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. It was enhanced by the elimination of inauspicious beams during the ongoing competition to improve the efficiency and speed of the training. 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.