Abstract
We present centralized-based iterative algorithms that jointly determine the optimal transceiver filters as well as the optimum power allocation for a $K$ -user multiple-input multiple-output (MIMO) interference channel (IC). The optimality criterion is developed on the basis of the average per user multiplexing gain and the achievable sum-rate in the MIMO IC. By allowing channel state information (CSI) exchanged between base stations (BSs) and a central unit (CU), we design a feedback topology where CU collects local CSIs from all BSs, computes all transceiver filters and sends them to corresponding user-BS pairs. Note that the local CSIs at BSs are obtained from the estimation of the channel states during the so-called uplink-training phase. At the CU, using the alternating optimization strategy, various iterative algorithms are proposed to design the filters. In other related studies, the equal transmit power policy for all user-BS pairs is chosen ignoring the essential need to search for the optimal power allocation policy; they do not take the full advantage of the system’s total power. Thus, another key aspect of this paper is to make optimal power allocation decisions for all the user-BS pairs based on the sum-rate maximization strategy and under a sum power constraint.
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