Per-subcarrier antenna selection for OFDMA-based cognitive radio systems

The performance of an OFDM system can be improved by performing per-subcarrier antenna selection, which facilitates the exploitation of frequency and spatial diversity in the wireless channel. In this paper, we extend the concept of per-subcarrier antenna selection to a multiuser cognitive radio environment and present a practical subcarrier and antenna selection algorithm that exploits the multiuser, frequency and spatial diversities inherent in such systems while requiring only limited channel knowledge. The problem is formulated as an integer programming (IP) problem. We demonstrate that a linear relaxation of the problem still leads to an optimal solution, thus reducing the computational complexity relative to other approaches found in the literature. Simulation results demonstrate that the proposed resource allocation problem leads to an improvement in secondary users' link qualities, compared to a single-input single-output system and, at the same time, limits the interference to the primary user.