Sensing-based resource allocation in multi-channel cognitive radio networks

Abstract

In this paper, we investigate the resource allocation issue for cooperative sensing-based cognitive radio networks (CRNs). The CRN consists of multiple secondary users (SUs) and a secondary base station (SBS), and implements a two-phase protocol. In the first phase, cooperative spectrum sensing is carried out to detect the vacant channels in a primary user network. In the second phase, the SUs transmit data in the uplink to the SBS. We optimize the sensing parameters, transmit power and channel assignments of the SUs jointly to minimize the total energy consumption with the constraints on the SUs' quality of service and detection probability of the primary users. We represent the problem as a bilevel optimization problem, in which the slave subproblem is to optimize the resource allocation parameters for any given sensing parameter, whereas the master subproblem is to optimize the sensing parameters. To benchmark the performance of our proposed joint optimization solution, we study the separate optimization, in which the sensing parameters of SUs are set regardless of the allocated resources. Numerical results show that, our proposed joint optimization method can introduce up to 15.07% and 15.6% energy saving with the total transmission bandwidth of 1.25 MHz and 2.5 MHz, respectively.