Abstract
In this work, we consider the problem of a Multiple-Input Single-Output (MISO) Multiple-Access Channel with a large number of users K. In practical scenarios, only a small sub-set of the users can be scheduled simultaneously. However, since solutions which collect Channel State Information (CSI) from all users and schedule the best subset to transmit do not scale with K, distributed scheduling algorithms are advantageous. We analyze a distributed scheduling algorithm, which selects a group of users to transmit without coordinating between the users and without all users sending CSI to the base station. The expected capacity under Minimum Mean Squared Error (MMSE) decoding is given, with a special emphasis on large K. It is shown that the algorithm achieves the same scaling laws as the optimal centralized scheme.
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