Energy efficient ultra‐dense networks (UDNs) based on joint optimisation evolutionary algorithm. Issue 1 (1st January 2019)

• Record Type: Journal Article
• Authors: Salem, Ahmed Abdelaziz; El‐Rabaie, Sayed; Shokair, Mona
• Is Part Of: IET communications. Volume 13:Issue 1(2019)
• Page Start: 99
• Page End: 107
• Publication Date: 2019-01-01
• Subjects: energy conservation -- optimisation -- radio spectrum management -- Monte Carlo methods -- cellular radio -- evolutionary computation -- power control -- wireless channels; energy efficient ultra‐dense networks -- joint optimisation evolutionary algorithm -- network operators -- spectrum scarcity -- current bandwidth -- advanced technique -- enormous communicating devices -- inclusive metrics -- cell network performance -- energy efficiency maximisation -- pivotal design parameters -- crucial impact -- dense network performance -- conventional alternating optimisation -- selected optimisation variables -- energy consumption -- hardware design -- simulation results -- hardware distortion -- optimisation parameters -- accumulated interference -- optimal design parameters -- mutual selection -- inter‐cell interference -- dense small cells -- power control coefficient -- user number -- base station density -- EE optimisation; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2018.5613
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : In future cellular 5G, the network operators have recognised the spectrum scarcity as one of the major problems. Therefore, expanding or even re‐utilising the current bandwidth requires an advanced technique to accommodate the enormous communicating devices. In this paper, energy efficiency (EE) maximization is jointly carried out with respect to the following design parameters: base station density, number of users, number of attached antennas, and power control coefficient based on analytical channel estimates and feasible pilot reuse. Although dense network performance is restricted to the accumulation of both user and inter‐cell interferences, the reasons of mutual selection among the optimal design parameters will be clearly discussed to discover their effects on mitigating interference. Simulation results validate that the diversity of the design parameters achieves the maximum EE given a predefined quality of service constraints. Also, the study of hardware distortion will expose the relevant influence on the optimised EE. Moreover, the results will be extended to study the energy consumption in terms of optimised design variables. Finally, our results will be confirmed through a fair comparison with the alternating optimisation based on Monte Carlo simulation, wherein, our proposal shows a reality and fast convergence.