Energy Efficient Resource Allocation for 5G Heterogeneous Networks Using Genetic Algorithm

• Published in: IEEE access Vol. 9; pp. 160510 - 160520
• Main Authors: Qi, Xiaomin, Khattak, Shahid, Zaib, Alam, Khan, Imdad
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G mobile communication; Electric power distribution; Energy efficiency; Frequency division multiple access; Frequency reuse; genetic algorithm; Genetic algorithms; heterogeneous networks; Interference; Mathematical programming; Mixed integer; Networks; Optimization; Power distribution; Resource allocation; Resource management; Sorting algorithms; Throughput; Wireless communication
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2021.3131823

The energy efficient resource allocation scheme based on genetic algorithm (GA) for the downlink orthogonal frequency division multiple access (OFDMA) heterogeneous networks (HetNets) is developed in this paper. To maximize the spectrum efficiency for the fifth generation (5G) mobile networks, frequency reuse-1 is employed. Thus, advanced inter-cell interference coordination techniques are required to mitigate the inter-cell interference for 5G HetNets. In this paper, the energy efficient optimization problem based on coordinated scheduling is formulated, which is a mixed-integer nonlinear fractional programming problem and is intractable to solve directly. To tackle this, a two-step GA based scheme is proposed to solve the optimization problem. In the first step, the resource blocks matrix is solved by normal GA in the spectral efficiency aspect with fixed power distribution matrix, and then the power distribution matrix is obtained in the second step by non-dominated sorting genetic algorithm II (NSGA-II) with obtained resource blocks allocation matrix. Finally, the system level numerical evaluation process is provided to illustrate the effectiveness of the developed scheme.