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[ "贺智敏(1999- ),男,北京邮电大学网络与交换技术国家重点实验室硕士生,主要研究方向为车联网通信感知一体化和资源管理" ]
[ "林育哲(1998- ),男,北京邮电大学网络与交换技术国家重点实验室硕士生,主要研究方向为通信感知一体化、车联网系统级仿真" ]
[ "程宇杰(2000- ),男,北京邮电大学网络与交换技术国家重点实验室硕士生,主要研究方向为车联网络车路协同和数据融合" ]
[ "闫实(1988- ),男,博士,北京邮电大学网络与交换技术国家重点实验室副教授,主要研究方向为通信感知计算融合关键技术" ]
网络出版日期:2022-09,
纸质出版日期:2022-09-20
移动端阅览
贺智敏, 林育哲, 程宇杰, 等. 基于无线感知辅助的车联网下行无线资源分配方法[J]. 电信科学, 2022,38(9):60-70.
Zhimin HE, Yuzhe LIN, Yujie CHENG, et al. Downlink wireless resource allocation method of V2X based on wireless sensing assistance[J]. Telecommunications science, 2022, 38(9): 60-70.
贺智敏, 林育哲, 程宇杰, 等. 基于无线感知辅助的车联网下行无线资源分配方法[J]. 电信科学, 2022,38(9):60-70. DOI: 10.11959/j.issn.1000-0801.2022253.
Zhimin HE, Yuzhe LIN, Yujie CHENG, et al. Downlink wireless resource allocation method of V2X based on wireless sensing assistance[J]. Telecommunications science, 2022, 38(9): 60-70. DOI: 10.11959/j.issn.1000-0801.2022253.
在车联网(vehicle-to-everything,V2X)中,感知与安全类数据的高速下发与共享对道路交通安全至关重要。然而,车辆高速移动所引起的通信链路不稳定,会导致现有的基于车辆位置信息上报的通信资源分配方法不再高效。为此,提出了一种基于通信节点无线感知辅助的车联网下行无线资源分配方法。首先,构建了通信与感知资源正交下的通信模式选择与无线资源分配联合优化问题;之后,为解决这一问题提出了基于Delaunay三角划分的分簇通信模式选择与基于改进图着色的资源分配策略,以实现下行吞吐量的提升;最后,仿真分析了无线感知估计误差、车辆数量对算法性能的影响。仿真结果表明,与传统方法相比,所提算法在相同感知带宽资源占比下可获得更好的下行通信性能增益,并能够承受更大的感知误差对性能的影响,同时,所提算法的计算复杂度较低,可节省网络算力资源。
In vehicle-to-everything
the high-speed distribution and sharing of perception and safety data is crucial to road safety.However
the instability of communication links caused by high-speed vehicle movement will make the existing communication resource allocation methods based on vehicle location information reporting no longer efficient.Therefore
a downlink wireless resource allocation method based on wireless sensing assistance of communication nodes was proposed.Firstly
a joint optimization problem of communication mode selection and wireless resource allocation under the orthogonality of communication and sensing resources was constructed.Then
a communication mode selection based on clustering by Delaunay triangulation and a resource allocation strategy based on improved graph coloring to improve the downlink throughput was proposed to solve the problem of construction.Finally
the impact of wireless sensing estimation error and the number of vehicles on the performance of the algorithm was simulated and analyzed.Simulation results show that compared with traditional methods
the proposed algorithm can obtain better downlink communication performance gain under the same proportion of sensing bandwidth resources
and can withstand the impact of larger sensing errors on performance.At the same time
the computational complexity of the proposed algorithm is lower and the network computing resources can be saved.
KIM S W , LIU W , ANG M H , et al . The impact of cooperative perception on decision making and planning of autonomous vehicles [J ] . IEEE Intelligent Transportation Systems Magazine , 2015 , 7 ( 3 ): 39 - 50 .
