An improved user selection algorithm in multiuser MIMO broadcast with channel prediction

In multiuser MIMO-BC (Multiple-Input Multiple-Output Broadcasting) systems, user selection is important to achieve multiuser diversity. The optimal user selection algorithm is to try all the combinations of users to find the user group that can achieve the multiuser diversity. Unfortunately, the high calculation cost of the optimal algorithm prevents its implementation. Thus, instead of the optimal algorithm, some suboptimal user selection algorithms were proposed based on semiorthogonality of user channel vectors. The purpose of this paper is to achieve multiuser diversity with a small amount of calculation. For this purpose, we propose a user selection algorithm that can improve the orthogonality of a selected user group. We also apply a channel prediction technique to a MIMO-BC system to get more accurate channel information at the transmitter. Simulation results show that the channel prediction can improve the accuracy of channel information for user selections, and the proposed user selection algorithm achieves higher sum rate capacity than the SUS (Semiorthogonal User Selection) algorithm. Also we discuss the setting of the algorithm threshold. As the result of a discussion on the calculation complexity, which uses the number of complex multiplications as the parameter, the proposed algorithm is shown to have a calculation complexity almost equal to that of the SUS algorithm, and they are much lower than that of the optimal user selection algorithm.