Adaptive Random Access for Cooperative Spectrum Sensing in Cognitive Radio Networks
In this paper, an adaptive cooperative spectrum sensing scheme using random access is proposed in a cognitive radio network. Although cooperative spectrum sensing improves the performance of spectrum sensing considerably, the problem of how to collect sensing data should be solved for the implementation of the cooperative sensing. This is not an easy problem because complicated coordination between secondary users paprticipating in the cooperative sensing is required. This study addresses this problem in an environment of unequal SNR values of primary user signal at the secondary users. In the proposed scheme, random access is used to collect the spectrum sensing data of the secondary users during collection period and the length of the collection period is determined adaptively based on the sensing data collected so far. Thus, complex slot management for the collection of the sensing data is not necessary. This adaptive determination of the collection period is formulated as a finite-horizon decision problem. Backward induction approach is employed to decide the optimal stopping time of the collection period. In addition, a heuristic algorithm is proposed, which almost equals the performance of the backward induction method and whose time complexity is much smaller than the backward induction scheme. Analysis of the proposed scheme is also provided. Numerical results show that the proposed scheme performs much better than other conventional methods.