Linear Precoding and Decoding for Multiple Input Multiple Output (mimo) Wireless Channels

Space-time coding and spatial multiplexing are prime candidates for achieving high data rates and link quality in multiple-input multiple-output (MIMO) wireless links. However, both the schemes assume no channel knowledge at the transmitter. In a number of applications, channel knowledge can be made available at the transmitter. A natural question to ask is how to use these channel estimates to further optimize the transmitter. There can be several ways to linearly or non-linearly optimize the transmitter and receiver depending on channel knowledge. In this thesis, we consider linear optimization schemes at the transmitter (precoding) and receiver (decoding) to improve performance of MIMO systems. We consider a number of designs depending on the performance criteria and degree of channel knowledge at the transmitter. First, assuming perfect channel knowledge at the transmitter and receiver, and a flat-fading channel, we propose a generalized linear block precoding and decoding scheme based on the weighted mean square error criteria, assuming a total power constraint at the transmitter. The optimum design forces transmission only on the