Joint power and spectrum optimization algorithm for ICV in diverse service scenarios

Zhang Haibo; Hu Yuting; Hu Yanli; Xu Yongjun; Li Yongfu

doi:10.11959/j.issn.1000-436x.2026072

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Joint power and spectrum optimization algorithm for ICV in diverse service scenarios

Papers | 更新时间：2026-05-07

- Joint power and spectrum optimization algorithm for ICV in diverse service scenarios
- Journal on Communications Vol. 47, Issue 4, Pages: 181-191(2026)
- 作者机构：
  
  1.重庆邮电大学通信与信息工程学院，重庆 400065
  2.重庆市沙坪坝区歌乐山旅游景区事务中心，重庆 400036
  3.重庆邮电大学自动化学院，重庆 400065
- 作者简介：
- 基金信息：
  
  The National Key Research and Development Program of China(SQ2023YFB250002402);The National Natural Science Foundation of China(62371082;U23A20279;62271094)
- DOI：10.11959/j.issn.1000-436x.2026072
  CLC： TN929.5
- Received：05 January 2026，
  
  Revised：2026-03-10，
  
  Accepted：11 March 2026，
  
  Published：20 April 2026
- 稿件说明：
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张海波,胡雨婷,胡艳丽等.智能网联汽车多样化服务场景下功率与频谱联合优化算法[J].通信学报,2026,47(04):181-191.

Zhang Haibo,Hu Yuting,Hu Yanli,et al.Joint power and spectrum optimization algorithm for ICV in diverse service scenarios[J].Journal on Communications,2026,47(04):181-191.
张海波,胡雨婷,胡艳丽等.智能网联汽车多样化服务场景下功率与频谱联合优化算法[J].通信学报,2026,47(04):181-191. DOI： 10.11959/j.issn.1000-436x.2026072.

Zhang Haibo,Hu Yuting,Hu Yanli,et al.Joint power and spectrum optimization algorithm for ICV in diverse service scenarios[J].Journal on Communications,2026,47(04):181-191. DOI： 10.11959/j.issn.1000-436x.2026072.

摘要

针对智能网联汽车协同通信场景中日益增长的多样化服务需求，提出了一种基于链路自适应的功率控制与频谱共享联合资源分配方案，从而实现异构协同通信场景下的差异化资源分配。首先，构建了一个包含车到基础设施（V2I）和车到车（V2V）链路的异构网络模型，并提出了在发射功率和频谱资源受限的条件下，最大化系统加权和速率的优化问题。在此基础上，提出了一种基于几何规划理论的最优功率控制策略，并推导出了在不同加权因子下的闭式功率分配解，在有效降低计算复杂度的同时，保证了车辆用户的服务质量。最后，设计了功率控制与频谱共享的联合优化算法，进一步提升了系统整体性能。仿真结果表明，与基准算法相比，所提算法在系统加权和速率方面提升了33.7%。

Abstract

To address the problem of the increasingly diverse service demands in the cooperative communication scenarios of intelligent connected vehicles

a joint resource allocation scheme based on link adaptation was proposed for power control and spectrum sharing

thereby achieving differentiated resource allocation in heterogeneous cooperative communication scenarios. Firstly

a heterogeneous network model including vehicle to infrastructure (V2I) and vehicle to vehicle (V2V) links was constructed

and an optimization problem was proposed to maximize the system’s weighted sum rate under the constraints of limited transmit power and spectrum resources. Secondly

an optimal power control strategy based on geometric programming theory was proposed

and a closed form power solution was derived under different weighting factors. While effectively reducing computational complexity

the service quality of vehicle users was ensured. Finally

a joint optimization algorithm for power control and spectrum sharing was proposed

further improving the overall system performance. Compared to the benchmark algorithm

the weighted sum rate is improved by approximately 33.7%.

关键词

Keywords

references

Siegel J E , Erb D C , Sarma S E . A survey of the connected vehicle landscape: architectures, enabling technologies, applications, and development areas [J ] . IEEE Transactions on Intelligent Transportation Systems , 2018 , 19 ( 8 ): 2391 - 2406 .

Alharthi A , Ni Q , Jiang R . Internet of vehicles [M ] . Boca Raton : CRC Press , 2022 .

Zhou H B , Xu W C , Chen J C , et al . Evolutionary V2X technologies toward the Internet of vehicles: challenges and opportunities [J ] . Proceedings of the IEEE , 2020 , 108 ( 2 ): 308 - 323 .

Sehla K , Nguyen T M T , Pujolle G , et al . Resource allocation modes in C-V2X: from LTE-V2X to 5G-V2X [J ] . IEEE Internet of Things Journal , 2022 , 9 ( 11 ): 8291 - 8314 .

Abbas F , Fan P Z , Khan Z . A novel low-latency V2V resource allocation scheme based on cellular V2X communications [J ] . IEEE Transactions on Intelligent Transportation Systems , 2019 , 20 ( 6 ): 2185 - 2197 .

