Joint Spectrum Sensing and Resource Allocation for OFDM-based Transmission with a Cognitive Relay

In this paper, we investigate the joint spectrum sensing and resource allocation problem to maximize throughput capacity of an OFDM-based cognitive radio link with a cognitive relay. By applying a cognitive relay that uses decode and forward (D&F), we achieve more reliable communications, generating less interference (by needing less transmit power) and more diversity gain. In order to account for imperfections in spectrum sensing, the proposed schemes jointly modify energy detector thresholds and allocates transmit powers to all cognitive radio (CR) subcarriers, while simultaneously assigning subcarrier pairs for secondary users (SU) and the cognitive relay. This problem is cast as a constrained optimization problem with constraints on (1) interference introduced by the SU and the cognitive relay to the PUs; (2) miss-detection and false alarm probabilities and (3) subcarrier pairing for transmission on the SU transmitter and the cognitive relay and (4) minimum Quality of Service (QoS) for each CR subcarrier. We propose one optimal and two sub-optimal schemes all of which are compared to other schemes in the literature. Simulation results show that the proposed schemes achieve significantly higher throughput than other schemes in the literature for different relay situations.Comment: EAI Endorsed Transactions on Wireless Spectrum 14(1): e4 Published 13th Apr 201

Robust Power and Subcarrier Allocation for OFDM-based Cognitive Radio Networks Considering Spectrum Sensing Uncertainties

‎In this paper‎, ‎we address power and subcarrier allocation for cooperative cognitive radio (CR) networks in the presence of spectrum sensing errors‎. ‎First‎, ‎we derive the mutual interference of primary and secondary networks affecting each other by taking into account spectrum sensing errors‎. ‎Then‎, ‎taking into account the interference constraint imposed by the cognitive network to the primary user and the power budget constraint of cognitive network‎, ‎we maximize the achievable data rates of secondary users‎. ‎Besides‎, ‎in a multi secondary user scenario‎, ‎we propose a suboptimal but low complexity power and subcarrier allocation algorithm to solve the formulated optimization problem‎. ‎Our numerical results indicate that the proposed power loading scheme increases the cognitive achievable data rates compared to classical power loading algorithms that do not consider spectrum sensing errors‎

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

Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks

In cognitive radio (CR) networks, there are scenarios where the secondary (lower priority) users intend to communicate with each other by opportunistically utilizing the transmit spectrum originally allocated to the existing primary (higher priority) users. For such a scenario, a secondary user usually has to trade off between two conflicting goals at the same time: one is to maximize its own transmit throughput; and the other is to minimize the amount of interference it produces at each primary receiver. In this paper, we study this fundamental tradeoff from an information-theoretic perspective by characterizing the secondary user's channel capacity under both its own transmit-power constraint as well as a set of interference-power constraints each imposed at one of the primary receivers. In particular, this paper exploits multi-antennas at the secondary transmitter to effectively balance between spatial multiplexing for the secondary transmission and interference avoidance at the primary receivers. Convex optimization techniques are used to design algorithms for the optimal secondary transmit spatial spectrum that achieves the capacity of the secondary transmission. Suboptimal solutions for ease of implementation are also presented and their performances are compared with the optimal solution. Furthermore, algorithms developed for the single-channel transmission are also extended to the case of multi-channel transmission whereby the secondary user is able to achieve opportunistic spectrum sharing via transmit adaptations not only in space, but in time and frequency domains as well.Comment: Extension of IEEE PIMRC 2007. 35 pages, 6 figures. Submitted to IEEE Journal of Special Topics in Signal Processing, special issue on Signal Processing and Networking for Dynamic Spectrum Acces

CROSS-LAYER RESOURCE ALLOCATION SCHEME UNDER HETEROGENEOUS CONSTRAINTS FOR NEXT GENERATION HIGH RATE WPAN

International audienceIn the next generation wireless networks, the growing demand for new wireless applications is accompanied with high expectations for better quality of service (QoS) fulfillment especially for multimedia applications. Furthermore, the coexistence of future unlicensed users with existing licensed users is becoming a challenging task in next generation communication systems to overcome the underutilization of the spectrum. A QoS and interference aware resource allocation is thus of special interest in order to respond to the heterogeneous constraints of the next generation networks. In this work, we address the issue of resource allocation under heterogeneous constraints for unlicensed multi-band ultra-wideband (UWB) systems in the context of Future Home Networks, i.e. WPAN. The problem is first studied analytically using a heterogeneous constrained optimization problem formulation. After studying the characteristics of the optimal solution, we propose a low-complexity suboptimal algorithm based on a cross-layer approach that combines information provided by the PHY and MAC layers. While the PHY layer is responsible for providing the channel quality of the unlicensed UWB users as well as their interference power that they cause on licensed users, the MAC layer is responsible for classifying the unlicensed users using a two-class based approach that guarantees for multimedia services a high-priority level compared to other services. Combined in an efficient and simple way, the PHY and MAC information present the key elements of the aimed resource allocation. Simulation results demonstrate that the proposed scheme provides a good tradeoff between the QoS satisfaction of the unlicensed applications with hard QoS requirements and the limitation of the interference affecting the licensed users

Resource Allocation for Downlink Multi-Cell OFDMA Cognitive Radio Network Using Hungarian Method

This paper considers the problem of resource allocation for downlink part of an OFDM-based multi-cell cognitive radio network which consists of multiple secondary transmitters and receivers communicating simultaneously in the presence of multiple primary users. We present a new framework to maximize the total data throughput of secondary users by means of subchannel assignment, while ensuring interference leakage to PUs is below a threshold. In this framework, we first formulate the resource allocation problem as a nonlinear and non-convex optimization problem. Then we represent the problem as a maximum weighted matching in a bipartite graph and propose an iterative algorithm based on Hungarian method to solve it. The present contribution develops an efficient subchannel allocation algorithm that assigns subchannels to the secondary users without the perfect knowledge of fading channel gain between cognitive radio transmitter and primary receivers. The performance of the proposed subcarrier allocation algorithm is compared with a blind subchannel allocation as well as another scheme with the perfect knowledge of channel-state information. Simulation results reveal that a significant performance advantage can still be realized, even if the optimization at the secondary network is based on imperfect network information