Scholarlink

<p>With the increasing densification of cellular networks and the evolution toward next-generation technologies such as Fifth Generation (5G) and Sixth Generation (6G), optimizing radio parameters has become essential to ensure effective coverage and satisfactory Quality of Service (QoS). This study proposes a hybrid method, MetaOpt-SIG &amp; EM, which integrates Remote Electrical Tilt (RET) antennas configured via the Operations Support System (OSS) platform and is compatible with Self-Organizing Network (SON) mechanisms for centralized and cost-effective reconfiguration. The approach combines metaheuristic algorithms, Geographic Information Systems (GIS), and electromagnetic (EM) propagation models to optimize antenna tilt. The objective is to maximize radio coverage measured by the Reference Signal Received Power (RSRP) while minimizing inter-cell interference expressed by the Carrier-to-Interference ratio (C/I). The method is applied to a 13.5 km<sup>2</sup> urban area in downtown Oran, covered by the Algerie Telecom Mobilis (ATM Mobilis) Long Term Evolution Advanced (LTE-A) network. Out of 32 existing sites, 19 (representing 55 sector cells) were selected for optimization. Four scenarios were compared: default tilt configuration, the operator’s current configuration, single objective optimization based on RSRP, and multi-objective optimization considering both RSRP and C/I. The results show that the multi-objective strategy offers the best trade-off between coverage and interference management. The Particle Swarm Optimization (PSO) algorithm outperformed the Genetic Algorithm (GA) in terms of convergence speed and overall performance. These findings confirm the relevance of the MetaOpt-SIG &amp; EM approach for optimizing cellular networks in real-world environments, particularly within ATM Mobilis deployments.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Radio Network Optimization Through Antenna Tilt Adjustment Using Metaheuristic Algorithms and Geographic Information Systems

  • 期刊论文

  • 发表日期：

    2026年3月17日

查看全文
  • Hicham Megnafi,
  • Zoheir Karaouzene,
  • Sidi Mohammed Meriah,
  • Lotfi Merad

摘要

With the increasing densification of cellular networks and the evolution toward next-generation technologies such as Fifth Generation (5G) and Sixth Generation (6G), optimizing radio parameters has become essential to ensure effective coverage and satisfactory Quality of Service (QoS). This study proposes a hybrid method, MetaOpt-SIG & EM, which integrates Remote Electrical Tilt (RET) antennas configured via the Operations Support System (OSS) platform and is compatible with Self-Organizing Network (SON) mechanisms for centralized and cost-effective reconfiguration. The approach combines metaheuristic algorithms, Geographic Information Systems (GIS), and electromagnetic (EM) propagation models to optimize antenna tilt. The objective is to maximize radio coverage measured by the Reference Signal Received Power (RSRP) while minimizing inter-cell interference expressed by the Carrier-to-Interference ratio (C/I). The method is applied to a 13.5 km2 urban area in downtown Oran, covered by the Algerie Telecom Mobilis (ATM Mobilis) Long Term Evolution Advanced (LTE-A) network. Out of 32 existing sites, 19 (representing 55 sector cells) were selected for optimization. Four scenarios were compared: default tilt configuration, the operator’s current configuration, single objective optimization based on RSRP, and multi-objective optimization considering both RSRP and C/I. The results show that the multi-objective strategy offers the best trade-off between coverage and interference management. The Particle Swarm Optimization (PSO) algorithm outperformed the Genetic Algorithm (GA) in terms of convergence speed and overall performance. These findings confirm the relevance of the MetaOpt-SIG & EM approach for optimizing cellular networks in real-world environments, particularly within ATM Mobilis deployments.