journal article·2022Open access

Conflict Resolution Strategy in Handover Management for 4G and 5G Networks

Abdulraqeb Alhammadi, Wan Haslina Hassan, Ayman A. El-Saleh, Ibraheem Shayea, Hafizal Mohamad, Yousef Ibrahim Daradkeh

Computers, Materials & Continua· Volume 72· Issue 3

Abstract

Fifth-generation (5G) cellular networks offer high transmission rates in dense urban environments. However, a massive deployment of small cells will be required to provide wide-area coverage, which leads to an increase in the number of handovers (HOs). Mobility management is an important issue that requires considerable attention in heterogeneous networks, where 5G ultra-dense small cells coexist with current fourth-generation (4G) networks. Although mobility robustness optimization (MRO) and load balancing optimization (LBO) functions have been introduced in the 3GPP standard to address HO problems, non-robust and nonoptimal algorithms for selecting appropriate HO control parameters (HCPs) still exist, and an optimal solution is subjected to compromise between LBO and MRO functions. Thus, HO decision algorithms become inefficient. This paper proposes a conflict resolution technique to address the contradiction between MRO and LBO functions. The proposed technique exploits received signal reference power (RSRP), cell load and user speed to adapt HO margin (HM) and time to trigger (TTT). Estimated HM and TTT depend on a weighting function and HO type which is represented by user status during mobility. The proposed technique is validated with other existing algorithms from the literature. Simulation results demonstrate that the proposed technique outperforms existing algorithms overall performance metrics. The proposed technique reduces the overall average HO ping-pong probability, HO failure rate and interruption time by more than 90%, 46% and 58%, respectively, compared with the other schemes overall speed scenarios and simulation time.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced MIMO Systems Optimization · Advanced Wireless Network Optimization · Cooperative Communication and Network Coding

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (28)

Show source-provided references
1. 3GPP, “Evolved universal terrestrial radio access (e-utra); relay architectures for e-utra (lte-advanced), Tech. Rep. No. TS 36.133,” 2018.
2. 3GPP, “Requirements for further advancements for evolved universal terrestrial radio access (e-utra) (lte-advanced) (Tech. Rep. No. TR 36.913),” 2018.
3. Mobility management in small cell cluster of cellular network10.32604/cmc.2021.016529 ↗
4. 3GPP, “Nr; user equipment (ue) radio transmission and reception; part 1: Range 1, standalone (Tech. Rep. No. TS 38.101-1),” 2019.
5. Auto tuning self-optimization algorithm for mobility management in LTE-A and 5G HetNets10.1109/ACCESS.2019.2961186 ↗
6. 3GPP, “Self-organizing networks (son) policy network resource model (nrm) integration reference point (irp); requirements release 15 (Tech. Rep. No. TS 28.627),” 2018.
7. A conflict avoidance scheme between mobility load balancing and mobility robustness optimization in self-organizing networks10.1007/s11276-016-1331-y ↗
8. Handover scheme with enode-B pre-selection and parameter self-optimization for LTE-A heterogeneous networks
9. Load-dependent handover margin for throughput enhancement and load balancing in HetNets10.1109/ACCESS.2018.2878489 ↗
10. Adaptive mobility load balancing algorithm for LTE small-cell networks10.1109/TWC.2018.2789902 ↗
11. Velocity-aware handover self-optimization management for next generation networks10.3390/app10041354 ↗
12. Dynamic handover control parameters for LTE-A/5G mobile communications
13. Self-optimization of handover control parameters for mobility management in 4G/5G heterogeneous networks10.3103/S014641161905002X ↗
14. Individualistic dynamic handover parameter self-optimization algorithm for 5G networks based on automatic weight function10.1109/ACCESS.2020.3037048 ↗
15. New weight function for adapting handover margin level over contiguous carrier aggregation deployment scenarios in LTE-advanced system10.1007/s11277-019-06463-2 ↗
16. A novel heuristic for handover priority in mobile heterogeneous networks10.1109/ACCESS.2019.2963069 ↗
17. Adaptive hysteresis margin based on fuzzy logic for handover in mobile networks with dense small cells10.1109/ACCESS.2018.2811047 ↗
18. Multi-criteria handover using modified weighted TOPSIS methods for heterogeneous networks10.1109/ACCESS.2018.2846045 ↗
19. Handover optimization scheme for LTE-advance networks based on AHP-TOPSIS and Q-learning10.1016/j.comcom.2018.10.011 ↗
20. Optimization of user behavior based handover using fuzzy Q-learning for LTE networks10.1007/s11276-016-1348-2 ↗
21. Adaptive multi-fuzzy engines for handover decision in heterogeneous wireless networks10.1007/s11277-017-3963-3 ↗
22. Multi-criteria fuzzy-based decision making algorithm to optimize the VHO performance in HetNets10.32604/cmc.2022.015299 ↗
23. Reduction in ping-pong effect in heterogeneous networks using fuzzy logic10.1007/s00500-018-3246-2 ↗
24. 3GPP, “Self-organizing networks (son) policy network resource model (nrm) integration reference point (irp); requirements,” Tech. Rep. No. TS 28.628, 2020.
25. 3GPP, “Self-organizing networks (son) policy network resource model (nrm) integration reference point (irp); requirement,” Tech. Rep. No. TR 32.521, 2012.
26. 5G Ultra-dense cellular networks10.1109/MWC.2016.7422408 ↗
27. G. T. 36.814, “Evolved universal terrestrial radio access (E-UTRA); further advancements for E-UTRA physical layer aspects,” 2017.
28. 3GPP, “Study on channel model for frequencies from 0.5 to 100 GHz,” Tech. Rep., TR 38.901, 2020.