Mobility and Blockage-aware Communications in Millimeter-Wave Vehicular Networks
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Mobility may degrade the performance of next-generation vehicular networks operating at the millimeter-wave spectrum: frequent loss of alignment and blockages require repeated beam training and handover, thus incurring huge overhead. In this paper, an adaptive and joint design of beam training, data transmission and handover is proposed, that exploits the mobility process of mobile users (MUs) and the dynamics of blockages to optimally trade-off throughput and power consumption. At each time slot, the serving base station decides to perform either beam training, data communication, or handover when blockage is detected. The decision problem is cast as a partially observable Markov decision process, and the goal is to maximize the throughput delivered to the MU, subject to an average power constraint. To address the high dimensionality of the problem, an approximate dynamic programming algorithm based on a variant of PERSEUS [1] is developed, where both the primal and dual functions are simultaneously optimized to meet the power constraint. Numerical results show that the PERSEUS-based policy has near-optimal performance, and achieves a 55 periodic beam training. Motivated by the structure of the PERSEUS-based policy, two heuristic policies with lower computational cost are proposed. These are shown to achieve a performance comparable to that of PERSEUS, with just a 10 loss in spectral efficiency.
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