Complexity Optimization for Cooperative Sensing Using Coalition Games

Cognitive radio is a far effective method to solve the problem of limited spectrum resources in the wireless communication in cloud manufacturing, involved in kinds of networks. Cooperative spectrum sensing, as a research hotspot in cognitive radio, can improve the sensing quality in cognitive radio networks, but it will also bring in extra cost when forming coalitions and conduct cooperative spectrum sensing. Although CSS based on coalition formation games can significantly conquer this problem by improving the sensing quality and at the same time reducing extra cost, it is much too complex with many nodes. In this paper, we analyze the complexity of the proposed coalition formation (CF) algorithm, and then present an enhanced Selecting SUs and Coalition Formation (SSCF) algorithm where coalition formation and cooperative spectrum sensing is carried out with SUs selected before. In addition, it is shown that SSCF can lower the complexity of CF by reducing the number of nodes for coalition formation while hardly bringing down the sensing quality of CF with at most 0.5% decrease of utility in common case and at average 3% increase of that.