3GPP . Study on enhancement of 3GPP support for 5G V2X services:TR 22.886 V16.2.0 [S ] . 2018 .
全球移动通信系统协会 , 中国信息通信研究院 . 中国 5G 垂直行业应用案例2021 [EB ] . 2021 .
GSMA , CAICT . Application case of 5G vertical industry in China 2021 [EB ] . 2021 .
ZHIOUA G E M , TABBANE N , LABIOD H , et al . A fuzzy multi-metric QoS-balancing gateway selection algorithm in a clustered VANET to LTE advanced hybrid cellular network [J ] . IEEE Transactions on Vehicular Technology , 2015 , 64 ( 2 ): 804 - 817 .
GARBISO J , DIACONESCU A , COUPECHOUX M , et al . Fair self-adaptive clustering for hybrid cellular-vehicular networks [J ] . IEEE Transactions on Intelligent Transportation Systems , 2021 , 22 ( 2 ): 1225 - 1236 .
KHAN H , SAMARAKOON S , BENNIS M . Enhancing video streaming in vehicular networks via resource slicing [J ] . IEEE Transactions on Vehicular Technology , 2020 , 69 ( 4 ): 3513 - 3522 .
WANG T Y , CAO X , WANG S W . Self-adaptive clustering and load-bandwidth management for uplink enhancement in heterogeneous vehicular networks [J ] . IEEE Internet of Things Journal , 2019 , 6 ( 3 ): 5607 - 5617 .
何朵奇 , 王斌 , 季文君 , 等 . LTE 网络下基于图着色理论的D2D分簇资源分配方案 [J ] . 南京邮电大学学报(自然科学版) , 2015 , 35 ( 6 ): 44 - 50 .
HE D Q , WANG B , JI W J , et al . D2D clustering resource allocation scheme based on graph-coloring underlaying LTE networks [J ] . Journal of Nanjing University of Posts and Telecommunications (Natural Science Edition) , 2015 , 35 ( 6 ): 44 - 50 .
LIANG L , XIE S J , LI G Y , et al . Graph-based resource sharing in vehicular communication [J ] . IEEE Transactions on Wireless Communications , 2018 , 17 ( 7 ): 4579 - 4592 .
LIANG L , YE H , LI G Y . Spectrum sharing in vehicular networks based on multi-agent reinforcement learning [J ] . IEEE Journal on Selected Areas in Communications , 2019 , 37 ( 10 ): 2282 - 2292 .
ZHANG X R , PENG M G , YAN S , et al . Deep-reinforcementlearning-based mode selection and resource allocation for cellular V2X communications [J ] . IEEE Internet of Things Journal , 2020 , 7 ( 7 ): 6380 - 6391 .
ZHANG A , RAHMAN M L , HUANG X J , et al . Perceptive mobile networks:cellular networks with radio vision via joint communication and radar sensing [J ] . IEEE Vehicular Technology Magazine , 2021 , 16 ( 2 ): 20 - 30 .
ZHANG Q X , WANG X N , LI Z H , et al . Design and performance evaluation of joint sensing and communication integrated system for 5GmmWave enabled CAVs [J ] . IEEE Journal of Selected Topics in Signal Processing , 2021 , 15 ( 6 ): 1500 - 1514 .
LUONG N C , LU X , HOANG D T , et al . Radio resource management in joint radar and communication:a comprehensive survey [J ] . IEEE Communications Surveys & Tutorials , 2021 , 23 ( 2 ): 780 - 814 .
GUO J , YANG C Y . Impact of prediction errors on high throughput predictive resource allocation [J ] . IEEE Transactions on Vehicular Technology , 2020 , 69 ( 9 ): 9984 - 9999 .
MASMOUDI A , MNIF K , ZARAI F . A survey on radio resource allocation for V2X communication [J ] . Wireless Communications and Mobile Computing,2019 , 2019 :2430656.
3GPP . Study on LTE support for vehicle to everything (V2X) services:TR 22.885 V14.0.0 [S ] . 2016 .
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