Abstract
In Vehicular Sensor Networks (VSNs), the configuration of connected vehicles is in such a manner that enhances the data traffic. Due to this challenge, researchers have explored device to device (D2D) communication which provides the desired connectivity with mobility between the connected vehicles. It also reduces the energy consumption while increasing the system capacity. D2D communication is strongly affected by interference because it works with large number of vehicles in limited area. Various schemes have been attempted to manage interference while maintaining energy efficiency such as power control, mode selection etc. This paper presents a signal-to-interference-noise-ratio (SINR) based energy optimization technique for 5th generation VSNs. The major factors taken in account of are transmit power, battery lifetime, system load and SINR. An energy efficient algorithm is proposed with mathematical model to optimize the battery lifetime with respect to power control. Simulation results have been used to present the comparison of existing and proposed technique.
Similar content being viewed by others
References
Bello, O., & Zeadally, S. (2014). Intelligent device-to-device communication in the internet of things. IEEE Systems Journal, 10(3), 1172–1182
Iqbal, J., Iqbal, M. A., Ahmad, A., Khan, M., Qamar, A., & Han, K. (2019). Comparison of spectral efficiency techniques in device-to-device communication for 5G. IEEE Access, 7, 57440–57449
Chiang, M., Hande, P., Lan, T., & Tan, C. W. (2007). Power control in wireless cellular networks. Foundations and Trends in Networking, 2(4), 381–533
Memmi, A., Rezki, Z., & Alouini, M. S. (2016). Power control for D2D underlay cellular networks with channel uncertainty. IEEE Transactions on Wireless Communications, 16(2), 1330–1343
Sun, P., Shin, K. G., Zhang, H., & He, L. (2016). Transmit power control for D2D-underlaid cellular networks based on statistical features. IEEE Transactions on Vehicular Technology, 66(5), 4110–4119
Su, Z., Hui, Y., & Guo, S. (2016). D2D-based content delivery with parked vehicles in vehicular social networks. IEEE Wireless Communications, 23, 90–95
Akinlade, O.M. Adaptive transmission power with vehicle density for congestion control. Master’s Thesis, Windsor University, Windsor, ON, Canada, July 2018.
Wu, X., Sun, S., Li, Y., Tan, Z., Huang, W., & Yao, X. (2018). A Power control algorithm based on outage probability awareness in vehicular ad hoc networks. Adv. Multimed., 2018, 1–8
Hong, H., Kim, Y., Kim, R., & Ahn, W. (2019). An effective wide-bandwidth channel access in next-generation WLAN-based V2X communications. Applied Sciences, 10, 222
Liang, L., Ye, H., & Li, G. Y. (2019). Spectrum sharing in vehicular networks based on multi-agent reinforcement learning. IEEE Journal on Selected Areas in Communications, 37, 2282–2292
Zhang, X., Peng, M., Sun, Y. (2019). Deep reinforcement learning based mode selection and resource allocation for cellular V2X communications. IEEE Internet Things. pp 1–12.
Huang, J., Jinyun, Z., & Cong-Cong, X. (2018). Energy-efficient mode selection for D2D communications in cellular networks. IEEE Transactions on Cognitive Communication and Networking, 4, 869–882
Akkarajitsakul, K.; Phunchongharn, P., Hossain, E.; Bhargava, V.K. (2012). Mode selection for energy-efficient D2D communications in LTE-advanced networks: A coalitional game approach. In: Proceedings of the IEEE international conference on communication systems, Singapore, 21–23 November 2012; pp. 488–492.
Zuo, J.; Chao, Z.; Nan, B. (2017). Mode selection for energy efficient D2D communications underlaying C-RAN. In: Proceedings of the International Conference on Information Technology, Singapore, 27–29 December 2017; pp. 287–291.
Huang, J., Liao, Y., Xing, C. (2018). Efficient power control for D2D with SWIPT. In: Proceedings of the conference on research in adaptive and convergent systems, Honolulu, HI, USA, 9–12 October 2018; pp. 106–111.
Peng, S., Kang, G., Hailin, Z., & Liang, H. (2017). Transmit power control for D2D-underlaid cellular networks based on statistical features. IEEE Transactions on Vehicular Technology, 66, 4110–4119
Xu, Y., & Wang, S. (2016). Mode selection for energy efficient content delivery in cellular networks. IEEE Communications Letters, 20, 728–731
Klaus, D., Chia-Hao, Y., Cassio, B.R., Peckka, J. (2010). Mode selection for device-to-device communication underlying an LTE-advanced network. In: Proceedings of the IEEE wireless communication and networking conference, Sydney, Australia, 18–21 April 2010; pp. 1–6.
