A Low Complexity PMI/RI Selection Scheme in LTE-A Systems

Recent wireless radio technologies have utilized precoding matrix and rank adaptation as a technique to increase frequency efficiency. In 3rd generation partnership project (3GPP) long term evolution (LTE) and LTE-advanced (LTE-A) systems, codebook based precoding is utilized. In the codebook based system, a mobile station (MS) needs to estimate optimum channel state information (CSI) which includes a channel quality indicator (CQI), a precoding matrix indicator (PMI) and rank indicator (RI) and to feed back the CSI to the base station (BS) in order to get higher frequency efficiency. Generally, the MS estimates the optimum precoding matrix from all possible precoding matrices which are predefined as the codebook. When such an exhaustive search algorithm is utilized in LTE-A MS, the MS needs huge computation power because the number of rank and precoding matrix patterns is large in a LTE-A system. In this paper, we propose a novel PMI/RI selection algorithm which is less complex than the exhaustive search algorithm in a LTE-A system. After evaluating the throughput performances by simulation and analyzing the computations, it is described that the proposed algorithm has the same throughput performances as the conventional algorithm and 13% of the computations compared with the conventional algorithm.