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<p>Optimizing energy efficiency and spectrum efficiency metrics of a 5G small cell ultra-dense network (UDN) is crucial for maximizing the network capacity and performance. However, these two objectives often trade off against each other, posing a significant design challenge. It is also observed that the existing studies on 5G UDN employ metaheuristics, such as the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) for network optimization that introduces substantial algorithmic complexity. This paper proposes an innovative Multi-Objective Superiority Index-based Fuzzy Genetic Algorithm (MOSI-FGA) for intelligent resource allocation and cell planning framework in 5G UDN. The MOSI-FGA demonstrates reduced algorithmic complexity compared to the NSGA-II Algorithm. MOSI-FGA incorporates the concept of Superiority Index calculation to evaluate chromosome’s fitness in GA’s population. The MOSI-FGA further employs a fuzzy logic controller (FLC) that dynamically optimizes crossover and mutation rates to improve genetic diversity of the population. The MOSI-FGA driven resource allocation and cell planning framework perceives the 5G UDN design as a multi-objective optimization problem and jointly maximizes the energy efficiency and spectrum efficiency through optimal resource block allocation and transmission power distribution to the user equipment of the UDN. Simulation results demonstrate&#xa0;that the&#xa0;proposed&#xa0;MOSI-FGA based optimization&#xa0;technique&#xa0;achieves&#xa0;9.34 Mbits/s/W energy efficiency and&#xa0;spectrum efficiency of&#xa0;4.73 bits/s/Hz&#xa0;for the 5G UDN,&#xa0;outperforming&#xa0;other state-of-the-art 5G resource allocation&#xa0;techniques.</p>

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MOSI-FGA: A Lightweight Multi-Objective Superiority Index Based Fuzzy Genetic Algorithm optimizing 5G UDN

  • 期刊论文

  • 发表日期：

    2025年9月2日

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  • Abhishek Gupta,
  • Satya Sai Srikant

摘要

Optimizing energy efficiency and spectrum efficiency metrics of a 5G small cell ultra-dense network (UDN) is crucial for maximizing the network capacity and performance. However, these two objectives often trade off against each other, posing a significant design challenge. It is also observed that the existing studies on 5G UDN employ metaheuristics, such as the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) for network optimization that introduces substantial algorithmic complexity. This paper proposes an innovative Multi-Objective Superiority Index-based Fuzzy Genetic Algorithm (MOSI-FGA) for intelligent resource allocation and cell planning framework in 5G UDN. The MOSI-FGA demonstrates reduced algorithmic complexity compared to the NSGA-II Algorithm. MOSI-FGA incorporates the concept of Superiority Index calculation to evaluate chromosome’s fitness in GA’s population. The MOSI-FGA further employs a fuzzy logic controller (FLC) that dynamically optimizes crossover and mutation rates to improve genetic diversity of the population. The MOSI-FGA driven resource allocation and cell planning framework perceives the 5G UDN design as a multi-objective optimization problem and jointly maximizes the energy efficiency and spectrum efficiency through optimal resource block allocation and transmission power distribution to the user equipment of the UDN. Simulation results demonstrate that the proposed MOSI-FGA based optimization technique achieves 9.34 Mbits/s/W energy efficiency and spectrum efficiency of 4.73 bits/s/Hz for the 5G UDN, outperforming other state-of-the-art 5G resource allocation techniques.