TY - GEN
T1 - Massive-MIMO Based Statistical QoS Provisioning for mURLLC Over 6G UAV Mobile Wireless Networks
AU - Zhang, Xi
AU - Zhu, Qixuan
AU - Poor, H. Vincent
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The sixth generation (6G) wireless networks are required to provide the massive ultra-reliable low-latency communication (mURLLC) services for massive subscribers, and thus, need to be supported by new techniques. Since the massive multiple-input multiple-output (massive MIMO) technique with massive antennas is able to substantially improve the channel performance, it has been widely applied to achieve the goal of mURLLC networks. Moreover, based on the inherent advantages of high mobility and dynamically deployment, the emerging unmanned aerial vehicle (UAV) technique has also been considered as one of the promising candidate techniques in the 6G wireless networks. However, how to integrate the massive MIMO and UAV techniques has never been thoroughly studied. In this paper, we first establish the massive MIMO channel model between a set of UAVs and a ground station, equipped with uniform rectangular antenna array. Then, we derive the expression of channel capacity for this channel model, which is a function of the distance between each UAV and each antenna. To support the mURLLC traffics in the 6G wireless networks, we employ the effective capacity theory to measure the maximum packet arrival rate, and we also derive the upper-bound on the effective capacity, which is a function of our obtained channel capacity. Finally, we validate and evaluate our derived results of the UAV communication with massive MIMO channel over 6G wireless networks through numerical analyses.
AB - The sixth generation (6G) wireless networks are required to provide the massive ultra-reliable low-latency communication (mURLLC) services for massive subscribers, and thus, need to be supported by new techniques. Since the massive multiple-input multiple-output (massive MIMO) technique with massive antennas is able to substantially improve the channel performance, it has been widely applied to achieve the goal of mURLLC networks. Moreover, based on the inherent advantages of high mobility and dynamically deployment, the emerging unmanned aerial vehicle (UAV) technique has also been considered as one of the promising candidate techniques in the 6G wireless networks. However, how to integrate the massive MIMO and UAV techniques has never been thoroughly studied. In this paper, we first establish the massive MIMO channel model between a set of UAVs and a ground station, equipped with uniform rectangular antenna array. Then, we derive the expression of channel capacity for this channel model, which is a function of the distance between each UAV and each antenna. To support the mURLLC traffics in the 6G wireless networks, we employ the effective capacity theory to measure the maximum packet arrival rate, and we also derive the upper-bound on the effective capacity, which is a function of our obtained channel capacity. Finally, we validate and evaluate our derived results of the UAV communication with massive MIMO channel over 6G wireless networks through numerical analyses.
KW - The sixth generation (6G) wireless communication
KW - effective capacity
KW - mURLLC
KW - massive multiple-input multiple-input (MIMO)
KW - statistical QoS provisioning
KW - uniform rectangular array (URA)
KW - unmanned aerial vehicles (UAV)
UR - http://www.scopus.com/inward/record.url?scp=85130691907&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85130691907&partnerID=8YFLogxK
U2 - 10.1109/WCNC51071.2022.9771841
DO - 10.1109/WCNC51071.2022.9771841
M3 - Conference contribution
AN - SCOPUS:85130691907
T3 - IEEE Wireless Communications and Networking Conference, WCNC
SP - 1850
EP - 1855
BT - 2022 IEEE Wireless Communications and Networking Conference, WCNC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE Wireless Communications and Networking Conference, WCNC 2022
Y2 - 10 April 2022 through 13 April 2022
ER -