A Greedy Adaptive Sensor Set Selecting Algorithm under Correlated Log-normal Shadowing

摘要

The problem of optimal sensor set (OptSS) selection in cognitive radio networks is considered in this paper. Although the method of cooperative spectrum sensing can greatly improve the sensing performance, the consumption of system resources will increase as the number of sensors increases, therefore, the number of sensors to use is a compromise between sensing performance and consumption of system resources. Firstly, the definition of OptSS is given out. Then a relational expression between the number of sensors of OptSS and the minimum distance between each pair of sensors of OptSS is derived, based on which an optimal selecting method of OptSS is acquired. Lastly, a suboptimal adaptive selecting algorithm of OptSS based on greedy with a lower complexity is proposed, which not only obtains the near-optimal solution rapidly, but also adapts to the variety of dynamic network topologies. Analysis and simulation results demonstrate the effectiveness and reliability of the proposed greedy adaptive sensor set selecting algorithm.