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<p>The emergence of 5G New Radio (NR) networks marks a significant advancement in connectivity and data transmission capabilities, presenting a host of novel challenges in effectively managing resources. Conversely, optimizing resource allocation for multicast sessions requires narrower antenna directivities, creating a trade-off between the demands of different types of traffic, ultimately influencing decisions regarding system deployment. This paper proposes a new smart resource allocation technique for 5G NR networks. The challenge of resource allocation is conceptualized as a stochastic optimization problem. To solve this, optimal resource allocation is performed through a new Improved optimization algorithm called Self Improved-Lyrebird Optimization Algorithm (SI-LOA). This optimization is the inspiration of the hunting behavior of Lyrebird. Moreover, this optimization is performed under the consideration of parameters like throughput and path loss. The proposed work ensures the maximization of average throughput utility and maintain the network stability. The SI-LOA scheme exhibited a cost rate of 0.1249, while LOA, KOA, RPO, COA, and JSO yielded maximal cost values of 0.1251, 0.1255, 0.1252, 0.1253, and 0.1254, respectively. Theoretical analyses and simulation outcomes assess the effectiveness of our suggested method within the context of network stability assumptions.</p>

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Intelligent resource allocation technique for 5G NR self-organizing networks via self-improved lyrebird optimization algorithm

  • 期刊论文

  • 发表日期：

    2026年6月29日

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  • Jyoti Sharma,
  • Amandeep Noliya,
  • Dharmender Kumar,
  • Kulbir Kumar

摘要

The emergence of 5G New Radio (NR) networks marks a significant advancement in connectivity and data transmission capabilities, presenting a host of novel challenges in effectively managing resources. Conversely, optimizing resource allocation for multicast sessions requires narrower antenna directivities, creating a trade-off between the demands of different types of traffic, ultimately influencing decisions regarding system deployment. This paper proposes a new smart resource allocation technique for 5G NR networks. The challenge of resource allocation is conceptualized as a stochastic optimization problem. To solve this, optimal resource allocation is performed through a new Improved optimization algorithm called Self Improved-Lyrebird Optimization Algorithm (SI-LOA). This optimization is the inspiration of the hunting behavior of Lyrebird. Moreover, this optimization is performed under the consideration of parameters like throughput and path loss. The proposed work ensures the maximization of average throughput utility and maintain the network stability. The SI-LOA scheme exhibited a cost rate of 0.1249, while LOA, KOA, RPO, COA, and JSO yielded maximal cost values of 0.1251, 0.1255, 0.1252, 0.1253, and 0.1254, respectively. Theoretical analyses and simulation outcomes assess the effectiveness of our suggested method within the context of network stability assumptions.