Swarm Intelligence Optimization of Multi-RIS Aided MmWave Beamspace MIMO
By: Zaid Abdullah , Mario R. Camana , Abuzar B. M. Adam and more
Potential Business Impact:
Makes wireless signals reach through walls better.
We investigate the performance of a multiple reconfigurable intelligence surface (RIS)-aided millimeter wave (mmWave) beamspace multiple-input multiple-output (MIMO) system with multiple users (UEs). We focus on a challenging scenario in which the direct links between the base station (BS) and all UEs are blocked, and communication is facilitated only via RISs. The maximum ratio transmission (MRT) is utilized for data precoding, while a low-complexity algorithm based on particle swarm optimization (PSO) is designed to jointly perform beam selection, power allocation, and RIS profile configuration. The proposed optimization approach demonstrates positive trade-offs between the complexity (in terms of running time) and the achievable sum rate. In addition, our results demonstrate that due to the sparsity of beamspace channels, increasing the number of unit cells (UCs) at RISs can lead to higher achievable rates than activating a larger number of beams at the MIMO BS.
Similar Papers
Multi-beam Beamforming in RIS-aided MIMO Subject to Reradiation Mask Constraints -- Optimization and Machine Learning Design
Optimization and Control
Improves phone signals by bouncing them smartly.
Experimental Evaluation of Multiple Active RISs for 5G MIMO Commercial Networks
Information Theory
Boosts phone internet speed with smart signal mirrors.
RIS-Assisted Survivable Fronthaul Design in Cell-Free Massive MIMO System
Information Theory
Makes cell towers work even if cables break.