Resource allocation for cognitive radio networks with a beamforming user selection strategy

In this paper we address the problem of resource allocation in the context of cognitive radio networks (CRN). With the deployment of K antennas at the cognitive base station (CBS), an efficient transmit beamforming technique combined with user selection is proposed to maximize the uplink throughput and satisfy the signal-to-noise and interference ratio (SNIR) constraint, as well as to limit interference to the primary user (PU). In the proposed user selection algorithm, secondary users (SUs) are first pre-selected so as to maximize the per-user sum capacity subject to minimize the mutual interference. Then, the PU verifies the outage probability constraint and a number of SUs are selected from those pre-selected SUs. Simulation results show that our proposed method exhibits a significant number of cognitive users able to transmit while minimizing interference to guarantee QoS for the PU. We also compare the results obtained by the proposed method to those obtained using a binary power allocation method. The reported results demonstrate the efficiency of the proposed technique to maximize the SU rate while maintaining a QoS to a PU, and its superiority to the binary power allocation.