Sum-rate maximising in cognitive MIMO ad-hoc networks using weighted MMSE approach

This reported work focuses on weighted sum-rate maximisation (WSRM) of cognitive radio ad-hoc networks, where a K user multiple-input multiple-output interference network (K-MIMO-IFN) uses the same spectrum with a licenced primary user. Because the WSRM problem in K-MIMO-IFN is non-convex and it is difficult to get an optimal solution directly, the weighted minimum mean square error (MMSE) approach is used to make the problem easier to handle. This report then proposes a dual-MMSE-algorithm, which iteratively finds a local optimal solution and only needs the local channel knowledge. Simulation results show that the proposed algorithm outperforms other conventional algorithms.