Performance tradeoffs and coding for MIMO wireless systems

Wireless has revolutionized communication by providing users with tetherless connectivity. Wireless is currently undergoing a revolution in improved data rates and reliability. A key component in delivering such performance is that of multiple-input multiple-output (MIMO) techniques, where multiple transmit and receive antennas are used. These MIMO systems promise two important performance gains. First is diversity, which mitigates fading and asymptotically reduces the outage probability. The second leverage of MIMO wireless is spatial multiplexing, which establishes parallel channels and can increase the link spectral efficiency.; Achieving the performance gains of a MIMO wireless communication system requires proper coding. Specifically, space time codes are required. Several important tradeoffs exist In space time coding for the MIMO channel. First is that of the diversity-multiplexing tradeoff where for a given SNR increment, the outage probability can be decreased or the data rate of the system can be increased. Additionally, some combination of these two improvements can also be accomplished. The second important tradeoff in wireless coding is that of the rate-diversity tradeoff. This tradeoff describes the maximum achievable diversity as a function of the level of redundancy in the coding, described by the code rate.; In this thesis, we combine the two tradeoffs described above. The diversity-multiplexing and the rate-diversity tradeoff are then generalized into the code rate-diversity-multiplexing tradeoff, where the notion of rate is extended to the proportional code rate. Both a converse and a proof of achievability of the generalized tradeoff are given. The theoretical results are then compared to simulations results and implications of systems design are discussed. A space time code is proposed and the performance dependence on the code rate is studied by simulation. Finally, for multiplexing optimal codes, the link between code rate and receiver decode complexity is considered. Here, we see that the lower the code rate, the more complex the receiver. Other code design techniques for reducing receiver complexity are also considered. Finally, we consider the case of partial channel state information at the transmitter with linear precoder design for high multiplexing gain codes.