Full Diversity Full Multiplexing Beamforming Techniques for Multiple-Input Multiple-Output Wireless Communication Systems

Multiple-Input Multiple-Output (MIMO) wireless systems have drawn substantial interest because they can offer high spectral efficiency and performance in a given bandwidth. Beamforming techniques have been applied to increase throughput or performance for flat fading channels, when Channel State Information at the Transmitter (CSIT) is available. Although uncoded multiple beamforming cannot offer full diversity, Bit-Interleaved Coded Multiple Beamforming (BICMB) applying channel coding can achieve both full diversity and full multiplexing if the code rate Rc and the number of employed subchannels S satisfy the condition RcS≤1. Moreover, by constellation precoding, both uncoded and coded beamforming can achieve full diversity and full multiplexing simultaneously for any RcS value with increased decoding complexity. In this dissertation, Perfect Coded Multiple Beamforming (PCMB) and BICMB with Perfect Coding (BICMB-PC) are proposed. They apply Perfect Space-Time Block Codes (PSTBCs) and achieve both full diversity and full multiplexing for uncoded and coded beamforming respectively. PCMB has substantially lower decoding complexity than a MIMO system employing PSTBC. Its decoding complexity is also much lower than fully precoded multiple beamforming in dimensions 2 and 4. BICMB-PC has much lower decoding complexity than BICMB with full precoding in these two dimensions, and the complexity gain is greater than the uncoded case.;MIMO techniques have been incorporated with Orthogonal Frequency Division Multiplexing (OFDM) for frequency selective fading channels. BICMB-OFDM can provide spatial diversity, multipath diversity, spatial multiplexing and frequency multiplexing simultaneously. In this dissertation, the diversity analysis of BICMB-OFDM is carried out, and a full diversity condition RcSL≤1 is proved, where S and L are the number of parallel streams at each subcarrier and the number of channel taps respectively. Furthermore, a full-diversity precoding design to overcome the restriction RcSL≤1 is developed with minimum decoding complexity.;Although precoding techniques can increase the performance of beamforming systems, their Maximum Likelihood (ML) decoding has high complexity. Sphere Decoding (SD) is an alternative for ML decoding with reduced complexity. Additionally, the complexity of SD can be further reduced. In this dissertation, a new technique is introduced for both uncoded and coded MIMO systems, which substantially decreases the computational complexity of SD.