Beam Elimination Based on Sequentially Estimated a Posteriori Probabilities of Winning

A robust and adaptive variable length beam selection strategy based on M-ary sequential competition was proposed in [1]. It was enhanced by the elimination of inauspicious beams during the ongoing competition to improve the efficiency and speed of the training in [2]. In this paper, we refine the elimination process by introducing a new elimination mechanism based on estimated winning probability i.e. probability of being the strongest candidate for each beam at each time step. These probabilities are calculated using sequentially estimated a posterirori PDFs of the unknown signal amplitudes after beamforming. This way least promising beams that fail to promise a minimum predefined winning probability can be eliminated from the remaining candidates as early as possible.