Abstract
As an important application scenario of edge computing, the Internet of Vehicles (IoV) is a special wireless network which needs a serious requirement on communication speed and latency. Nowadays, the 5G wireless networks have been put into commercial use, which makes IoV’s higher speed and lower latency requirements possible. However, comparing with 4G base station, the cost of 5G base station is very high, while its cover range is small. These weaknesses make 5G wireless network difficult to be used directly on IoV. Fortunately, Coherent Beamforming (CB) technology makes the long distance transmission possible in 5G wireless network. While as a new technology in communication, few works has been done on considering to use it on IoV. In this paper, we consider to use CB on IoV scenario. We aim to give an optimal scheme for deploying the roadside CB-nodes so that we can transmit data to the edge server with a low cost. We first give the mathematical model and clarify that it is an NP-hard model. Then we design a heuristic algorithm for solving the problem. We call our algorithm as the Iterative Coherent Beamforming Node Design (ICBND) algorithm. Simulation results show that the ICBND algorithm can greatly reduce the cost of communication network infrastructure.
This article was supported by the National Natural Science Foundation of China (Grant No. 61806067) and Key Research and Development Project in Anhui Province (Grant No. 201904a06020024).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Cai, Z., Zheng, X., Yu, J.: A differential-private framework for urban traffic flows estimation via taxi companies. IEEE Trans. Ind. Inform. 15(12), 6492–6499 (2019)
Xiong, Z., Li, W., Han, Q., Cai, Z.: Privacy-preserving auto-driving: a GAN-based approach to protect vehicular camera data. In: 2019 IEEE International Conference on Data Mining (ICDM), pp. 668–677 (2019)
Guan, X., Huang, Y., Cai, Z., Ohtsuki, T.: Intersection-based forwarding protocol for vehicular ad hoc networks. Telecommun. Syst. 62(1), 67–76 (2015). https://doi.org/10.1007/s11235-015-9983-y
Hou, X., et al.: Reliable computation offloading for edge computing-enabled software-defined IoV. IEEE Internet Things J. 7, 7097–7111 (2020)
Xie, R., Tang, Q., Wang, Q., Liu, X., Yu, F.R., Huang, T.: Collaborative vehicular edge computing networks: architecture design and research challenges. IEEE Access 7, 178942–178952 (2019)
Wang, J., Cai, Z., Yu, J.: Achieving personalized \(k\)-anonymity-based content privacy for autonomous vehicles in CPS. IEEE Trans. Ind. Inform. 16(6), 4242–4251 (2020)
Na, W., Jang, S., Lee, Y., Park, L., Dao, N., Cho, S.: Frequency resource allocation and interference management in mobile edge computing for an internet of things system. IEEE Internet Things J. 6(3), 4910–4920 (2019)
Xu, X., Zhang, X., Liu, X., Jiang, J., Qi, L., Bhuiyan, M.Z.A.: Adaptive computation offloading with edge for 5G-envisioned internet of connected vehicles. IEEE Trans. Intell. Transp. Syst. (2020). https://doi.org/10.1109/TITS.2020.2982186
LiWang, M., Dai, S., Gao, Z., Du, X., Guizani, M., Dai, H.: A computation offloading incentive mechanism with delay and cost constraints under 5G satellite-ground IoV architecture. IEEE Wirel. Commun. 26(4), 124–132 (2019)
Zhang, L., Cao, W.J., Zhang, X.X., Xu, H.T.: Mac(2): enabling multicasting and congestion control with multichannel transmission for intelligent vehicle terminal in internet of vehicles. Int. J. Distrib. Sens. Netw. 14(8) (2018). https://doi.org/10.1177/1550147718793586
Shah, S.A.A., Ahmed, E., Imran, M., Zeadally, S.: 5G for vehicular communications. IEEE Commun. Mag. 56(1), 111–117 (2018)
Gupta, A., Jha, R.K.: A survey of 5G network: architecture and emerging technologies. IEEE Access 3, 1206–1232 (2015)
Li, S.C., Xu, L.D., Zhao, S.: 5G internet of things: a survey. J. Ind. Inf. Integr. 10, 1–9 (2018)
Cheng, X., Chen, C., Zhang, W., Yang, Y.: 5G-enabled cooperative intelligent vehicular (5GenCIV) framework: when Benz meets Marconi. IEEE Intell. Syst. 32(3), 53–59 (2017)
Shi, Y., Sagduyu, Y.E.: Coherent communications in self-organizing networks with distributed beamforming. IEEE Trans. Veh. Technol. 69(1), 760–770 (2020)
Nanzer, J.A., Schmid, R.L., Comberiate, T.M., Hodkin, J.E.: Open-loop coherent distributed arrays. IEEE Trans. Microw. Theory Tech. 65(5), 1662–1672 (2017)
Bai, C., Zhang, X., Qiao, X., Sang, Y., Wan, M.: Ultrasound transcranial imaging based on fast coherent-time-delay and correlative pixel-based beamforming. In: IEEE International Ultrasonics Symposium (2018)
Deng, H., Geng, Z., Himed, B.: MIMO radar waveform design for transmit beamforming and orthogonality. IEEE Trans. Aerosp. Electron. Syst. 52(3), 1421–1433 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Xu, J., Wu, L., Shi, L., Shi, Y., Zhou, W. (2020). Research on 5G Internet of Vehicles Facilities Based on Coherent Beamforming. In: Yu, D., Dressler, F., Yu, J. (eds) Wireless Algorithms, Systems, and Applications. WASA 2020. Lecture Notes in Computer Science(), vol 12385. Springer, Cham. https://doi.org/10.1007/978-3-030-59019-2_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-59019-2_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-59018-5
Online ISBN: 978-3-030-59019-2
eBook Packages: Computer ScienceComputer Science (R0)