Joint mixed-timescale optimization of content caching and delivery policy in NOMA-based vehicular networks
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date
2023-12
Department
Department of Information and Communications Engineering
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en
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Computer Networks, Volume 237
Abstract
Recently, the development of Internet of Vehicles (IoV) and the increasing popularity of video applications have led to the fast-growing in-car video demand causing numerous challenges in wireless networks. Pre-caching and non-orthogonal multiple access (NOMA) have been regarded as two effective techniques to alleviate the mentioned challenge. In this paper, we propose a cache-aided cooperative transmission to maximize the quality of service (QoS) in the NOMA-based vehicular network. A QoS-oriented joint optimization problem is formulated, which incorporates power allocation, content caching, and delivery strategy. Considering, on the one hand, the slow update rate of cache content and, on the other hand, frequent handovers of vehicles between different transmitters, a mixed-timescale optimization is proposed where the serving cache is updated in a long-term phase, while content delivery and power allocation are optimized in a short-term phase. In the proposed approach, content caching is determined based on future user requests, vehicle tracking, and other delivery information. To make this possible, we leverage a substantial number of stochastic samples to approximate content caching in the long-term caching phase. Due to the NOMA-based transmission and integral variables, the setting leads to a Mixed Integer Non-Linear Programming (MINLP) problem, which is NP-hard. To solve this problem, an iterative method based on sample average approximation (SAA) and Successive Convex Approximation (SCA) is applied. Simulations demonstrate that the proposed algorithm can achieve better QoS than other recently proposed transmission schemes.Description
Funding Information: Jingyao Liu received the B.S. degree in 2017 from Harbin Engineering University, Harbin, China, where she is currently pursuing a Ph.D. degree. She is also a visiting Ph.D. student under the support of the China Scholarship Council (CSC) at the School of Electrical Engineering, Aalto University, Espoo, Finland since 1 September 2022. Her current research interests include edge computing, content caching, vehicle video streaming, and network resource allocation. Funding Information: This work is supported by the National Natural Science Foundation of China (No. 61872104 ). This work is also partially supported by the project “ PCL Future Greater-Bay Area Network Facilities for Large-scale Experiments and Applications ( LZC0019 )”. Publisher Copyright: © 2023 Elsevier B.V.
Keywords
Content caching, Delivery policy, Dense vehicular networks, Non-orthogonal multiple access (NOMA), Power allocation
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Citation
Liu, J, Feng, G, Zhang, Z, Zheng, L, Wang, H & Hämäläinen, J 2023, ' Joint mixed-timescale optimization of content caching and delivery policy in NOMA-based vehicular networks ', Computer Networks, vol. 237, 110075 . https://doi.org/10.1016/j.comnet.2023.110075