Abstract
The D2D-enabled heterogeneous network services have strict requirements on communication delay and quality. D2D users can share spectrum resources with cellular users, which can effectively improve the spectrum efficiency. But it can cause serious co-channel interference in dense user scenarios. In order to satisfy the highly dynamic patterns of the data traffic and wireless communication environment, a joint optimization algorithm of D2D-enabled heterogeneous network resources is proposed while meeting the delay and quality requirements. Specifically, a heterogeneous network is established where users are clustered. We maximize system energy efficiency under the premise of meeting the user delay and reliability requirements. In addition, we use the Lyapunov algorithm to optimize the dynamic allocation of wireless resources. The results of the experiment show that the proposed algorithm can improve the spectrum efficiency, reduce the D2D power consumption and reduce the co-channel interference, while ensuring the reliability and time delay requirements of both D2D users and cellular users.
Supported by Major Technological Projects of Jiangsu Province Transportation Department (2019Z07).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Ashraf, M.I., Liu, C.-F., Bennis, M., Saad, W., Hong, C.S.: Dynamic resource allocation for optimized latency and reliability in vehicular networks. IEEE Access 6, 63843–63858 (2018)
Han, Y., Tao, X., Zhang, X., Jia, S.: Delay-aware resource management for multi-service coexisting LTE-D2D networks with wireless network virtualization. IEEE Trans. Veh. Technol. 69(7), 7339–7353 (2020)
Qiao, G., Leng, S., Zhang, Y.: Online learning and optimization for computation offloading in D2D edge computing and networks. Mob. Netw. Appl. 1–12 (2019)
Little, J.D.: A proof for the queuing formula: L= λ W. Oper. Res. 9(3), 383–387 (1961)
Ashraf, M.I., Liu, C., Bennis, M., et al.: Dynamic resource allocation for optimized latency and reliability in vehicular networks. IEEE Access 6, 63843–63858 (2018)
Bao, H., Liu, Y.: A two-sided matching approach for distributed edge computation offloading. In: 2019 IEEE/CIC International Conference on Communications in China (ICCC), Changchun, China, pp. 535–540 (2019)
Wang, L., Wu, H., Han, Z., et al.: Multi-hop cooperative caching in social IoT using matching theory. IEEE Trans. Wirel. Commun. 17(4), 2127–2145 (2018)
Ehsanpour, M., Bayat, S., Mohammad, A., et al.: On efficient and social-aware object allocation in named data networks using matching theory. In: 2018 IEEE Symposium on Computers and Communications (ISCC), pp. 298–303 (2018)
Hmila, M., Manuel, F., Miguel, R.: Matching-theory-based resource allocation for underlay device to multi-device communications. In: 2018 14th International Conference on Wireless and Mobile Computing Networking and Communications (WiMob), pp. 28–35 (2018)
Li, J., Liu, M., Lu, J., et al.: On social-aware content caching for D2D-enabled cellular networks with matching theory. Internet Things J. IEEE 6(1), 297–310 (2019)
Neely, M.J.: Stochastic Network Optimization with Application to Communication and Queueing Systems. Morgan & Claypool, San Rafael (2010)
Grant, M., Boyd, S.: CVX: Matlab software for disciplined convex programming. Wordpress and MathJax (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Yang, D., Ni, B., Wang, H., Wei, B. (2022). Joint Optimization of D2D-Enabled Heterogeneous Network Based on Delay and Reliability Constraints. In: Gao, H., Wun, J., Yin, J., Shen, F., Shen, Y., Yu, J. (eds) Communications and Networking. ChinaCom 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 433. Springer, Cham. https://doi.org/10.1007/978-3-030-99200-2_14
Download citation
DOI: https://doi.org/10.1007/978-3-030-99200-2_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-99199-9
Online ISBN: 978-3-030-99200-2
eBook Packages: Computer ScienceComputer Science (R0)