TY - GEN
T1 - Statistical AoI, Delay, and Error-Rate Bounded QoS Provisioning for Satellite-Terrestrial Integrated Networks
AU - Wang, Jingqing
AU - Cheng, Wenchi
AU - Poor, H. Vincent
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Massive ultra-reliable and low latency communications (mURLLC) has emerged to support wireless time/error-sensitive services, which has attracted significant research attention while imposing several unprecedented challenges not encountered before. By leveraging the significant improvements in space-aerial-terrestrial resources for comprehensive 3D coverage, satellite-terrestrial integrated networks have been proposed to achieve rigorous and diverse quality-of-services (QoS) constraints of mURLLC. To effectively measure data freshness in satellite communications, recently, age of information (AoI) has surfaced as a novel QoS criterion for ensuring time-critical applications. Nevertheless, because of the complicated and dynamic nature of network environments, how to efficiently model multi-dimensional statistical QoS provisioning while upper-bounding peak AoI, delay, and error-rate for diverse network segments is still largely open. To address these issues, in this paper we propose statistical QoS provisioning schemes over satellite-terrestrial integrated networks in the finite blocklength regime. In particular, first we establish a satellite-terrestrial integrated wireless network architecture model and an AoI metric model. Second, we derive a series of fundamental statistical QoS metrics including peak-AoI bounded QoS exponent, delay-bounded QoS exponent, and error-rate bounded QoS exponent. Finally, we conduct a set of simulations to validate and evaluate our proposed statistical QoS provisioning schemes over satellite-terrestrial integrated networks.
AB - Massive ultra-reliable and low latency communications (mURLLC) has emerged to support wireless time/error-sensitive services, which has attracted significant research attention while imposing several unprecedented challenges not encountered before. By leveraging the significant improvements in space-aerial-terrestrial resources for comprehensive 3D coverage, satellite-terrestrial integrated networks have been proposed to achieve rigorous and diverse quality-of-services (QoS) constraints of mURLLC. To effectively measure data freshness in satellite communications, recently, age of information (AoI) has surfaced as a novel QoS criterion for ensuring time-critical applications. Nevertheless, because of the complicated and dynamic nature of network environments, how to efficiently model multi-dimensional statistical QoS provisioning while upper-bounding peak AoI, delay, and error-rate for diverse network segments is still largely open. To address these issues, in this paper we propose statistical QoS provisioning schemes over satellite-terrestrial integrated networks in the finite blocklength regime. In particular, first we establish a satellite-terrestrial integrated wireless network architecture model and an AoI metric model. Second, we derive a series of fundamental statistical QoS metrics including peak-AoI bounded QoS exponent, delay-bounded QoS exponent, and error-rate bounded QoS exponent. Finally, we conduct a set of simulations to validate and evaluate our proposed statistical QoS provisioning schemes over satellite-terrestrial integrated networks.
KW - QoS exponents
KW - Statistical QoS provisioning
KW - finite blocklength coding
KW - mURLLC
KW - peak AoI
KW - satellite-terrestrial integrated networks
UR - http://www.scopus.com/inward/record.url?scp=85187387822&partnerID=8YFLogxK
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U2 - 10.1109/GLOBECOM54140.2023.10436889
DO - 10.1109/GLOBECOM54140.2023.10436889
M3 - Conference contribution
AN - SCOPUS:85187387822
T3 - Proceedings - IEEE Global Communications Conference, GLOBECOM
SP - 740
EP - 745
BT - GLOBECOM 2023 - 2023 IEEE Global Communications Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE Global Communications Conference, GLOBECOM 2023
Y2 - 4 December 2023 through 8 December 2023
ER -