Genetic algorithm based coverage optimization 5G networks. Issue 5 (4th July 2022)

• Record Type: Journal Article
• Authors: Dash, Shatarupa; Sahu, Bharat J. R.
• Is Part Of: Journal of information & optimization sciences. Volume 43:Issue 5(2022)
• Page Start: 933
• Page End: 939
• Publication Date: 2022-07-04
• Subjects: 68; 5G networks -- Network planning -- Energy efficiency -- Genetic algorithm -- Green communication; Electronic data processing -- Periodicals; Information science -- Periodicals; Mathematical optimization -- Periodicals; 519.6
• DOI: 10.1080/02522667.2022.2101212
• Languages: English
• ISSNs: 0252-2667

Abstract

Abstract: The advancements of smart and intelligent devices have resulted in the exponential growth of data traffic, which has increased the need for higher capacity wireless networks. Naturally, 5G networks must deal with exponentially increasing devices. This poses excessive stress on resource allocation tasks, both in terms of scalability and throughput for network deployment. In this sense, location intelligence can be key to addressing this challenge and complementing legacy methods at a temporal and spatial scale that are not currently given importance. Thus, this paper presents a genetic algorithm ( GA ) approach and its application in estimating the best location for 5G base stations in terms of coverage and transmission power. Our experimental results exhibit the proposed approach's effectiveness.