TY - JOUR
T1 - Robust Resource Allocation for Vehicular Communications with Imperfect CSI
AU - Wu, Weihua
AU - Liu, Runzi
AU - Yang, Qinghai
AU - Quek, Tony Q.S.
N1 - Funding Information:
Manuscript received October 21, 2020; revised January 27, 2021 and March 21, 2021; accepted March 31, 2021. Date of publication April 12, 2021; date of current version September 10, 2021. This work was supported in part by the NSF China under Grant 61801365, Grant 61701365, and Grant 61971327; in part by the China Postdoctoral Science Foundation under Grant 2018M643581; in part by the Young Talent Fund of University Association for Science and Technology of Shaanxi Province under Grant 20200112; in part by the Natural Science Foundation of Shaanxi Province under Grant 2020JQ-686; in part by the Postdoctoral Foundation of Shaanxi Province; in part by the MOE ARF Tier 2 under Grant T2EP20120-0006; in part by the SUTD Growth Plan Grant for AI; in part by the Key Project of Ningbo under Grant 2019B10081; and in part by the Fundamental Research Funds for the Central Universities of China. The associate editor coordinating the review of this article and approving it for publication was X. Wang. (Corresponding author: Runzi Liu.) Weihua Wu and Qinghai Yang are with the State Key Laboratory of Integrated Services Network (ISN), School of Telecommunications Engineering, Xidian University, Xi’an 710071, China, and also with the Guangzhou Institute of Technology, Xidian University, Guangzhou 510555, China (e-mail: xdweihuawu@hotmail.com).
Publisher Copyright:
© 2002-2012 IEEE.
PY - 2021/9
Y1 - 2021/9
N2 - The resource allocation in vehicle-to-everything (V2X) communications face a great challenge for satisfying the heterogeneous quality of service (QoS) requirements of the ultra-reliable safety-related services and the minimum throughput required entertainment services, due to the channel uncertainties caused by high mobility. In this paper, we first consider an optimistic scenario where the distribution of uncertain channel state information (CSI) can be deterministic and accurately known at the eNB. Then, a low-complexity resource allocation approach is developed, in which the probabilistic QoS constraint of V2V is transformed into a computable optimization constraint. To deal with the scenario with unknown uncertain CSI distribution, we develop a distributionally robust resource allocation approach for converting the intractable chance constraint of V2V into a deterministic semidefinite constraint based only on the first- and second-order moments of uncertain CSI. For alleviating the conservatism of above approach, a support-based distributionally robust resource allocation approach is developed to tighten the semidefinite constraint by utilizing the support information of uncertain CSI. Finally, we conduct simulations to show that the effectiveness of the proposed approaches outperforms other state-of-art approaches.
AB - The resource allocation in vehicle-to-everything (V2X) communications face a great challenge for satisfying the heterogeneous quality of service (QoS) requirements of the ultra-reliable safety-related services and the minimum throughput required entertainment services, due to the channel uncertainties caused by high mobility. In this paper, we first consider an optimistic scenario where the distribution of uncertain channel state information (CSI) can be deterministic and accurately known at the eNB. Then, a low-complexity resource allocation approach is developed, in which the probabilistic QoS constraint of V2V is transformed into a computable optimization constraint. To deal with the scenario with unknown uncertain CSI distribution, we develop a distributionally robust resource allocation approach for converting the intractable chance constraint of V2V into a deterministic semidefinite constraint based only on the first- and second-order moments of uncertain CSI. For alleviating the conservatism of above approach, a support-based distributionally robust resource allocation approach is developed to tighten the semidefinite constraint by utilizing the support information of uncertain CSI. Finally, we conduct simulations to show that the effectiveness of the proposed approaches outperforms other state-of-art approaches.
UR - http://www.scopus.com/inward/record.url?scp=85104229136&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85104229136&partnerID=8YFLogxK
U2 - 10.1109/TWC.2021.3070894
DO - 10.1109/TWC.2021.3070894
M3 - Article
AN - SCOPUS:85104229136
SN - 1536-1276
VL - 20
SP - 5883
EP - 5897
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
IS - 9
M1 - 9400748
ER -