Collaborative spectrum sensing in multi-channel cognitive networks: A coalition game approach

Collaborative spectrum sensing among secondary users (SUs) in cognitive radio (CR) networks is shown to yield a significant performance improvement. However, much previous work in CR networks focus on single channel sensing performed by SU cooperatively while spectrum sensing on multiple channels is largely ignored. In order to overcome the foregoing shortcoming, coalition game theory is introduced. In this paper, we mainly study the throughput maximization problem which considers optimizing the network throughput and channel sensing period synchronously. Moreover, the the missing detection and false alarm probability are also constrained. Then a modified merge and split algorithm (MMSA) is designed. Extensive simulation results illustrate that the proposed MMSA algorithm can significantly improve the overall network throughput and guarantee low missing detection and false alarm probability for channels.