Coalitional game based resource allocation in D2D-enabled V2V communication

doi:10.23919/JSEE.2023.000040

Journal of Systems Engineering and Electronics ›› 2023, Vol. 34 ›› Issue (6): 1508-1519.doi: 10.23919/JSEE.2023.000040

• ELECTRONICS TECHNOLOGY • Previous Articles Next Articles

Coalitional game based resource allocation in D2D-enabled V2V communication

Piming MA¹(), Peng ZHAO¹(), Zhiquan BAI¹^,*(), Xu DONG¹(), Xinghai YANG²(), Kyungsup KWAK³()

¹ Shandong Provincial Key Lab of Wireless Communication Technologies, School of Information Science and Engineering, Shandong University, Qingdao 266237, China
² School of Information Science and Technology, Qingdao University of Science and Technology, Qingdao 266100, China
³ Graduate School of Information Technology and Telecommunications, Inha University, Incheon 22212, Korea

Received:2021-10-25 Online:2023-12-18 Published:2024-01-02
Contact: Zhiquan BAI E-mail:mapiming@sdu.edu.cn;929616871@qq.com;zqbai@sdu.edu.cn;dongxu@mail.sdu.edu.cn;yangxh@qust.edu.cn;kskwak@inha.ac.kr
About author:
MA Piming was born in 1970. She received her B.S., M.S., and Ph.D. degrees in communication and information systems from Shandong University, in 1992, 1997, and 2005, respectively. She is currently an associate professor with the School of Information Science and Engineering, Shandong University. Her current research interests include MIMO technology, wireless physical-layer security, and resource allocation and optimization in wireless communications. E-mail: mapiming@sdu.edu.cn

ZHAO Peng was born in 1994. He received his B.S. degree from University of Jinan, Ji’nan, China, in 2018, and M.S. degree in electronic and communication engineering from the School of Information Science and Engineering, Shandong University, Qingdao, China, in 2021. His research interests include vehicular communication, convex optimization, game theory, and low latency communication. E-mail: 929616871@qq.com

BAI Zhiquan was born in 1978. He received his M.E. degree in communication and information system from Shandong University, Ji’nan, China, in 2003, and Ph.D. degree (Hons.) from INHA University, Incheon, South Korea, in 2007, under the Grant of Korean Government IT Scholarship. He held a postdoctoral position with INHA University, and was a visiting professor with University of British Columbia, Canada. He is currently a professor with the School of Information Science and Engineering, Shandong University. His research interests include cooperative technology and spatial modulation, orthogonal time frequency space modulation, MIMO technology, resource allocation and optimization, and deep-learning-based 5G wireless communications. E-mail: zqbai@sdu.edu.cn

DONG Xu was born in 1997. He recived his B.S. degree from Shandong University, Qingdao, China, in 2020. He is currently pursuing his M.S. degree with the School of Information Science and Engineering, Shandong University, Qingdao, China. His research interests include D2D-enabled V2V communication convex optimization, and low latency communication. E-mail: dongxu@mail.sdu.edu.cn

YANG Xinghai was born in 1976. He recieved his B.S., M.S. and Ph.D. degrees from Shandong University, Ji’nan, China. He is currently an associate professor with the School of Information Science and Technology, Qingdao University of Science and Technology. He was a visiting professor with University of British Columbia, Canada, from 2015 to 2016 and Dresden University of Technology, Germany, in 2017. His research interests include optical wireless communication, MIMO technology, and deep-learning-based wireless technology. E-mail: yangxh@qust.edu.cn

KWAK Kyungsup was born in 1949. He received his M.S. and Ph.D. degrees from University of California, San Diego, in 1981 and 1988, respectively. From 1989 to 1990, he was with the IBM Network Analysis Center, Research Triangle Park, NC, USA. Since 1990, he has been with the School of Information and Communication Engineering, Inha University, South Korea, as a professor, where he was the dean of the Graduate School of Information Technology and Telecommunications, from 2001 to 2002. He has been the director of the UWB Wireless Communications Research Center, South Korea, since 2003. In 2006, he served as the president of the Korean Institute of Communication Sciences and the Korea Institute of Intelligent Transport Systems, in 2009. His research interests include wireless communications, ultrawideband systems, sensor networks, and wireless body area networks. E-mail: kskwak@inha.ac.kr
Supported by:
This work was supported by the National Natural Scientific Foundation of China(61771291;61571272) and the Major Science and Technological Innovation Project of Shandong Province (2020CXGC010109).

