Capacity Upper Bound of Channel Assembling in Cognitive Radio Networks With Quasistationary Primary User Activities

Abstract

In cognitive radio networks (CRNs) with multiple channels, various channel-assembling (ChA) strategies may be applied to secondary users (SUs), resulting in different achieved capacity. However, there is no previous work on determining the capacity upper bound (UB) of ChA for SUs under given system configurations. In this paper, we derive the maximum capacity for CRNs with ChA through Markov chain modeling, considering that primary user (PU) activities are relatively static, compared with SU services. We first deduce a closed-form expression for the maximum capacity in a dynamic ChA strategy and then demonstrate that no other ChA strategy can provide higher capacity than that achieved by this dynamic strategy.