RIS-NOMA integrated low-complexity transceiver architecture: Sum rate and energy efficiency perspective
Kali Krishna Kota, Praful D. Mankar
TL;DR
The paper addresses the challenge of achieving high data rates and energy efficiency in mmWave communications with low-complexity transceivers by integrating a RIS and NOMA into a fully analog BS architecture. It develops a unified optimization framework based on quadratic transformation, successive convex approximation, and SDR to jointly design the transmit beamformer, RIS phase shifts, and power allocation under imperfect CSI and minimum-rate constraints. The key contributions include a detailed QT-based reformulation, an alternating optimization algorithm for sum-rate and another for energy efficiency, and analytical WMSE-equivalence links, supported by simulations showing RIS-NOMA with FA can surpass optimally configured fully digital systems in SR at low SNR and EE across a broad SNR range, with reduced hardware complexity. The results highlight the potential of RIS to compensate for FA limitations and enable scalable, energy-efficient mmWave deployments, while identifying CSI accuracy and RIS size as pivotal performance drivers.
Abstract
This paper aims to explore reconfigurable intelligent surface (RIS) integration in a millimeter wave (mmWave) communication system with low-complexity transceiver architecture under imperfect CSI assumption. Towards this, we propose a RIS-aided system with a fully analog (FA) architecture at the base station. However, to overcome the disadvantage of single-user transmission due to the single RF-chain, we employ NOMA. For such a system, we formulate sum rate (SR) and energy efficiency (EE) maximization problems to obtain the joint transmit beamformer, RIS phase shift matrix, and power allocation solutions under minimum rate constraint. We first tackle the fractional objectives of both problems by reformulating the SR and EE maximization problems into equivalent quadratic forms using the quadratic transform. On the other hand, we employ successive convex approximation and the semi-definite relaxation technique to handle the non-convex minimum rate and unit modulus constraint of the RIS phase shifts, respectively. Next, we propose an alternating optimization-based algorithm that iterates over the transmit beamformer, power allocation, and RIS phase shift subproblems. Further, we also show that the quadratic reformulation is equivalent to the WMSE-based reformulation for the case of SR maximization problem. Our numerical results show that the proposed RIS-NOMA integrated FA architecture system outperforms the optimally configured fully digital architecture in terms of SR at low SNR and EE for a wide range of SNR while still maintaining low hardware complexity and cost. Finally, we present the numerical performance analysis of the RIS-NOMA integrated low-complexity system for various system configuration parameters.