The transition to sixth-generation (6G) wireless networks focuses on fulfilling extraordinary demands for ultra-high data rates, extensive connectivity, and ultra-low latency. Achieving these goals requires extensive spectrum resources, particularly in the emerging millimeter-wave (mmWave) and terahertz (THz) frequency bands. Unfortunately, reliable communication at these frequencies is greatly hindered by high path loss, molecular absorption, blockage, and, even more so, the growing susceptibility to loss of line of sight. To combat these issues, path adaptive beamforming methods are critical in targeting narrow beams to improve link reliability. This work focuses on complete coverage of adaptive beamforming methods applied to 6G mmWave and THz communications, covering all forms of beamforming from fully analog to hybrid and digital architectures. This also includes recent machine learning advancements in beam alignment optimization, channel estimation, user tracking, and overhead minimization. Further, the paper details these systems' performance, complexity, and energy-efficient trade-off factors while putting forth open research opportunities towards developing intelligent, resilient, and adaptive beamforming techniques for next-generation wireless systems.
Kundra et al. (Mon,) studied this question.