Tadele A Abose, Thomas O Olwal, Abel D Daniel, Murad R Hassen,
Volume 20, Issue 3 (9-2024)
Abstract
Due to cost and energy concerns with digital beamformers, much of the beamforming is done by hybrid beamformers in mm-wave (mm) massive multiple input multiple output (MIMO). Various works in hybrid beamforming structures considered either phase shifters, switches, or radio frequency lenses individually as switching mechanisms between antennas and precoding systems. Works that consider the hybrid use of phase shifters, switches, and radio frequency lenses need further investigation since there is a tradeoff between cost and system performance in each switching mechanism. The main aim of this research is to analyze the performance of a hybrid switch, a 1-bit phase shifter, and radio frequency (RF)-Lens in a hybrid beamforming network as a switching network. Simulation results showed that the hybrid of three has a spectral efficiency (SE) performance of 59.04 bps/Hz, which increases by 6.9 bps/Hz from that of the switch and lens antenna array network. The energy efficiency (EE) of the switch, phase shifter, and lens showed a performance of 46.41 bps/Hz/W, while the switch and lens antenna array, phase shifter, and lens antenna array showed a performance of 48.52 bps/Hz/W. The result also shows that the hybrid network achieves optimum performance at the expense of higher computational complexity.
Mousa Abdollahvand, Sima Sobhi-Givi,
Volume 21, Issue 1 (3-2025)
Abstract
This paper introduces a new method for improving wireless communication systems by employing beyond diagonal reconfigurable intelligent surfaces (BD-RIS) and unmanned aerial vehicle (UAV) alongside deep reinforcement learning (DRL) techniques. BD-RIS represents a departure from traditional RIS designs, providing advanced capabilities for manipulating electromagnetic waves to optimize the performance of communication. We propose a DRL-based framework for optimizing the UAV and configuration of BD-RIS elements, including hybrid beamforming, phase shift adjustments, and transmit power coefficients for non-orthogonal multiple access (NOMA) transmission by considering max-min fairness. Through extensive simulations and performance evaluations, we demonstrate that BD-RIS outperforms conventional RIS architectures. Additionally, we analyze the convergence speed and performance trade-offs of different DRL algorithms, emphasizing the importance of selecting the appropriate algorithm and hyper-parameters for specific applications. Our findings underscore the transformative potential of BD-RIS and DRL in enhancing wireless communication systems, laying the groundwork for next-generation network optimization and deployment.
