Abstract
This thesis studies hardware-aware modeling, design and optimization for the sys tems of wireless power transfer (WPT), intelligent reflecting surface (IRS) assisted wire less communication, and IRS-assisted backscatter communication. First, we study the power waveform design for WPT from a multi-antenna energy transmitter (ET) to multiple single-antenna energy receivers (ERs) simultaneously in multi-path frequency-selective channels. A refined nonlinear current-voltage model of the diode in the ER rectifier is proposed. Leveraging this new model and by adopting a multisine waveform structure for the transmit signal, we formulate and solve power waveform design problems to maximize the end-to-end efficiency. Next, we study the beamforming optimization for IRS-assisted multi-user multiple input single-output (MISO) communication system. A practical IRS phase shift model that captures the phase-dependent amplitude variation in the element-wise reflection coefficient is proposed. Based on the proposed phase shift model, we formulate and solve optimization problems to minimize the total transmit power at the multi-antenna access point (AP) by jointly designing the AP transmit beamforming and the IRS re flect beamforming, subject to the users’ individual signal-to-interference-plus-noise ra tio (SINR) constraints. Finally, we study the channel estimation for an IRS-assisted backscatter commu nication system with a full-duplex single-antenna reader and a single-antenna tag. A novel channel estimation scheme is proposed to efficiently estimate both the reader-tag direct channel and reader-IRS-tag reflecting channel, by controlling the IRS training re flections over time. The IRS training matrix is also optimized to minimize the channel estimation error