UC Irvine

Future wireless communication systems are expected to have much higher mobility and data rate. To achieve these goals, millimeter-wave (mmWave) communication has been considered as a key technology for the future wireless communication systems, because of the high data rates provided by the large bandwidth at the mmWave carrier frequency. However, obstacles such as the severe path-loss and the hardware complexity hinder the practical application of the mmWave communication. Incorporating beamforming into the mmWave communication systems is an effective way to combat the severe path-loss. In this dissertation, we explore the beamforming technique in mmWave communication systems. Four scenarios are investigated: multi-user networks, amplify-and-forward (AF) relay networks, mmWave non-orthogonal multiple access (NOMA) networks, and reconfigurable intelligent surface (RIS)-assisted mmWave unmanned aerial vehicles (UAV) networks. For the multi-user networks, we design an analog-only beamforming scheme for downlink multi-user mmWave systems to optimize the beamforming gain and the inter-user interference at the same time. Traditional analog beamforming schemes, such as the beam selection method, use the array response vector corresponding to the strongest path of the channel to generate a beam pointing to the user. In multi-user systems, such schemes will lead to large inter-user interference, especially when the users are closely located. In this dissertation, we formulate a multi-objective problem to strike a balance between the beamforming gain and the inter-user interference. Furthermore, to alleviate the effects of the channel estimation and feedback quantization errors, we design a robust beamforming scheme to provide robustness against imperfect channel information. We first develop a channel error model for the scattering clustered channel model, which can serve as a general channel error model for the mmWave channels. Then, we formulate a multi-objective problem using the stochastic approach to suppress the interference and enhance the beamforming gain at the same time.

For the AF relay networks, we consider the amplify-and-forward relay networks in mmWave systems and propose a hybrid precoder/combiner design approach. The phase-only RF precoding/combining matrices are first designed to support multi-stream transmission, where we compensate the phase for the eigenmodes of the channel. Then, the baseband precoders/combiners are performed to achieve the maximum mutual information. In addition, we also propose a robust joint transceiver design for imperfect channel state information.

For the mmWave-NOMA networks, we first take the limited channel coherence time into account for NOMA in mmWave hybrid beamforming systems. Due to the limited coherence time, the beamwidth of the hybrid beamformer affects the beam-training time, which in turn directly impacts the data transmission rate. To investigate this trade-off, we utilize a combined beam-training algorithm. Then, we formulate a sum-rate expression which considers the channel coherence time and beam-training time as well as users’ power and other system parameters. Further, a joint power and beamwidth optimization problem is solved by iterating between the power allocation and the beamwidth optimization.

Further, We propose a new two-step beamwidth design and power allocation algorithm, in mmWave-NOMA systems, which takes the channel coherence time and users' locations into account. A joint beamwidth and power allocation optimization algorithm is proposed to maximize the sum-rate. For the RIS-assisted mmWave UAV networks, we jointly optimize the deployment, user scheduling, beamforming vector and RIS phases to maximize the sum-rate, with the constraints of the minimum rate, the UAV movement, the analog beamforming and the RIS phases.