  In this thesis, we investigate the problem of efficient data detection in
large MIMO and high order MU-MIMO systems. First, near-optimal low-complexity
detection algorithms are proposed for regular MIMO systems. Then, a family of
low-complexity hard-output and soft-output detection schemes based on channel
matrix puncturing targeted for large MIMO systems is proposed. The performance
of these schemes is characterized and analyzed mathematically, and bounds on
capacity, diversity gain, and probability of bit error are derived. After that,
efficient high order MU-MIMO detectors are proposed, based on joint modulation
classification and subspace detection, where the modulation type of the
interferer is estimated, while multiple decoupled streams are individually
detected. Hardware architectures are designed for the proposed algorithms, and
the promised gains are verified via simulations. Finally, we map the studied
search-based detection schemes to low-resolution precoding at the transmitter
side in massive MIMO and report the performance-complexity tradeoffs.
