Scaled SLNR Precoding for Cognitive Radio

In this paper, we propose and analyze a lowcomplexity precoding scheme for cognitive radio networks. We consider a secondary user, equipped with multiple transmit antennas, that is allowed to access the spectrum of the primary network only if it does not interfere to the reception of the primary users. The proposed precoder is based on the signal to leakage plus noise ratio (SLNR) criterion, with additional scaling to comply with the cognitive constraint. The proposed Scaled SLNR (SSLNR) scheme is attractive for practical cognitive wireless networks as it combines near optimal performance with low implementation complexity. The SSLNR parameter is optimized using stochastic geometry analysis of an alternative gated zero-forcing scheme. The optimal parameter value is shown to depend only on the system parameters and not on the primary network density. Simulations results demonstrate the accuracy of the optimization, and show that the performance of the resulting SSLNR scheme is close to the performance of the optimal solution.