Cluster based cooperative spectrum sensing for cognitive radios

Abstract

Wireless communication standards have been evolved by the researchers and developersfor further enhancements and changes. Where as these wireless systems havemostly ended up in increased spectrum allocations along with increased data rates. Resultantly,development of these enhanced data rate wireless standards also introducedexcessive spectrum deficiency. Due to which further research on concepts of SoftwareDefined Radio (SDR) and Cognitive Radio (CR) gain momentum. This laid the base ofintelligent devices for accessing the spectrum for unlicensed users. Spectrum Sensing(SS) is used as the main initiator analysis tool which helps development of awarenessin CR. CR is considered as possible solution for the radio spectrum congestion issue. The main objective of CR is to detect the free spectrum and to use it with nearly zero percentinterference with the Primary Users (PUs) present in the environment. CRs can sensethe free spectrum individually but the chances of error are more as there is a huge probability of the hidden node problem and error (in sensed spectrum) due to fading channel. To clear away these issues and to increase reliability of the decision of sensed spectrum the CRs collaborate with each other to reach the more accurate final decision. Idea of cooperation and clustering amongst CR network has recently been focus of attention of research community, owing to its potential to enhance performance of SS techniques, which has led to the paradigm of Cluster Based Cooperative SS (CBCSS). In the perspective of high data rate 4th generation wireless systems, which are characterizedby Orthogonal Frequency Division Multiplexing (OFDM) and spatial diversity,there is a need to devise effective SS strategies. A novel CBCSS scheme is proposed for OFDM subcarrier detection in order to enable the non-contiguous OFDM at the physical layer of CRs for efficient utilization of spectrum holes. Proposed scheme is based on the energy detection in MIMO CR network, using equal gain combiner as diversity combining technique, hard combining (AND, OR and Majority (MAJ)) rule as data fusion technique and antenna diversity based weighted clustering as virtual sub clustering algorithm. Results of proposed CBCSS are compared with conventional CBCSS scheme for AND, OR and MAJ data fusion rules. Moreover the effects of antenna diversity, cooperation and cooperating clusters are also discussed. The simulation results show that proposed scheme outperforms the conventional CBCSS scheme. Moreover, OR rule is preferable for achieving better detection performanceand AND rule is better for the scenarios where lesser false alarms are required.The presence of CRs with multiple number of antennas improves the performance of aCBCSS scheme hence weights should be assigned to give priority to the decisions of CRs with more number of antennas.