform with limited memory resources and processing capabilities. The cognitive radio systems feature adaptive behavior based on wireless channel conditions and are compliant with the IEEE 802.22 sensing constraints. The resource limitations on implementation platforms post a variety of challenges to transceiver configurability and spectrum sensing. Overcoming these fundamental features on small form factors paves the way for portable cognitive radio devices and extends the range of cognitive radio applications.Several techniques are proposed to overcome resource limitation on a small form factor software radio platform based on a hybrid processing architecture comprised of a digital signal processor and a field programmable gate array. Hardware reuse and task partitioning over a number of processing devices are among the techniques used to realize a configurable radio transceiver that supports several communication modes, including modulations and data rates. In particular, these techniques are applied to build configurable modulation architecture and a configurable synchronization. A mode-switching architecture based on circular buffers is proposed to facilitate a reliable transitioning between different communication modes.The feasibility of efficient spectrum sensing based on a compressive sampling technique called "Fast Fourier Sampling" is examined. The configuration parameters are analyzed mathematically, and performance is evaluated using computer simulations for local spectrum sensing applications. The work proposed herein features a cooperative Fast Fourier sampling scheme to extend the narrowband and wideband sensing performance of this compressive sensing technique.The précis of this dissertation establishes the foundation of efficient cognitive radio implementation on small form factor software radio of hybrid processing architecture