<p>In 5G and beyond networks, device-to-device (D2D) communication has become a crucial method for improving spectrum efficiency, reducing latency, and offloading cellular infrastructure due to the exponential growth in data traffic and user density. This paper presents a particle swarm optimization (PSO)-based multi-objective enhanced dynamic resource allocation (PSO-MO-EDRA) scheme for D2D communication underlaying cellular networks. The proposed framework jointly optimizes four key performance metrics: sum rate, outage probability, spectrum utilization, and fairness. To achieve this, PSO-MO-EDRA integrates SINR-aware resource initialization, distance-based adaptive power control, and a multi-objective fitness function with penalty constraints to guarantee minimum user connectivity and QoS. The system model incorporates realistic elements, including user mobility (Random Waypoint), Rayleigh fading, background and multi-cell interference, and cellular user interference, with SINR thresholds based on 3GPP standards. Simulation results show that PSO-MO-EDRA outperforms benchmark methods, achieving 50% higher sum rate, 75% lower outage probability, 15% higher spectrum utilization, and 20% improved fairness. These outcomes validate PSO-MO-EDRA as an efficient, scalable, and low-complexity solution for QoS-aware resource management in dense D2D-enabled wireless networks.</p>

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Multi-objective PSO-based dynamic distance-aware resource allocation with adaptive power control for device-to-device (D2D) communications

  • Abdullah H. Al-Quhali,
  • Mardeni Roslee,
  • Osama Abuajwa,
  • Mohamad Y. Alias

摘要

In 5G and beyond networks, device-to-device (D2D) communication has become a crucial method for improving spectrum efficiency, reducing latency, and offloading cellular infrastructure due to the exponential growth in data traffic and user density. This paper presents a particle swarm optimization (PSO)-based multi-objective enhanced dynamic resource allocation (PSO-MO-EDRA) scheme for D2D communication underlaying cellular networks. The proposed framework jointly optimizes four key performance metrics: sum rate, outage probability, spectrum utilization, and fairness. To achieve this, PSO-MO-EDRA integrates SINR-aware resource initialization, distance-based adaptive power control, and a multi-objective fitness function with penalty constraints to guarantee minimum user connectivity and QoS. The system model incorporates realistic elements, including user mobility (Random Waypoint), Rayleigh fading, background and multi-cell interference, and cellular user interference, with SINR thresholds based on 3GPP standards. Simulation results show that PSO-MO-EDRA outperforms benchmark methods, achieving 50% higher sum rate, 75% lower outage probability, 15% higher spectrum utilization, and 20% improved fairness. These outcomes validate PSO-MO-EDRA as an efficient, scalable, and low-complexity solution for QoS-aware resource management in dense D2D-enabled wireless networks.