The hypothesis that base station can acquire full channel station information (CSI) is the precondition of the research above, but it is impossible in real systems. So in recent years, the more actual system models have attracted more and more research attentions, for example, the ralph lauren polo shirts performance of multi-user MIMO systems and the algorithms to eliminate inter-user interference and so on. Considering both perfect CSI and partial CSI, the respective multi-user selection algorithms are studied in this dissertation. In general, this dissertation mainly discusses as follows:(1) In case of perfect CSI, by considering multi-user MIMO downlink systems, an upper bound of sum-rate capacity is given, and then a suboptimal adaptive user selection algorithm is proposed. Regard current capacity and the upper bound as the adaptive criterions. The performance of the proposed algorithm is near to the optimal method in Lacoste Polo Shirts different SNRs and with different number of users. Based on this method, a fair scheduling scheme is further given to ensure fair service to all users in the system. Users with poor Lacoste Polo Shirts channel condition can also be served while keeping relatively high data rate.(2) In case of partial CSI, an Lacoste Shirts antenna feedback algorithm is proposed, so that, the multi-user MIMO systems transform to the multi-user multiple input single output (MISO) systems. In this equivalent system model, current Cheap Lacoste Polo Shirts capacity-based algorithm and channel correlation-based algorithm are used to select available user subset. The performance of the former one is enhanced obviously with the same computational complexity and the number of bits back to the base station. The latter one is a litter worse, but its computational complexity reduces a lot. The two different algorithms are conformable to different actual systems.
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