Weight-driven particle swarm optimization for power allocation in dual-band millimeter wave heterogeneous networks

Dual-band millimeter-wave (mmWave) heterogeneous networks (HetNets) operating at 28 and 73 GHz offer high capacity, but interference-coupled SINR, subchannel reuse, and per-base-station power constraints make transmit-power allocation nonconvex. This paper proposes Weight-Driven Particle Swarm Optimization (WD-PSO), which uses a recursively decaying weight to jointly regulate particle momentum and attraction strength. WD-PSO is evaluated against five PSO variants, Equal Power Allocation, Random Feasible Search, and Differential Evolution (DE) over 30 paired Monte Carlo realizations. Results show that WD-PSO achieves final throughput comparable to the strongest PSO variants while consistently outperforming the additional baselines. Across 𝐾 = 5 and 𝐾 = 1 0 , WD-PSO improves throughput over DE by 4.48–6.10%. Its mean throughput varies by less than 0.8% across a 5000-fold range of the initialization coefficient 𝛼 . Scalability analysis further shows near-linear runtime growth with population size and iteration count, supporting a practical balance between solution quality, robustness, and computational cost.