Non-Uniform Quantization based Reporting in Cooperative Cognitive Radio

Abstract

In this paper we propose a non-uniform quantization technique for reporting the test statistics computed by local cognitive radio (CR) sensors to the fusion center. Local CR sensors are assumed to compute the test statistics based on conventional energy detection technique and fusion center on accumulating the respective test statistics makes final decision about presence or absence of primary user (PU). In order to communicate the test statistics to the fusion center over a band limited channel, the locally computed test statistics are quantized using d bit non-uniform quantizer. The number of bits can be selected on the basis of system specification or amount of backhaul communication that can be supported by the system. The proposed non-uniform quantization is performed on the basis of likelihood function, which is defined as the probability of null and alternate hypothesis when test statistic is known. Next at fusion center the reported local quantized test statistics are combined using optimal weights to get global test statistic. Finally the global test statistic is compared with a threshold to decide for presence or absence of PU. Our simulation results illustrate that the performance of proposed non-uniform quantization is better than conventional uniform quantization.