Feedback Strategies for Multiantenna Multiuser Systems

Abstract

In this chapter, we focus on the different feedback strategies for the case of a multiuser wireless communication system with multiple transmitter and receiver antennas. Firstly, we analyze the capacity of the multiuser MIMO system with single receive antenna for uplink and downlink by assuming that the full channel state information (CSI) is available at the transmitter. Secondly, we examine the precoding and user selection algorithms for MIMO multiuser systems with one and multiple receive antennas in flat fading and frequency selective wireless channels. Since optimal precoding using dirty paper coding has a prohibitively high computational complexity due to the associated encoding process, it is a great practical interest to design MIMO multiuser systems with low complexity and a minimum CSI requirement at the transmitter side. One suboptimal approach is to apply linear precoding schemes, such as zero forcing beamforming (ZF-BF) or minimum mean square error criterion. Multiuser MIMO wireless communication with ZF-BF requires a brute-force exhaustive search over all possible user sets and the complexity of an exhaustive search is prohibitive when the number of users is large. In order to decrease the complexity of this search, several suboptimal user scheduling algorithms have been designed. Generally, these algorithms fall into two categories: Capacity-based and Frobenius norm-based algorithm. Lastly, we show the effect of reduced and limited feedback information including user selection at the receiver side and quantization for both single carrier and multicarrier transmissions. We perform user selection at the user side since the users having a poor channel (low norm or/and interference) should not take part in the user selection algorithm, nor feedback their channel information. By using a self-discrimination criterion at the receiver side, it is possible to reduce the feedback load and the complexity of the user selection algorithm at base station. We show different user selection criteria and quantization strategies to reduce feedback load for both single and multicarrier communication systems.