TY - JOUR
T1 - Mobility and Blockage-Aware Communications in Millimeter-Wave Vehicular Networks
AU - Hussain, Muddassar
AU - Scalabrin, Maria
AU - Rossi, Michele
AU - Michelusi, Nicolo
N1 - Funding Information:
Manuscript received November 21, 2019; revised April 26, 2020 and July 15, 2020; accepted August 25, 2020. Date of publication September 1, 2020; date of current version November 12, 2020. This work was supported in part by NSF under Grant CNS-1642982, in part by MIUR (Italian Ministry of Education, University and Research) through the initiative “Departments of Excellence” (Law 232/2016), and in part by the EU MSCA ITN Project SCAVENGE “Sustainable Cellular Networks Harvesting Ambient Energy” (Project 675891). The review of this article was coordinated by Prof. J. Liu. (Corresponding author: Muddassar Hussain.) Muddassar Hussain and Nicolò Michelusi are with the School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47906 USA (e-mail: hussai13@purdue.edu; michelus@purdue.edu).
Funding Information:
This work has been supported, in part, by NSF under Grant CNS-1642982, by MIUR (Italian Ministry of Education, University and Research) through the initiative “Departments of Excellence” (Law 232/2016) and by the EU MSCA ITN Project SCAVENGE “Sustainable Cellular Networks Harvesting Ambient Energy” (Project no. 675891). The views and opinions expressed in this article are those of the authors and do not necessarily reflect those of the funding institutions.
Publisher Copyright:
© 1967-2012 IEEE.
PY - 2020/11
Y1 - 2020/11
N2 - Mobility may degrade the performance of next-generation vehicular networks operating at the millimeter-wave spectrum: frequent mis-alignment and blockages require repeated beam-training and handover, with enormous overhead. Nevertheless, mobility induces temporal correlations in the communication beams and in blockage events. In this paper, an adaptive design is proposed, that learns and exploits these temporal correlations to reduce the beam-training overhead and make handover decisions. At each time-slot, the serving base station (BS) decides to perform either beam-training, data communication, or handover, under uncertainty in the system state. The decision problem is cast as a partially observable Markov decision process, with the goal to maximize the throughput delivered to the user, under an average power constraint. To address the high-dimensional optimization, an approximate constrained point-based value iteration (C-PBVI) method is developed, which simultaneously optimizes the primal and dual functions to meet the power constraint. Numerical results demonstrate a good match between the analysis and a simulation based on 2D mobility and 3D analog beamforming via uniform planar arrays at both BSs and UE, and reveal that C-PBVI performs near-optimally, and outperforms a baseline scheme with periodic beam-training by 38% in spectral efficiency. Motivated by the structure of C-PBVI, two heuristics are proposed, that trade complexity with sub-optimality, and achieve only 4% and 15% loss in spectral efficiency. Finally, the effect of mobility and multiple users on blockage dynamics is evaluated numerically, demonstrating superior performance over the baseline scheme.
AB - Mobility may degrade the performance of next-generation vehicular networks operating at the millimeter-wave spectrum: frequent mis-alignment and blockages require repeated beam-training and handover, with enormous overhead. Nevertheless, mobility induces temporal correlations in the communication beams and in blockage events. In this paper, an adaptive design is proposed, that learns and exploits these temporal correlations to reduce the beam-training overhead and make handover decisions. At each time-slot, the serving base station (BS) decides to perform either beam-training, data communication, or handover, under uncertainty in the system state. The decision problem is cast as a partially observable Markov decision process, with the goal to maximize the throughput delivered to the user, under an average power constraint. To address the high-dimensional optimization, an approximate constrained point-based value iteration (C-PBVI) method is developed, which simultaneously optimizes the primal and dual functions to meet the power constraint. Numerical results demonstrate a good match between the analysis and a simulation based on 2D mobility and 3D analog beamforming via uniform planar arrays at both BSs and UE, and reveal that C-PBVI performs near-optimally, and outperforms a baseline scheme with periodic beam-training by 38% in spectral efficiency. Motivated by the structure of C-PBVI, two heuristics are proposed, that trade complexity with sub-optimality, and achieve only 4% and 15% loss in spectral efficiency. Finally, the effect of mobility and multiple users on blockage dynamics is evaluated numerically, demonstrating superior performance over the baseline scheme.
KW - Blockage
KW - Markov decision process
KW - beam training
KW - handover
KW - millimeter wave
KW - point based value iteration
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U2 - 10.1109/TVT.2020.3020898
DO - 10.1109/TVT.2020.3020898
M3 - Article
AN - SCOPUS:85089416841
VL - 69
SP - 13072
EP - 13086
JO - IEEE Transactions on Vehicular Communications
JF - IEEE Transactions on Vehicular Communications
SN - 0018-9545
IS - 11
M1 - 9184011
ER -