User grouping and power allocation for energy efficiency maximization in mmWave-NOMA heterogeneous networks

• Published in: Wireless networks Vol. 28; no. 6; pp. 2403 - 2420
• Main Authors: Khazali, Azadeh, Shayesteh, Mahrokh G., Kalbkhani, Hashem
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.08.2022; Springer Nature B.V
• Subjects: Algorithms; Cellular communication; Communications Engineering; Computer Communication Networks; Electrical Engineering; Energy efficiency; Engineering; Exact solutions; Heuristic methods; IT in Business; Mathematical analysis; Maximization; Millimeter waves; Monte Carlo simulation; Networks; Nonorthogonal multiple access; Optimization; Original Paper; Wireless networks; mmWave; NOMA; User grouping; Heterogeneous network; Small cell; Energy efficiency; Power allocation
• ISSN: 1022-0038; 1572-8196
• DOI: 10.1007/s11276-022-02982-2

This paper investigates the application of non-orthogonal multiple access (NOMA) and millimeter-wave (mmWave) transmission in the fifth-generation (5G) of heterogeneous cellular networks (HetNets). Due to the high penetration loss of mmWave, we propose that a small cell base station (SBS) serves small cell user (SCU) equipment in the mmWave band, and a macrocell base station (MBS) serves macrocell users (MCUs) in the microwave band. Cell association, user grouping, and power allocation are fundamental challenges in NOMA-based transmission. We formulate optimization problems for SCU and MCU to maximize the energy efficiency (EE) subject to the required minimum data rates and maximum transmission powers. User grouping algorithms are introduced to demonstrate the significance of selecting the best users. To allocate transmission powers, we formulate an EE maximization problem that is non-convex and NP-hard. We propose to use the Bat algorithm, which is one of the popular and efficient metaheuristic algorithms in solving non-convex problems. Analytical expressions for cell association and outage probabilities are derived. We present Monte Carlo simulation results to validate the analytical expressions and show that: (1) choosing the best user among far users influences the overall EE of system impressively; (2) the optimum values of transmission powers can be obtained by Bat algorithm; (3) the proposed grouping algorithms with power allocation methods outperform the other scenarios in terms of EE and spectral efficiency (SE).