Power allocation method based on modified social network search algorithm

With the increase of communication devices and demands, the problems of high power consumption, tight spectrum resources, and low energy efficiency in the two-layer heterogeneous network are the popular topics, which need to be solved urgently. For the purpose of solving these problems in a two-laye...

Full description

Saved in:
Bibliographic Details
Published in:Applied intelligence (Dordrecht, Netherlands) Vol. 54; no. 24; pp. 12851 - 12884
Main Authors: Gao, Hongyuan, Li, Huishuang, Lin, Yun, Ma, Jingya
Format: Journal Article
Language:English
Published: New York Springer US 01.12.2024
Springer Nature B.V
Subjects:
ISSN:0924-669X, 1573-7497
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:With the increase of communication devices and demands, the problems of high power consumption, tight spectrum resources, and low energy efficiency in the two-layer heterogeneous network are the popular topics, which need to be solved urgently. For the purpose of solving these problems in a two-layer heterogeneous network consisting of femtocell base stations in randomly distributed a macrocell base station, which can also be called the Macrocell/Femtocell two-layer heterogeneous network, the hierarchical clustering algorithm is firstly used to cluster femtocell base stations in accordance with a distance threshold, the spectrum partitioning mechanism and non-orthogonal multiple access technique are combined to obtain spectrum allocation schemes for different users. Then, the modified social network search algorithm is used to simulate the power allocation problem in the two-layer heterogeneous network with system energy efficiency as the objective function. By comparing with the previous algorithms, the proposed algorithm’s superior performance is verified on the test functions. The results show that the proposed method can effectively improve spectrum utilization and reduce interference. The modified social network search algorithm is more robust and widely applicable regarding energy and computational efficiency.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0924-669X
1573-7497
DOI:10.1007/s10489-024-05804-4