An intelligent load balancing algorithm for 5G‐satellite networks

Summary Cellular networks are projected to deal with an immense rise in data traffic, as well as an enormous and diverse device, plus advanced use cases, in the nearest future; hence, future 5G networks are being developed to consist of not only 5G but also different radio access technologies (RATs)...

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Bibliographic Details
Published in:International journal of satellite communications and networking Vol. 42; no. 5; pp. 329 - 353
Main Authors: Bello, Mobolanle, Pillai, Prashant, Sadiq, Ali Safaa
Format: Journal Article
Language:English
Published: Chichester Wiley Subscription Services, Inc 01.09.2024
Subjects:
5G mobile communication
5G Network
Admission control
Algorithms
artificial intelligent
call admission control
Cellular communication
Communications traffic
heterogeneous wireless network
Load balancing
Performance measurement
RAT selection
Satellite network
Satellite networks
Simulated annealing
Swarm intelligence
Wireless networks
ISSN:1542-0973, 1542-0981
Online Access:Get full text
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Summary:Summary Cellular networks are projected to deal with an immense rise in data traffic, as well as an enormous and diverse device, plus advanced use cases, in the nearest future; hence, future 5G networks are being developed to consist of not only 5G but also different radio access technologies (RATs) integrated. In addition to 5G, the user's device (UD) will be able to connect to the network via LTE, WiMAX, WiFi, Satellite and other technologies. On the other hand, Satellite has been suggested as a preferred network to support 5G use cases. However, achieving load balancing is essential to guarantee an equal amount of traffic distributed between different RATs in a heterogeneous wireless network; this would enable optimal utilisation of the radio resources and lower the likelihood of call blocking/dropping. This study presented an artificial intelligent‐based application in heterogeneous wireless networks and proposed an enhanced particle optimisation (EPSO) algorithm to solve the load balancing problem in 5G‐Satellite networks. The algorithm uses a call admission control strategy to admit users into the network to ensure that users are evenly distributed on the network. The proposed algorithm was compared with the Artificial Bee Colony and Simulated Annealing algorithm using three performance metrics: throughput, call blocking and fairness. Finally, based on the experimental findings, results outcomes were analysed and discussed. Future 5G networks are evolving to incorporate multiple Radio Access Technologies (RATs) to handle increased data traffic and diverse devices, including LTE, WiMAX, WiFi, and Satellite. Satellites are particularly promising for supporting 5G use cases. Load balancing is crucial for optimal resource utilization and reducing call blocking/dropping in heterogeneous wireless networks. An Enhanced Particles Optimization (EPSO) algorithm with call admission control was proposed to address this, outperforming Artificial Bee Colony and Simulated Annealing algorithms in throughput, call blocking, and fairness metrics, as shown in the study's analysis.
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ISSN:1542-0973
1542-0981
DOI:10.1002/sat.1517