Hybrid User Pairing for Spectral and Energy Efficiencies in Multiuser MISO-NOMA Networks With SWIPT

• Published in: IEEE transactions on communications Vol. 68; no. 8; pp. 4874 - 4890
• Main Authors: Nguyen, Toan-Van, Nguyen, Van-Dinh, da Costa, Daniel Benevides, An, Beongku
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G mobile communication; Algorithms; Array signal processing; Computer simulation; Continuity (mathematics); Convergence; Downlink; Energy conversion efficiency; Energy efficiency; Energy harvesting; inner approximation; Iterative algorithms; Linearity; MISO communication; NOMA; non-convex optimization; non-linear energy harvesting; non-orthogonal multiple access (NOMA); Nonorthogonal multiple access; Optimization; Power consumption; Power transfer; Resource management; Resource utilization; spectral efficiency; transmit beamforming; user pairing; Wireless networks
• ISSN: 0090-6778; 1558-0857
• DOI: 10.1109/TCOMM.2020.2994204

In this paper, we propose a novel hybrid user pairing (HUP) scheme in multiuser multiple-input single-output non-orthogonal multiple access networks with simultaneous wireless information and power transfer. In this system, two information users with distinct channel conditions are optimally paired while energy users perform energy harvesting (EH) under non-linearity of the EH circuits. We consider the problem of jointly optimizing user pairing and power allocation to maximize the overall spectral efficiency (SE) and energy efficiency (EE) subject to user-specific quality-of-service and harvested power requirements. A new paradigm for the EE-EH trade-off is then proposed to achieve a good balance of network power consumption. Such design problems are formulated as the maximization of non-concave functions subject to the class of mixed-integer non-convex constraints, which are very challenging to solve optimally. To address these challenges, we first relax binary pairing variables to be continuous and transform the design problems into equivalent non-convex ones, but with more tractable forms. We then develop low-complexity iterative algorithms to improve the objectives and converge to a local optimum by means of the inner approximation framework. Simulation results show the convergence of proposed algorithms and the SE and EE improvements of the proposed HUP scheme over state-of-the-art designs. In addition, the effects of key parameters such as the number of antennas and dynamic power at the BS, target data rates, and energy threshold, on the system performance are evaluated to show the effectiveness of the proposed schemes in balancing resource utilization.