This dissertation examines multi-antenna transceiver design over flat-fading wireless channels. Bit Interleaved Coded Modulation (BICM) and MultiLevel Coded Modulation (MLCM) transmitter structures are considered, as well as the used of an optional spatial precoder under slow and quasi-static fading conditions. At the receiver, MultiStage Decoder (MSD) and Iterative Detection and Decoding (IDD) strategies are applied. Precoder, mapper and subcode designs are optimized for different receiver structures over the different antenna and fading scenarios. Under slow and quasi-static channel conditions, fade resistant multi-antenna transmission is achieved through a combination of linear spatial precoding and non-linear multi-dimensional mapping. A time-varying random unitary precoder is proposed, with significant performance gains over spatial interleaving. The fade resistant properties of multidimensional random mapping are also analyzed. For MLCM architectures, a group random labelling strategy is proposed for large antenna systems. The use of complexity constrained receivers in BICM and MLCM transmissions is explored. Two multi-antenna detectors are proposed based on a group detection strategy, whose complexity can be adjusted through the group size parameter. These detectors show performance gains over the the Minimum Mean Squared Error (MMSE)detector in spatially multiplexed systems having an excess number of transmitter antennas. A class of irregular convolutional codes is proposed for use in BICM transmissions. An irregular convolutional code is formed by encoding fractions of bits with different puncture patterns and mother codes of different memory. The code profile is designed with the aid of extrinsic information transfer charts, based on the channel and mapping function characteristics. In multi-antenna applications, these codes outperform convolutional turbo codes under independent and quasi-static fading conditions. For finite length transmissions, MLCM-MSD performance is affected by the mapping function. Labelling schemes such as set partitioning and multidimensional random labelling generate a large spread of subcode rates. A class of generalized Low Density Parity Check (LDPC) codes is proposed, to improve low-rate subcode performance. For MLCM-MSD transmissions, the proposed generalized LDPC codes outperform conventional LDPC code construction over a wide range of channels and design rates.

This dissertation examines multi-antenna transceiver design over flat-fading wireless channels. Bit Interleaved Coded Modulation (BICM) and MultiLevel Coded Modulation (MLCM) transmitter structures are considered, as well as the used of an optional spatial precoder under slow and quasi-static fading conditions. At the receiver, MultiStage Decoder (MSD) and Iterative Detection and Decoding (IDD) strategies are applied. Precoder, mapper and subcode designs are optimized for different receiver structures over the different antenna and fading scenarios. Under slow and quasi-static channel conditions, fade resistant multi-antenna transmission is achieved through a combination of linear spatial precoding and non-linear multi-dimensional mapping. A time-varying random unitary precoder is proposed, with significant performance gains over spatial interleaving. The fade resistant properties of multidimensional random mapping are also analyzed. For MLCM architectures, a group random labelling strategy is proposed for large antenna systems. The use of complexity constrained receivers in BICM and MLCM transmissions is explored. Two multi-antenna detectors are proposed based on a group detection strategy, whose complexity can be adjusted through the group size parameter. These detectors show performance gains over the the Minimum Mean Squared Error (MMSE)detector in spatially multiplexed systems having an excess number of transmitter antennas. A class of irregular convolutional codes is proposed for use in BICM transmissions. An irregular convolutional code is formed by encoding fractions of bits with different puncture patterns and mother codes of different memory. The code profile is designed with the aid of extrinsic information transfer charts, based on the channel and mapping function characteristics. In multi-antenna applications, these codes outperform convolutional turbo codes under independent and quasi-static fading conditions. For finite length transmissions, MLCM-MSD performance is affected by the mapping function. Labelling schemes such as set partitioning and multidimensional random labelling generate a large spread of subcode rates. A class of generalized Low Density Parity Check (LDPC) codes is proposed, to improve low-rate subcode performance. For MLCM-MSD transmissions, the proposed generalized LDPC codes outperform conventional LDPC code construction over a wide range of channels and design rates.