TY - GEN
T1 - User Association to Overcome Human Blockage at mmWave Cellular Networks
AU - Yuva Kumar, S.
AU - Ohtsuki, Tomoaki
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - The large spectral bandwidth at millimeter-wave (mmWave) frequencies provides a mean to achieve very high data rates in wireless communication systems. A unique characteristic of mmWave is that mmWave links are very sensitive to blockage and have large propagation path loss, which exhibits low line-of-sight (LoS) probability, unstable connectivity and unreliable communication. To overcome such challenges, one of the existing solution is to associate the user equipment (UE) with other available Base Stations (BSs) by handover (HO) if the serving BS is blocked. In this paper, for a pedestrian scenario, we propose two reinforcement learning (RL) based user association algorithms, which accounts for the past experience of the blockage on the position of the UE. One focuses on the reward to increase the sum LoS probability and is named as Blockage-Aware User Association (BAUA). The other focuses on the reward to balance the tradeoff between the throughput and the LoS probability and is named as modified BAUA. Simulation results show that the BAUA algorithm increased sum LoS probability and the modified BAUA algorithm show better trade-off between the throughput and the LoS probability than the maximum Signal-to-Interference-plus-Noise Ratio (SINR) based and maximum-throughput based user association algorithms.
AB - The large spectral bandwidth at millimeter-wave (mmWave) frequencies provides a mean to achieve very high data rates in wireless communication systems. A unique characteristic of mmWave is that mmWave links are very sensitive to blockage and have large propagation path loss, which exhibits low line-of-sight (LoS) probability, unstable connectivity and unreliable communication. To overcome such challenges, one of the existing solution is to associate the user equipment (UE) with other available Base Stations (BSs) by handover (HO) if the serving BS is blocked. In this paper, for a pedestrian scenario, we propose two reinforcement learning (RL) based user association algorithms, which accounts for the past experience of the blockage on the position of the UE. One focuses on the reward to increase the sum LoS probability and is named as Blockage-Aware User Association (BAUA). The other focuses on the reward to balance the tradeoff between the throughput and the LoS probability and is named as modified BAUA. Simulation results show that the BAUA algorithm increased sum LoS probability and the modified BAUA algorithm show better trade-off between the throughput and the LoS probability than the maximum Signal-to-Interference-plus-Noise Ratio (SINR) based and maximum-throughput based user association algorithms.
KW - Handover Performance
KW - Line-of-sight probability
KW - Millimeter-wave communications
KW - Reinforcement Learning
UR - http://www.scopus.com/inward/record.url?scp=85088283255&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85088283255&partnerID=8YFLogxK
U2 - 10.1109/VTC2020-Spring48590.2020.9129407
DO - 10.1109/VTC2020-Spring48590.2020.9129407
M3 - Conference contribution
AN - SCOPUS:85088283255
T3 - IEEE Vehicular Technology Conference
BT - 2020 IEEE 91st Vehicular Technology Conference, VTC Spring 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 91st IEEE Vehicular Technology Conference, VTC Spring 2020
Y2 - 25 May 2020 through 28 May 2020
ER -