Abstract

Abstract:

The joint resource block (RB) allocation and power optimization problem is studied to maximize the sum-rate of the vehicle-to-vehicle (V2V) links in the device-to-device (D2D)-enabled V2V communication system, where one feasible cellular user (FCU) can share its RB with multiple V2V pairs. The problem is first formulated as a nonconvex mixed-integer nonlinear programming (MINLP) problem with constraint of the maximum interference power in the FCU links. Using the game theory, two coalition formation algorithms are proposed to accomplish V2V link partitioning and FCU selection, where the transferable utility functions are introduced to minimize the interference among the V2V links and the FCU links for the optimal RB allocation. The successive convex approximation (SCA) is used to transform the original problem into a convex one and the Lagrangian dual method is further applied to obtain the optimal transmit power of the V2V links. Finally, numerical results demonstrate the efficiency of the proposed resource allocation algorithm in terms of the system sum-rate.

Key words: coalitional game, vehicle-to-vehicle (V2V) communication, successive convex approximation (SCA), resource block (RB) allocation, power allocation

Piming MA, Peng ZHAO, Zhiquan BAI, Xu DONG, Xinghai YANG, Kyungsup KWAK. Coalitional game based resource allocation in D2D-enabled V2V communication[J]. Journal of Systems Engineering and Electronics, 2023, 34(6): 1508-1519.

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References 10

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Notation	Meaning of the representative
$ h_m^{\rm{C}} $	The channel gain from the FCU $ m $ to the eNB
$ h_{m,k}^{\rm{CV}} $	The channel gain from the FCU $ m $ to the V2V Rx $ k $
$ h_{k,m}^{\rm{VC}} $	The channel gain from the V2V Tx $ k $ to the FCU $ m $
$ h_{k,k}^{\rm{V}} $	The channel gain from the V2V Tx $ k $ to the V2V Rx $ k $
$ h_{k,k^\prime}^{\rm{V}} $	The channel gain from the V2V Tx $ k $ to the V2V Rx $ k^\prime $
$ K $	The number of V2V links
$ M $	The number of FCUs
$\varTheta$	V2V set of $\{1,2,\cdots,K\}$
$\varOmega$	FCU set of $\{1,2,\cdots,M\}$
$ P_m^{\rm{C}} $	The transmit power of FCU $m\in \varOmega$
$ I_{\max} $	The maximum interference power from the V2V links to the FCU uplinks
$ \gamma_0 $	The minimum SINR of the FCU uplink
${ {\boldsymbol{P} } }^{\rm{V} }$	The transmit power vector of V2V links, ${ {\boldsymbol{P} } }^{\rm{V} }=\left(P_1^{\rm{V} },P_2^{\rm{V} },\cdots,P_K^{\rm{V} }\right)$
$ P_{\rm{max}}^V $	The maximum transmit power of V2V Tx

Parameter	V2V link	Other links (except V2V links)
Pathloss model	LOS in WINNER + B1 [24]	$ 128.1 + 37.6\log_{10}d $, $ d $ in km
Shadowing distribution	Log-normal	Log-normal
Shadowing standard deviation($ \zeta $)/dB	$ 3 $	$ 8 $

Parameter	Value
Cellular coverage/m	$ 500 $
The eNB’s height/m	$ 25 $
Distance from the highway to eNB/m	$ 35 $
Number of lanes	$ 6 $ lanes in two driections
Lane width/m	$ 4 $
Vehicle drop model	Spatial Poisson process
Vehicle and CU antenna height/m	$ 1.5 $
Absolute vehicle speed/(km/h)	$60 - 120$
Average inter-vehicle distance/m	$ 2.5v $, $ v $ in m/s
Carrier frequency/GHz	$ 2 $
Bandwidth/MHz	$ 10 $
Vehicle antenna gain/dBi	$ 3 $
eNB antenna gain/dBi	$ 8 $
Vehicle receiver noise figure/dB	$ 9 $
eNB receiver noise figure/dB	$ 9 $
CU SINR threshold ($ \gamma_{0} $)/dB	$6 - 18$
Maximum V2V transmit power ($ P_{{\rm{max}}}^{{\rm{V}}} $)/mW	$ 200 $
Maximum CU transmit power ($ P_{{\rm{max}}}^{{\rm{C}}} $)/mW	$ 200 $
Noise power ($ \sigma^2 $)/mW	$ 10^{-10} $
The number of CUs	$ 60 $

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Coalitional game based resource allocation in D2D-enabled V2V communication

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