Title: Channel-Quality-Driven High-Performance Receivers for Next Generation Wireless Communication Systems

Committee:

Dr. Xiaoli Ma, ECE, Chair 

Dr. Gee-Kung Chang, ECE 

Dr. John Barry, ECE

Dr. Mary Ann Weitnauer, ECE

Dr. Ellen Zegura, CoC

Abstract: The objective of this dissertation is to explore the relation between channel quality and detection performance in multi-input multi-output (MIMO) systems and develop high-performance receivers by improving the channel quality within reasonable complexity. MIMO technology greatly improves the spectral efficiency and reliability of wireless communication systems. As the demand on spectral efficiency keeps increasing, large MIMO has been proposed for next generation wireless systems, where tens or hundreds of antennas are equipped at either or both ends of the communication link. In such cases, it becomes critical to design high-performance detectors with affordable complexity. For MIMO systems where similar numbers of antennas exist at both sides of the communication link, several lattice reduction (LR) algorithms have been proposed to enhance the channel quality and provide near-optimum bit-error-rate for linear detectors (LDs). We first study the theoretical capacity limit of LR aided LDs. Then, we apply LR techniques to improve the performance of multiuser (MU) MIMO systems. For the MU MIMO uplink where users employ Alamouti space-time code, we develop LR-aided detectors that utilize the symmetric structure of the equivalent channel. For the MU MIMO downlink, we design LR-aided transceivers to minimize the sum of the mean-squared error. To improve the flexibility and adaptability of LR, we design learning-based LR algorithms that efficiently reduce the channel matrix according to pre-defined objectives. For MIMO systems where the number of antennas at one side of the link is much greater than that at the other side, we study the orthogonality deficiency of the MIMO channel and its relationship to the performance of LDs. We show that if the number of receive antennas exceeds a certain number while the number of transmit antennas is fixed, the channel is in ``good’’ quality for LDs to collect the same diversity as that of the optimal detector with high probability in practice. Other than spectral efficiency, future wireless applications also demand high reliability and low latency. Automatic retransmission request (ARQ) has been shown to be a key technique to meet the reliability constraint but often at the cost of latency. Targeting MIMO systems with linear receivers, we propose channel assisted ARQ strategies, where the retransmission of a data frame is requested as soon as the receiver decides the estimated channel is of ``bad’’ quality. By skipping detection and demodulation of data frames during ``bad’’ channels, the receiver has improved detection performance and reduced latency/complexity. The effectiveness of our proposed schemes is verified by extensive simulations.