Abstract: In multi-user massive (MIMO) wireless system, where the base station equipped with a large number of antennas simultaneously serves multiple users, user selection algorithms have become a rising concern. Two user selection algorithms, in which both channel quality and multi-user interference are taken in account, were proposed. The one is implemented by combining 1-bit feedback and minimizing the preceding vector correlation, it can effectively reduce the computation complexity; In the other algorithm, the list of users is got from potential users by comparing the preceding vector correlation with a threshold, then a set of users with the largest sum of the channel gain were selected, so the sum capacity is further improved. The performance and complexity of algorithms are analyzed.

Key words: multi-user selection, quantized precoding, sum capacity, feedback overhead, computation complexity