Adaptive cell selection algorithm for balancing cell loads in 5G heterogeneous networks

Heterogeneous networks (HetNets) are a promising solution for managing the exponential increase in the number of mobile users while maintaining high data rates and coverage. HetNets consist of various cell types with different cell coverage and system capacities. However, the traffic load in HetNets...

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Main Authors: Emre Gures, Ibraheem Shayea, Muntasir Sheikh, Mustafa Ergen, Ayman A. El-Saleh
Format: Article
Language:English
Published: Elsevier 2023-06-01
Series:Alexandria Engineering Journal
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016823002855
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author Emre Gures
Ibraheem Shayea
Muntasir Sheikh
Mustafa Ergen
Ayman A. El-Saleh
author_facet Emre Gures
Ibraheem Shayea
Muntasir Sheikh
Mustafa Ergen
Ayman A. El-Saleh
author_sort Emre Gures
collection DOAJ
description Heterogeneous networks (HetNets) are a promising solution for managing the exponential increase in the number of mobile users while maintaining high data rates and coverage. HetNets consist of various cell types with different cell coverage and system capacities. However, the traffic load in HetNets is variable, uneven and random over time, leading to unequal cell loads. Some cells have excessive user presence where the competition for system resources is high, while other cells have low user presence where system resources are not fully utilised. This paper proposes a mobility load balancing algorithm that prioritises millimetre-wave (mmWave) cells in target cell selection and user association to provide load balancing in 5G HetNets and improve overall system performance. A two-step target cell selection method that considers the load level of cells and reference signal received power (RSRP) is proposed. This method prioritises mmWave cells that meet cell load level and RSRP conditions in target cell selection, taking full advantage of the unique properties of mmWave cells (enhanced network throughput, spectral efficiency and enormous bandwidth) to balance traffic loads. The HO triggering and decision-making process is independently performed for each user. In case the serving cell is overloaded, different HO procedures are applied for load balancing depending on the target cell type (macro base station (BS) or mmWave BS). The scope of the study is further expanded by applying different HO procedures according to the serving and target cell types to maintain mobility robustness in case the serving cell is not overloaded. This research proposes various system scenarios with fixed HO margin (HOM) values and fixed time-to-trigger (TTT) durations to examine the effects of HCP settings on the proposed algorithm’s performance in terms of average load level of the serving cell, throughput, spectral efficiency and call dropping ratio (CDR). The system that provides the highest overall performance is applied to the proposed algorithm. To further assess and validate the performance of the proposed algorithm, it is compared with other load balancing algorithms from the literature. The simulation results reveal that the proposed algorithm does provide noticeable enhancements in network performance in terms of load level, throughput, spectral efficiency and CDR for various mobile speed scenarios as compared to existing load balancing algorithms.
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spelling doaj.art-806a0da480834d50b44e3d604adc90972023-04-27T06:05:30ZengElsevierAlexandria Engineering Journal1110-01682023-06-0172621634Adaptive cell selection algorithm for balancing cell loads in 5G heterogeneous networksEmre Gures0Ibraheem Shayea1Muntasir Sheikh2Mustafa Ergen3Ayman A. El-Saleh4Department of Electronics and Communication Engineering, Faculty of Electrical and Electronics Engineering, Istanbul Technical University (ITU), 34467 Istanbul, Turkey; Corresponding authors.Department of Electronics and Communication Engineering, Faculty of Electrical and Electronics Engineering, Istanbul Technical University (ITU), 34467 Istanbul, Turkey; Corresponding authors.Electrical and Computer Engineering Department, College of Engineering, King Abdulaziz University, Jeddah, Saudi ArabiaDepartment of Electronics and Communication Engineering, Faculty of Electrical and Electronics Engineering, Istanbul Technical University (ITU), 34467 Istanbul, TurkeyDepartment of Electronics and Communication Engineering, College of Engineering, A’Sharqiyah University (ASU), Ibra 400, OmanHeterogeneous networks (HetNets) are a promising solution for managing the exponential increase in the number of mobile users while maintaining high data rates and coverage. HetNets consist of various cell types with different cell coverage and system capacities. However, the traffic load in HetNets is variable, uneven and random over time, leading to unequal cell loads. Some cells have excessive user presence where the competition for system resources is high, while other cells have low user presence where system resources are not fully utilised. This paper proposes a mobility load balancing algorithm that prioritises millimetre-wave (mmWave) cells in target cell selection and user association to provide load balancing in 5G HetNets and improve overall system performance. A two-step target cell selection method that considers the load level of cells and reference signal received power (RSRP) is proposed. This method prioritises mmWave cells that meet cell load level and RSRP conditions in target cell selection, taking full advantage of the unique properties of mmWave cells (enhanced network throughput, spectral efficiency and enormous bandwidth) to balance traffic loads. The HO triggering and decision-making process is independently performed for each user. In case the serving cell is overloaded, different HO procedures are applied for load balancing depending on the target cell type (macro base station (BS) or mmWave BS). The scope of the study is further expanded by applying different HO procedures according to the serving and target cell types to maintain mobility robustness in case the serving cell is not overloaded. This research proposes various system scenarios with fixed HO margin (HOM) values and fixed time-to-trigger (TTT) durations to examine the effects of HCP settings on the proposed algorithm’s performance in terms of average load level of the serving cell, throughput, spectral efficiency and call dropping ratio (CDR). The system that provides the highest overall performance is applied to the proposed algorithm. To further assess and validate the performance of the proposed algorithm, it is compared with other load balancing algorithms from the literature. The simulation results reveal that the proposed algorithm does provide noticeable enhancements in network performance in terms of load level, throughput, spectral efficiency and CDR for various mobile speed scenarios as compared to existing load balancing algorithms.http://www.sciencedirect.com/science/article/pii/S1110016823002855Load balancingMobility managementHeterogeneous networks5GMillimetre-waveHandover
spellingShingle Emre Gures
Ibraheem Shayea
Muntasir Sheikh
Mustafa Ergen
Ayman A. El-Saleh
Adaptive cell selection algorithm for balancing cell loads in 5G heterogeneous networks
Alexandria Engineering Journal
Load balancing
Mobility management
Heterogeneous networks
5G
Millimetre-wave
Handover
title Adaptive cell selection algorithm for balancing cell loads in 5G heterogeneous networks
title_full Adaptive cell selection algorithm for balancing cell loads in 5G heterogeneous networks
title_fullStr Adaptive cell selection algorithm for balancing cell loads in 5G heterogeneous networks
title_full_unstemmed Adaptive cell selection algorithm for balancing cell loads in 5G heterogeneous networks
title_short Adaptive cell selection algorithm for balancing cell loads in 5G heterogeneous networks
title_sort adaptive cell selection algorithm for balancing cell loads in 5g heterogeneous networks
topic Load balancing
Mobility management
Heterogeneous networks
5G
Millimetre-wave
Handover
url http://www.sciencedirect.com/science/article/pii/S1110016823002855
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AT mustafaergen adaptivecellselectionalgorithmforbalancingcellloadsin5gheterogeneousnetworks
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