TY - JOUR
T1 - Optimal Resource Allocations for Statistical QoS Provisioning to Support mURLLC over FBC-EH-Based 6G THz Wireless Nano-Networks
AU - Zhang, Xi
AU - Wang, Jingqing
AU - Poor, H. Vincent
N1 - Funding Information:
Manuscript received July 12, 2020; revised November 22, 2020 and February 20, 2021; accepted March 1, 2021. Date of publication April 8, 2021; date of current version May 18, 2021. The work of Xi Zhang and Jingqing Wang was supported in part by the U.S. National Science Foundation under Grant CCF-2008975, Grant ECCS-1408601, and Grant CNS-1205726, and in part by the U.S. Air Force under Grant FA9453-15-C-0423. The work of H. Vincent Poor was supported in part by the U.S. National Science Foundation under Grant CCF-0939370 and Grant CCF-1908308. (Corresponding author: Xi Zhang.) Xi Zhang and Jingqing Wang are with the Networking and Information Systems Laboratory, Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843 USA (e-mail: xizhang@ece.tamu.edu; wang12078@tamu.edu).
Publisher Copyright:
© 1983-2012 IEEE.
PY - 2021/6
Y1 - 2021/6
N2 - One of most important techniques for enabling the sixth-generation (6G) mobile wireless network lies in how to efficiently guarantee various stringent quality-of-service (QoS) performance-metrics to support the emerging massive Ultra-Reliable Low-Latency Communications (mURLLC) in 6G. Correspondingly, finite blocklength coding (FBC) has been developed as an effective technique to significantly improve various QoS indices for mURLLC through implementing short-packet communications. On the other hand, Terahertz (THz) band wireless nano-communications have been widely envisioned as a promising 6G technique to efficiently support utra-high data-rate (up to 1 Tbps). One of the major constraints over THz-band nano-networks is the severely limited energy that can be accessed by nano devices. Towards this end, various novel energy harvesting (EH) mechanisms have been proposed to remedy the energy scarcity problem. However, how to accurately characterize the relationships among THz wireless channels, energy consumption, and EH models for FBC based nano communications remains a challenging problem to support statistical delay and error-rate bounded QoS provisioning over FBC based 6G THz wireless nano-networks. To overcome these challenges, in this paper we propose optimal resource allocation policies to achieve the maximum \epsilon -effective capacity in the THz band over FBC-EH-based nano-networks. Particularly, we establish nano-scale system models and characterize wireless channel models in the THz band using FBC. In order to support statistical delay and error-rate bounded QoS provisioning, we formulate and solve the \epsilon -effective capacity maximization problem under several different EH constraints for our proposed schemes. Simulation results are included, which validate and evaluate our proposed schemes in the finite blocklength regime.
AB - One of most important techniques for enabling the sixth-generation (6G) mobile wireless network lies in how to efficiently guarantee various stringent quality-of-service (QoS) performance-metrics to support the emerging massive Ultra-Reliable Low-Latency Communications (mURLLC) in 6G. Correspondingly, finite blocklength coding (FBC) has been developed as an effective technique to significantly improve various QoS indices for mURLLC through implementing short-packet communications. On the other hand, Terahertz (THz) band wireless nano-communications have been widely envisioned as a promising 6G technique to efficiently support utra-high data-rate (up to 1 Tbps). One of the major constraints over THz-band nano-networks is the severely limited energy that can be accessed by nano devices. Towards this end, various novel energy harvesting (EH) mechanisms have been proposed to remedy the energy scarcity problem. However, how to accurately characterize the relationships among THz wireless channels, energy consumption, and EH models for FBC based nano communications remains a challenging problem to support statistical delay and error-rate bounded QoS provisioning over FBC based 6G THz wireless nano-networks. To overcome these challenges, in this paper we propose optimal resource allocation policies to achieve the maximum \epsilon -effective capacity in the THz band over FBC-EH-based nano-networks. Particularly, we establish nano-scale system models and characterize wireless channel models in the THz band using FBC. In order to support statistical delay and error-rate bounded QoS provisioning, we formulate and solve the \epsilon -effective capacity maximization problem under several different EH constraints for our proposed schemes. Simulation results are included, which validate and evaluate our proposed schemes in the finite blocklength regime.
KW - 6G wireless nano-networks
KW - EH
KW - FBC
KW - Iu-effective capacity
KW - Statistical delay and error-rate bounded QoS
KW - THz band
KW - joint resource allocation
KW - mutual information
UR - http://www.scopus.com/inward/record.url?scp=85104201919&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85104201919&partnerID=8YFLogxK
U2 - 10.1109/JSAC.2021.3071816
DO - 10.1109/JSAC.2021.3071816
M3 - Article
AN - SCOPUS:85104201919
SN - 0733-8716
VL - 39
SP - 1544
EP - 1560
JO - IEEE Journal on Selected Areas in Communications
JF - IEEE Journal on Selected Areas in Communications
IS - 6
M1 - 9398935
ER -