Scholarlink

<p>The evolution of fifth-generation New Radio (5G-NR) networks has introduced Dual Connectivity (DC) as a powerful feature, enhancing network capacity by allowing simultaneous connectivity to multiple Radio Access Technologies (RATs), namely 5G-NR and fourth-generation LTE (4G-LTE). This study addresses a persistent challenge in DC-enabled heterogeneous networks (HetNets): optimizing power consumption while maximizing network capacity. Unlike prior works, which focused solely on either power or capacity optimization, this research pioneers a balanced approach for Non-Standalone (NSA) deployment, utilizing a novel base station (BS) pairing strategy to manage Next Generation NodeB (gNB) sleep cycles. Two innovative algorithms, the Super Greedy Algorithm and ILP-Greedy Algorithm, are introduced to refine power savings while boosting user throughput. ILP-Greedy leverages Integer Linear Programming for power minimization, augmented by a greedy approach for user association, demonstrating a 7.02% improvement in power conservation over standard benchmarks. Meanwhile, the Super Greedy Algorithm outperforms baseline models in both power savings and capacity gains, setting new standards for sustainable DC deployment in 5G-NR/4G-LTE NSA HetNets. This work’s insights advance green networking strategies crucial for next-gen wireless systems.</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

Next-Gen Green HetNets: A Dual Connectivity Approach To Optimized Capacity and Power Management in 5G-NR/4G-LTE

  • 期刊论文

  • 发表日期：

    2025年10月22日

查看全文
  • Nur Anisya Anis Binti Syukri,
  • Siva Priya Thiagarajah,
  • Made Harta Dwijaksara,
  • Md Tanjil Sarker,
  • Md. Golam Sadeque

摘要

The evolution of fifth-generation New Radio (5G-NR) networks has introduced Dual Connectivity (DC) as a powerful feature, enhancing network capacity by allowing simultaneous connectivity to multiple Radio Access Technologies (RATs), namely 5G-NR and fourth-generation LTE (4G-LTE). This study addresses a persistent challenge in DC-enabled heterogeneous networks (HetNets): optimizing power consumption while maximizing network capacity. Unlike prior works, which focused solely on either power or capacity optimization, this research pioneers a balanced approach for Non-Standalone (NSA) deployment, utilizing a novel base station (BS) pairing strategy to manage Next Generation NodeB (gNB) sleep cycles. Two innovative algorithms, the Super Greedy Algorithm and ILP-Greedy Algorithm, are introduced to refine power savings while boosting user throughput. ILP-Greedy leverages Integer Linear Programming for power minimization, augmented by a greedy approach for user association, demonstrating a 7.02% improvement in power conservation over standard benchmarks. Meanwhile, the Super Greedy Algorithm outperforms baseline models in both power savings and capacity gains, setting new standards for sustainable DC deployment in 5G-NR/4G-LTE NSA HetNets. This work’s insights advance green networking strategies crucial for next-gen wireless systems.