Throughput optimization for cognitive radios under sensing uncertainty
Rajgopal Kannan, Shuangqing Wei, Jian Zhang, Athanasios V. Vasilakos · 2010
The efficiency of a cognitive radio system depends critically on sensing reliability since post-sensing communication efficiency is subject to optimal resource allocation under this sensing uncertainty. In this paper, we develop online algorithms for maximizing throughput in a cognitive radio when the sensing outcome of the primary channel (available/unavailable) is not always reliable. We first develop a very efficient per-slot power allocation algorithm for a secondary user transmitting under total power constraints over a period of M time slots, assuming reliable sensing during each slot but with no look-ahead capability. Specifically, we show that it is always possible to achieve a transmission rate that is a constant fraction of the optimal transmission rate even with no apriori knowledge of the number of available slots. Our online power-allocation algorithm is 3.7-competitive, i.e the rate achieved by this algorithm is within a factor of 2.5/ln 20(1), for example √(M)), we show that no online algorithm can achieve a constant-factor competitive ratio.