Aslani R , Saberinia E , Rasti M . Resource allocation for cellular V2X networks mode-3 with underlay approach in LTE-V standard [J ] . IEEE Transactions on Vehicular Technology , 2020 , 69 ( 8 ): 8601 - 8612 . .

Thakur K P , Palit B . A QoS-aware uplink spectrum and power allocation with link adaptation for vehicular communications in 5G networks [J ] . IEEE Transactions on Network and Service Management , 2025 , 22 ( 1 ): 592 - 604 .

陈发堂 , 张若凡 . 可重构智能反射面辅助的车联网资源分配算法研究 [J ] . 通信学报 , 2023 , 44 ( 9 ): 70 - 78 .

Chen F T , Zhang R F . Research on IoV resource allocation algorithm assisted by reconfigurable intelligent surface [J ] . Journal on Communications , 2023 , 44 ( 9 ): 70 - 78 .

Ibrahim A M A , Chen Z G , Wang Y J , et al . Optimizing V2X communication: spectrum resource allocation and power control strategies for next-generation wireless technologies [J ] . Applied Sciences , 2024 , 14 ( 2 ): 531 .

Ji M X , Wu Q , Fan P Y , et al . Graph neural networks and deep reinforcement learning-based resource allocation for V2X communications [J ] . IEEE Internet of Things Journal , 2025 , 12 ( 4 ): 3613 - 3628 .

Bute M S , Fan P Z , Luo Q Y , et al . QoS-aware content dissemination based on integrated social and physical attributes among cellular and V2V users [J ] . IEEE Transactions on Vehicular Technology , 2023 , 72 ( 9 ): 12181 - 12194 .

Guo S Q , Hu B J , Wen Q J . Joint resource allocation and power control for full-duplex V2I communication in high-density vehicular network [J ] . IEEE Transactions on Wireless Communications , 2022 , 21 ( 11 ): 9497 - 9508 .

Zhou Q Z , Guo C , Wang C , et al . Radio resource management for C-V2X using graph matching and actor-critic learning [J ] . IEEE Wireless Communications Letters , 2022 , 11 ( 12 ): 2645 - 2649 .

Bahonar M H , Omidi M J , Yanikomeroglu H . Low-complexity resource allocation for dense cellular vehicle-to-everything (C-V2X) communications [J ] . IEEE Open Journal of the Communications Society , 2021 , 2 : 2695 - 2713 .

Ihsan A , Chen W , Zhang S Q , et al . Energy-efficient NOMA multicasting system for beyond 5G cellular V2X communications with imperfect CSI [J ] . IEEE Transactions on Intelligent Transportation Systems , 2022 , 23 ( 8 ): 10721 - 10735 .

Xue T , Ding H , Zhang H X , et al . Two-timescale vehicle association and resource management for C-V2X networks [J ] . IEEE Wireless Communications Letters , 2023 , 12 ( 7 ): 1259 - 1263 .

Saleh Bute M , Fan P Z , Liu G , et al . Trust-aware V2V relay-assisted content distribution in cellular V2X networks [J ] . IEEE Internet of Things Journal , 2024 , 11 ( 8 ): 13452 - 13466 .

Zhang M L , Dou Y , Chong P H J , et al . Fuzzy logic-based resource allocation algorithm for V2X communications in 5G cellular networks [J ] . IEEE Journal on Selected Areas in Communications , 2021 , 39 ( 8 ): 2501 - 2513 .

Shan L Q , Wang M M , Zhang F H , et al . Resource allocation for cellular device-to-device-aided vehicle-to-everything networks with partial channel state information [J ] . Transactions on Emerging Telecommunications Technologies , 2022 , 33 ( 7 ): e4501 .

Yu C H , Doppler K , Ribeiro C B , et al . Resource sharing optimization for device-to-device communication underlaying cellular networks [J ] . IEEE Transactions on Wireless Communications , 2011 , 10 ( 8 ): 2752 - 2763 .

3GPP. 6 Service requirements for enhanced V2X scenarios:3GPP TS 22.18 [S ] . 2019 .

Feng D Q , Lu L , Yi Y W , et al . Device-to-device communications underlaying cellular networks [J ] . IEEE Transactions on Communications , 2013 , 61 ( 8 ): 3541 - 3551 .

West D B . Introduction to graph theory [M ] . Bengaluru : India Pearson Education , 2002 .

Li X S , Ma L , Shankaran R , et al . Joint power control and resource allocation mode selection for safety-related V2X communication [J ] . IEEE Transactions on Vehicular Technology , 2019 , 68 ( 8 ): 7970 - 7986 .

3GPP. 3GPP release 14 technical specification group radio access network [R ] . 2016 .

Wang P , Wu W H , Liu J Y , et al . Joint spectrum and power allocation for V2X communications with imperfect CSI [J ] . IEEE Transactions on Vehicular Technology , 2023 , 72 ( 12 ): 16338 - 16353 .

Xue T , Zhang H X , Ding H , et al . Joint vehicle pairing, spectrum assignment, and power control for sum-rate maximization in NOMA-based V2X underlaid cellular networks [J ] . IEEE Internet of Things Journal , 2025 , 12 ( 12 ): 22337 - 22349 .

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