Beamforming Innovations in Emerging Communication Systems
The field of beamforming in emerging communication systems is witnessing significant advancements, particularly in the areas of Terahertz (THz) and millimeter wave (mmWave) communications. Researchers are focusing on developing robust and efficient beamforming techniques to address hardware imperfections and optimize system performance. Key innovations include the use of deep neural networks (DNN) for hardware imperfection compensation in THz systems, and novel optimization methods for continuous aperture array (CAPA) systems, which promise substantial gains over conventional discrete arrays. Additionally, there is a growing emphasis on ensuring covert communication and maximizing fairness in multi-user scenarios, with notable progress in hybrid beamforming designs and rate splitting multiple access (RSMA) techniques.
Noteworthy papers include one that proposes a two-stage DNN-based compensation algorithm for THz hybrid beamforming, significantly reducing hardware imperfection effects while maintaining performance. Another standout contribution is the optimal beamforming design for CAPA systems, which introduces a monotonic optimization method to achieve globally optimal solutions. These advancements collectively push the boundaries of what is possible in next-generation wireless communication systems, ensuring higher efficiency, robustness, and fairness in beamforming strategies.
Noteworthy Papers
- A two-stage DNN-based compensation algorithm for THz hybrid beamforming significantly reduces hardware imperfection effects while maintaining performance.
- Optimal beamforming design for CAPA systems introduces a monotonic optimization method to achieve globally optimal solutions.
