{'fraction_non_alphanumeric': 0.02585604472396925, 'fraction_numerical': 0.0, 'mean_word_length': 5.851674641148326, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A unified beamforming structure for wireless multicasting and power transfer in MIMO systems

This paper studies the downlink beamforming design problem in multi-user multi-input-multi-output (MIMO) systems. Specifically, two related scenarios are considered: max-min signal-to-noise ratios (SNR) in wireless multicasting and max-min power in wireless power transfer (WPT). The conventional approach recasts the original nonconvex problems into convex semidefinite programming (SDP) by applying semidefinite relaxation (SDR) technique. This approach directly optimizes the transmit beamforming vector, thus suffers from high computational complexity when the number of transmit antennas at the base station (BS) is large. In this paper, we propose a unified and optimal beamforming structure which is expressed as a linear combination of the channel vectors of all users. With this proposed structure, the problem of beamforming design is thus simplified to optimize the combining weight vector, the dimension of which equals the number of users. This indirect optimization can significantly reduce the computational complexity of the transmit beamforming design, especially for massive MIMO systems. Numerical results show that by using the proposed beamforming structure, the complexity of indirect optimization is significantly reduced without suffering performance degradation, compared to the conventional direct optimization.