A hybrid PSO-GWO-based phase shift design for a hybrid-RIS-aided heterogeneous network system

Area of Science:

• Wireless Communications
• Metamaterials
• Optimization Techniques

Background:

• Reconfigurable intelligent surfaces (RIS) enhance spectral efficiency (SE) in heterogeneous networks (HetNets).
• Optimizing phase shifts in hybrid RIS (H-RIS) for HetNets remains a challenge.
• Existing research often overlooks hybrid metaheuristic approaches for H-RIS phase control.

Purpose of the Study:

• To investigate the performance of a hybrid reconfigurable intelligent surface (H-RIS) in a HetNet.
• To propose and evaluate a hybrid metaheuristic optimization technique for H-RIS phase shifts.
• To demonstrate SE gains using a partially active H-RIS compared to passive and fully active RIS.

Main Methods:

• A hybrid RIS (H-RIS) with 8% active elements was proposed for signal reflection and amplification.
• Transmit beamforming at the SBS utilized a zero-forcing approach.
• Hybrid RIS phase shift optimization employed the hybrid PSO-GWO (HPSOGWO) metaheuristic, combining Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO).

Main Results:

• The HPSOGWO method achieved significant spectral efficiency improvements.
• The proposed H-RIS method with modest active elements outperformed passive RIS with SDR optimization.
• The H-RIS approach also surpassed fully active RIS with Lagrange multiplier (LM) phase shift design.

Conclusions:

• Hybrid RIS, optimized with hybrid metaheuristics, offers substantial SE gains in HetNets.
• Partially active H-RIS presents an efficient alternative to fully active or passive RIS.
• The HPSOGWO technique effectively optimizes hybrid RIS phase shifts for enhanced wireless network performance.