Quantization-Based Multibit Combination for Cooperative Spectrum Sensing

In the realm of cognitive radio (CR), the soft and hard combinations are commonly applied for the fusion rule of cooperative spectrum sensing (CSS) to detect the primary user (PU) signal for available vacant spectrum resources and allow cooperative secondary users (SUs) to opportunistically access the channel without harmful interference to the PU’s normal communication. However, in the process of submitting the sensing information to the fusion center (FC), the soft combination requires great communication overhead from the SU to the FC, and the hard combination reports only one bit of the local decision resulting in unsatisfactory detection performance. In view of this, in this paper we make an in-depth investigation on the quantization of raw measurement data and propose a quantization-based multi-bit combination method that utilizes the information of each sampling point. On the basis of the proposed multi-bit combination approach, each SU quantifies the information obtained from the local sensing information and transmits the quantified sensing data in a few bits to the FC. Furthermore, we formulate an optimization problem for the error probability of the multi-bit combination to achieve the optimal CSS performance. Finally, numerical simulation results confirm the effectiveness and robustness of the proposed multi-bit combination method, establishing its superiority in various environments, in terms of the overall error probability.