Abstract
The Deferred Acceptance (DA) algorithm has often been used to study spectrum sharing and to solve the assignment problem of Device-to-Device (D2D) links co-existing with traditional cellular users. We present a new reward-based DA algorithm denoted as priced-DA or (p-DA) to improve reuse gains in scenarios where there are variations in the number of cellular users and D2D links and when there are variations in the length of the preference lists. Interference coordination is implemented by jointly managing the power allocation and quality of service (QoS) admission control based on the inter-distances between devices. Simulation case studies demonstrate the advantages of the presented p-DA technique in comparison to other tested centralised approaches.
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
Tehrani, M.N., Uysal, M., Yanikomeroglu, H.: Device-to-device communication in 5G cellular networks: challenges, solutions, and future directions. IEEE Commun. Mag. 52(5), 86–92 (2014)
Chen, H., et al.: Ultra-reliable low latency cellular networks: use cases, challenges and approaches. IEEE Commun. Mag. 56(12), 119–125 (2018)
Safdar, G.A., Ur-Rehman, M., Muhammad, M., Imran, M.A., Tafazolli, R.: Interference mitigation in D2D communication underlaying LTE-A network. IEEE Access 4, 7967–7987 (2016)
Li, Z., Guo, C.: Multi-agent deep reinforcement learning based spectrum allocation for D2D underlay communications. IEEE Trans. Vehicular Technol. (2020)
Gu, Y., Zhang, Y., Pan, M., Han, Z.: Matching and cheating in device to device communications underlying cellular networks. IEEE J. Sel. Areas Commun. 33(10), 2156–2166 (2015)
Zhang, B., Mao, X., Yu, J.L., Han, Z.: Resource allocation for 5G heterogeneous cloud radio access networks with D2D communication: a matching and coalition approach. IEEE Trans. Vehicular Technol. 67(7), 5883–5894 (2018)
Vassaki, S., Poulakis, M.I., Panagopoulos, A.D.: Spectrum leasing in cognitive radio networks: a matching theory approach. In: Proceedings of 2015 IEEE 81st Vehicular Technology Conference (VTC Spring), pp. 1–5, May 2015
Yuan, Y., Yang, T., Xu, Y., Hu, B.: Cooperative spectrum sharing between D2D users and edge-users: a matching theory perspective. In: Proceedings of IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), pp. 1–6, 4 September 2016
Sanusi, I., Nasr, K.M., Moessner, K.: Resource allocation for a reliable D2D enabled cellular network in factories of the future. In: Proceedings IEEE European Conference on Networks and Communications (EuCNC), June 2020
Rahim, M., et al.: Efficient Channel Allocation using Matching Theory for QoS Provisioning in Cognitive Radio Networks. Sensors 20(7), 1872 (2020)
Wang, B., Sun, Y., Nguyen, H.M., Duong, T.Q.: A novel socially stable matching model for secure relay selection in D2D communications. IEEE Wirel. Commun. Lett. 9(2), 162–165 (2020)
Liang, L., Li, G.Y., Xu, W.: Resource allocation for D2D-enabled vehicular communications. IEEE Trans. Commun. 65(7), 3186–3197 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Sanusi, I.O., Nasr, K.M., Moessner, K. (2021). A Priced-Deferred Acceptance (p-DA) Technique for D2D Communication in Factories of the Future. In: Caso, G., De Nardis, L., Gavrilovska, L. (eds) Cognitive Radio-Oriented Wireless Networks. CrownCom 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 374. Springer, Cham. https://doi.org/10.1007/978-3-030-73423-7_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-73423-7_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-73422-0
Online ISBN: 978-3-030-73423-7
eBook Packages: Computer ScienceComputer Science (R0)