A Best Group selection algorithm to maximize capacity of MIMO Gaussian broadcast channels

In this paper the problem of maximizing the multi-user capacity of Gaussian multiple-input multiple-output (MIMO) broadcast channels (BC) under total power constraint is considered. Although dirty-paper coding (DPC) is capacity achieving for this channel, employing dirty-paper coding is a computationally complex non-convex problem. To deal with this problem, many algorithms use iterative procedures to find the optimal solution. However, when the number of active users is large, these algorithms introduce a high order of complexity and suffer from memory drawback. Best Group (BG) selection is a method to address this problem. We propose a new BG selection algorithm that when is used jointly with the iterative dirty paper coding algorithm, provides acceptable results. The main feature of the proposed algorithm is that it is more efficient in a sense of computationally complexity than the similar algorithms. In addition as our simulation results show the proposed algorithm not only is much faster than similar algorithms, but also, it has very negligible reduction in the BC capacity.