Adaptive location-based millimetre wave beamforming using compressive sensing based channel estimation

Analogue beamforming is normally used in conjunction with millimetre wave (mmWave) communications to overcome the high propagation and penetration losses inherent in mmWave transmissions. Thus, producing a high-efficient mmWave beamforming using low beamforming training (BT) complexity turns to be a big challenge towards ubiquitous mmWave communications. In this study, low-complex and high-efficient adaptive mmWave BT using compressive sensing (CS) based channel estimation is introduced utilising mobile station (MS) localisation. In which, MS positioning is used to estimate the ranges of angle of departures and angle of arrivals of the mmWave channel considering the statistics of its angular spread. Then, an adaptive multi-level beam search using CS-based channel estimation is used to estimate the best transmit/receive beam for establishing the mmWave link. Thus, the antenna weight vectors of each beam searching level, i.e. the beamwidth and the number of beams, used for constructing the sensing matrix are adaptively adjusted. The high potency of the proposed mmWave BT scheme over the conventional ones in both BT complexity and performance is proved by the means of mathematical and simulation analysis.