Title: Developing a new energy-efficient joint user and power allocation framework using a heuristic algorithm-based deep network in futuristic 5G millimetre wave networks

Authors: G. Subramani; M. Nagarajan; G. Sudhagar

Addresses: Department of ECE, BIHER, Chennai, 600073, Tamil Nadu, India; ECE Department, Kuppam Engineering College, Kuppam, 517425, AP, India ' Department of ECE, BIHER, Chennai, 600073, Tamil Nadu, India ' Department of ECE, BIHER, Chennai, 600073, Tamil Nadu, India

Abstract: Millimetre wave is a crucial role in developing Fifth Generation (5G) network and power allocation framework. Moreover the existing techniques limits from high power consumption, leading to increased energy usage. In order to solve the issues, the research study introduces future 5G mmWave networks to enhance energy-efficient joint user and power allocation. This work is considered the Base Station (BS) on/off switching mechanism. At first, optimal data generation is performed by intellectual frilled lizard optimisation with random updates (IFLO-RU). The adaptive residual autoencoder with spatiot-temporal attention (ARAE-STA) is employed for optimising the power allocation across distinct devices or users in a network. Some of the multi-objective functions such as the number of switched-off BSs, energy efficiency, network throughput, and power consumption are evaluated. Finally, the developed framework's performance analyses the other related methods to confirm the efficacy of the implemented system.

Keywords: energy-efficiency; joint user and power allocation; future 5G millimetre wave networks; IFLO-RU; intellectual frilled lizard optimisation with random updates; ARAE-STA; adaptive residual autoencoder with spatiot-temporal attention; QoS; quality of service.

DOI: 10.1504/IJAACS.2026.154874

International Journal of Autonomous and Adaptive Communications Systems, 2026 Vol.19 No.3, pp.375 - 412

Received: 26 Apr 2025
Accepted: 08 Dec 2025
Published online: 16 Jul 2026 *

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