Throughput analysis of multi‐antenna cognitive broadcast networks

In this study, the authors analyse the throughput of random beamforming (RBF) for a multi‐antenna cognitive radio (CR) broadcast network. Using extreme value theory, the asymptotic average throughput of a single‐beam RBF and a multiple‐beam RBF are derived from the limiting distribution of the sample maximum of received signal‐to‐noise ratio (signal‐to‐interference‐plus‐noise ratio) with maximal ratio combiner at the secondary user. It is shown that the throughput of the single‐beam RBF scales as logarithm of the number of users, which stands in contrast to the double logarithm of the number of users in non‐CR networks. They also found that the single‐beam RBF is always much preferable to the multi‐beam RBF on the throughput in the CR networks, which is opposite to the previous results in the non‐CR networks. Simulation results show that the author's approximated expressions match with the simulation results very well.