Quantization bit allocation for reporting-throughput tradeoff in cooperative cognitive radio networks

Abstract

In cognitive radio (CR) networks, secondary users (SUs) detect and share a spectrum band assigned to a primary user (PU) to communicate with their respective secondary receivers. In order to increase the reliability of the detection performance, the SUs cooperatively sense the spectrum by reporting their local information to a fusion center (FC) after quantization. For an accurate information transferring, the use of the enormous number of quantization bits for reporting is preferred, however, it simultaneously degrades the throughput performance in the perspective of reporting-throughput tradeoff. To tackle this problem, in this paper, we focus on the throughput enhancement for the secondary networks while satisfying a target sensing performance. To this end, we derive the quantized local test statistics of energy detector and propose the quantization bit allocation strategy which maximizes the throughput performance. Moreover, we introduce an adaptive framework to employ the proposed resource allocation scheme in a dynamic environment. Also, we investigate some general mobility models for computer simulation. Through the numerical results, it is shown that the proposed works exhibit the enhanced throughput performance compared to the conventional schemes even under various scenarios.