Resource Allocation Design for Intelligent Reflecting Surface-assisted Communication Systems

Abstract

The upcoming sixth-generation (6G) networks are expected to create a future intelligent digital society by 2030. They will offer better communication services than the current fifth-generation (5G) networks, such as super-fast data speeds, improved energy efficiency, widespread coverage, and highly secure communications. Due to the rapid progress in meta-materials and electromagnetic (EM) materials, intelligent reflecting surfaces (IRSs) have emerged as a promising technology for enhancing future wireless communications. They offer additional degrees of freedom (DoF) to manipulate wireless channel conditions intelligently. Achieving the performance gains promised by IRSs relies on optimising the design of IRS phase shifts along with other wireless network components. This thesis develops three resource allocation algorithms tailored for IRS-assisted wireless communication systems to facilitate reliable power- and spectrally-efficient communications in 6G and future wireless networks. Firstly, this thesis proposes a self-sustainable IRS assisting a multiple-input single-output (MISO) downlink transmission system to achieve robust, secure, and environmentally friendly wireless communication. Specifically, the self-sustainable IRS can harvest energy from incoming signals, ensuring it has sufficient power to operate while also reflecting these signals to users to improve signal quality. We propose a novel resource allocation algorithm to maximise the sum-rate of the system by jointly designing beamformers at an access point (AP) and phase shifts at the IRS, as well as an energy harvesting schedule at the IRS. The proposed algorithm considers the wireless energy harvesting capability of IRS elements, secure communications, and robustness against the impact of imperfect channel state information (CSI). Then, we propose a novel approach to multiuser MISO downlink communication systems, which involves the use of an IRS to enhance the quality of primary transmissions from the AP to its primary users (PUs) while simultaneously serving as a secondary transmitter for intended secondary users (SUs). Specifically, the IRS encodes its information by applying an on/off multi-level amplitude modulation technique on the index of the IRS elements. A practical upper bound of the average symbol error rate (SER) is derived to characterise the non-coherent decoding performance. Then, we design a resource allocation algorithm to jointly optimise the beamformer at the AP and the phase shifts at the IRS to maximise the average sum-rate of the primary system while taking into account the maximum tolerable SER constraint for the SU. Furthermore, we explore the security performance of multiuser MISO wireless communication systems supported by a multifunctional active IRS. The active IRS can perform dual functions of reflecting and amplifying incoming signals while emitting artificial noise (AN) to combat potential eavesdropping. We have proposed an algorithm to minimise the total system power consumption while guaranteeing communication security. This is achieved by optimising the resource allocation by designing the phase, amplitude, and IRS mode selection of the active IRS elements and the precoder and AN vector of the base station (BS). The simulation results indicate that the proposed scheme improves security compared to the conventional schemes without the multifunctional active IRS, even when the eavesdropper is equipped with more antennas than the BS.