Millimeter Wave and MIMO Antenna Beamforming for Next-Generation Wireless Communications

Abstract

Millimeter wave (mmWave) hybrid precoding systems are likely to have large antenna arrays to overcome the high channel path loss. In such circumstances, low cost hardware and power consumption are the main challenges. Furthermore, the hardware is tasked with computation of high dimensional optimal matrices of hybrid precoding design using Orthogonal Matching Pursuit (OMP). This dissertation addresses two algorithms to enhance the efficiency of the OMP reconstruction algorithm in mmWave precoding design. The spectral efficiency of the mmWave system using the proposed algorithms is compared with previous works and the optimal case (a fully digital precoder). The results show that the performance of the proposed algorithms is very close to that of the optimal design even though the complexity of the design is reduced. Millimeter wave systems rely on accurate channel state information (CSI) for the design of the precoding and combining matrices. Acquiring accurate CSI, however, is challenging due to the large number of antennas, the low signal-to-noise (SNR) ratio before beamforming, and possible interference from neighboring base stations (BSs). Prior work on channel estimation focused on the first two challenges and did not address inter-cell interference. Interference from neighboring BSs deteriorates the already low SNR and introduces errors in the channel estimate. This leads to additional interference in the system. This dissertation studies the effects of inter-cell interference on compressed sensing (CS) mmWave channel estimation techniques. A CS measurement matrix design is then proposed to jointly estimate the mmWave channel and null interference from neighboring BSs. Simulation results show that channel estimate errors strongly depend on the interference power and the number of interfering BSs. Moreover, in the presence of interference, the proposed techniques are shown to achieve channel estimates comparable to interference-free systems.