Chuluunbandi Naimannaran

Resource allocation that is both energy-efficient and fair remains a persistent challenge in 5G, beyond-5G, and emerging 6G networks, where users with heterogeneous service requirements compete for limited radio resources. Although rate-splitting multiple access (RSMA) is commonly investigated through physical-layer models, service-level datasets often contain demand indicators without channel matrices, beamforming variables, or stream-level power parameters. We develop and evaluate a QoS-driven allocation framework based on three allocation-inspired models: an RSMA-inspired balanced model, a NOMA-inspired signal-strength-aware model, and an OFDMA proportional-fair reference model. Four metaheuristic optimizers—Genetic algorithm(GA), simulated annealing (SA), particle swarm optimization (PSO), and ant colony optimization (ACO)—are applied to the same QoS demand profile, resource budget, constraints, feasibility-repair procedure, and performance measures, producing 12 model–optimizer combinations. The input comprises 400 user records, including 393 records with positive bandwidth requirements and seven records with zero bandwidth. Each method was evaluated over 30 independent runs. Under this QoS-level abstraction, RSMA-PSO produced the highest mean fitness and energy-efficiency values, whereas RSMA-GA achieved the strongest composite balance across fitness, energy efficiency, fairness, and satisfaction. The mean fitness of RSMA-GA was 9.32% higher than that of NOMA-GA and 18.00% higher than that of OFDMA-PF-GA. These results characterize allocation behavior under a shared QoS profile and should not be interpreted as full physical-layer validation of RSMA, NOMA, or OFDMA transmission.

This letter presents an analysis of the toroidal-core energy (TCE) harvester that draws power from the near-field of a UHF leaky-feeder communication cable to supply ultra-low-power IoT sensor nodes deployed inside underground tunnels. The NiZn ferrite toroid (Ri = 38 mm, R0 = 63 mm, height = 25 mm, μi= 700, N = 7 turns) is coupled inductively to an RLK78-50JFNA leaky-feeder cable resonating at f0 = 416.5 MHz, the center of the 411–422 MHz operating sub-band. Full-wave simulations performed in CST Microwave Studio are experimentally validated with a 24 W UHF transmitter that establishes an in-tunnel near-field along the cable, and the harvester delivers VAC = 6.83 V and IAC = 71.4 mA at resonance under the 1 W simulation reference power, corresponding to an AC power-conversion efficiency of 48.8%. A two-stage HSMS-285P Schottky voltage doubler followed by a commercial RFD199A-PCB RF-DC converter regulates the output to 4.7 V DC, sufficient to power low-duty-cycle sensor nodes. A linear post-processing methodology is introduced to reconcile CST's 1 W port-power normalization with the parametric input-power sweep required for experimental verification, enabling rapid design exploration without re-running the solver. To the best of the authors’ knowledge, the proposed harvester is the first reported device to exploit the UHF leakage from a slotted radiating coaxial cable as a stationary power source for in-tunnel IoT applications.