The development of six generation (6G) wireless communication technology is becoming increasingly imminent to achieve internet of everything (IoE) in today's digital era. Non- orthogonal multiple access (NOMA) is the pivotal technology in the upcoming 6G networks due to its high spectrum efficiency. The reconfiguable intelligent surface (RIS) has been widely acknowledged in both industry and academia since it is able to improve the quality of channels. Based on RIS, simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) can both transmit and reflect the signals and achieve full space communications. Meanwhile, the integrated sensing and communications (ISAC) is also widely considered as a paradigm-shifting approach to combine the sensing and communications into an unified framework in 6G. This thesis proposes four different communication frameworks based on NOMA scheme including a multi-user RIS assisted downlink NOMA network, multi-cluster STAR-RIS assisted downlink NOMA network, RIS assisted coordinated multi-point (CoMP) NOMA network and STAR-RIS assisted ISAC NOMA network. In the first network, an energy efficiency (EE) maximization problem is formulated by jointly designing the beamforming of the users and phase shifts of the RIS elements. Alternating optimization and relaxation are utilized to find the suboptimal solutions of original problem. In the second network, an EE maximzation problem is also formulated by jointly optimizing the phase shifts and beamforming. In particular, sequential rank-one constraint relaxation is proposed to tackle the rank-one constraints in phase shift semidefinite relaxation (SDR) problem. In the third network, the sum rate maximization problem of NOMA users is formulated. Specifically, manifold optimization is applied to tackle the phase shift problem since the norm constraints of RIS elements can be considered as a manifold. In the fourth network, a sum rate maximization problem of multiple primary users is formulated in an ISAC case. A penalty-based successive convex cancellation (SCA) is leveraged to solve the rank constraints in both beamforming and phase shift SDR problems.
Date of Award | 1 Aug 2024 |
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Original language | English |
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Awarding Institution | - The University of Manchester
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Supervisor | Daniel Ka Chun So (Supervisor) & Zhiguo Ding (Supervisor) |
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THE APPLICATIONS OF RECONFIGURABLE INTELLIGENT SURFACE IN NON-ORTHOGONAL MULTIPLE ACCESS NETWORKS
Wang, T. (Author). 1 Aug 2024
Student thesis: Phd