Cooperative Spectrum Sensing in Narrowband Cognitive Radio

Abstract

The advancement in wireless communication technologies and rapid growth in bandwidth hungry application has aggravated the need for efficient utilization of the spectrum resource. Cognitive radio (CR) has emerged as a promising solution to the present problem of spectrum crisis. It increased the efficiency of spectrum utilization by allowing secondary/unlicensed user to coexist with the primary/licensed user in a particular spectrum band. The stringent requirement is a reliable and efficient spectrum sensing technique. In this thesis both hard and soft combination based cooperative spectrum sensing techniques has been investigated. The local CR sensors sense the energy of a specified narrow band and report the data or the preliminary decision to the fusion center.
Double threshold based hard decision combining is reinvestigated in this thesis where the local CR sensors use two thresholds instead of one. When the sensed energy falls within the two thresholds no decision is made. Majority based decision combination is used at the fusion center to combine the local reliable decisions from the CR sensors. Analytical expressions of probability of sensing error and probability of false alarm are derived as a function of the width of the ambiguity region (region between the two thresholds). Using the analytical and simulation results it is shown that there exists an optimal value of the width of ambiguity region for which the performance is optimum. Finally an optimization problem is formulated solving which the optimum width of ambiguity region can be found.
Next, a soft decision based cooperative cognitive radio is investigated, where a non-uniform quantization technique is proposed prior to reporting. The quantization of the locally sensed energies controls the backhaul bandwidth required for reporting the data. The non-uniform quantization is done based on the likelihood function, which is the probability that a particular decision is correct given a value of sensed energy. At the fusion center the reported locally detected energies are combined using optimized combining weights, obtained by minimizing a generated cost function, to get the global test statistic. The simulation results shows that the performance of proposed non-uniform quantization is better than that of the conventional uniform quantization for a specified number of bits.