Yuri, V.L.M., Rodrigo, L.B., Carlos, F.M.S., Tarcisio, F.M., Jose, M.B.S., Francisco, R.P.C. (2014). Uplink power control with variable target SINR for D2D communications underlaying cellular networks. In: Proceedings of the 20th European wireless conference, Barcelona, Spain, 14–16 May 2014; pp. 1–5.
Lee, N., Lin, X., Andrews, J. G., & Heath, R. W. (2015). Power control for D2D underlaid cellular networks: Modelling, algorithms, and analysis. IEEE Journal on Selected Areas in Communications, 33, 1–13
Achki, S., Aziz, L., Gharnati F., & Ait Ouahman, A., (2020). User association strategy for energy efficiency and interference mitigation of heterogeneous networks. Advances in Materials Science and Engineering.
Bakht, K., Jameel F., Ali Z., Khan W.U., Khan I., Sardar Sidhu, G.A., Lee J.W. (2019). Power allocation and user assignment scheme for beyond 5G heterogeneous networks. Wireless Communication & Mobile Computing, Hindwai.
Mahmoud, H. H., ElAttar, H. M., Saafan, A., & ElBadawy, H. (2017). Optimal operational parameters for 5G energy harvesting cognitive wireless sensor networks, 5G wireless with cognitive radio and IoT. IETE Technical Review, 34, 62–72
Bei, M., Hailin, Z., & Zhaowei, Z. (2015). Joint power allocation and mode selection for D2D communications with imperfect CSI. China Communications, 12, 73–81
Yifei, H., Ali, A. N., Salman, D., & Xiangyun, Z. (2016). Mode selection, resource allocation, and power control for D2D-enabled two-tier cellular network. IEEE Transactions on Communications, 64, 3534–3547
Arifur, R., Youngdoo, L., & Insoo, K. (2016). An e_cient transmission mode selection based on reinforcement learning for cooperative cognitive radio networks. Human Centric Computing and Information Sciences, 6, 1–14
Yaohua, S., Mugen, P., & Shiwen, M. (2019). Deep reinforcement learning-based mode selection and resource management for green fog radio access networks. IEEE Internet of Things Journal, 6, 1960–1971
Shiwen, N., Zhiqiang, F., Ming, Z., Xinyu, G., Lin, Z. (2016). Q-learning based power control algorithm for D2D communication. In: Proceedings of the IEEE 27th annual international symposium on personal, indoor, and mobile radio communications, Valencia, Spain, 4–8 September 2016; pp. 1–6.
Yimingm, Q., Zelin, J., Yonghao, Z., Guanghao, M., Gang, X. (2018). Joint mode selection and power adaption for D2D communication with reinforcement learning. In: Proceedings of the 15th International Symposium on Wireless Communication Systems, Lisbon, Portugal, 28–31 August 2018; pp. 1–6.
Auer, G., Giannini, V., Desset, C., Godor, I., Skillermark, P., Olsson, M., Imran, M. A., Sabella, D., Gonzalez, M. J., Blume, O., & Fehske, A. (2011). How much energy is needed to run a wireless network? IEEE Wireless Communications, 18, 40–49
Xiaojian, L., Shaowei, W. (2017) E_cient remote radio head switching scheme in cloud radio access network: A load balancing perspective. In: Proceedings of the IEEE conference on computer communications, Atlanta, GA, USA, 1–4 May 2017; pp. 1–9.
Arnob, G., Laura, C., Eitan, A. (2015) Nash equilibrium for femto-cell power allocation in HetNets with channel uncertainty. In: Proceedings of the IEEE global communications conference, San Diego, CA, USA, 6–10 December 2015; pp. 1–7.
Park, H., Lim, Y. (2020) Adaptive power control using reinforcement learning in 5G mobile networks. In: Proceedings of the international conference on information networking, Barcelona, Spain, 7–10 January 2020; pp. 409–414.
Nasir, Y.S., Guo, D. (2018). Multi-agent deep reinforcement learning for distributed dynamic power allocation in wireless networks. arXiv, arXiv:1808.00490.
3GPP. TR 37.885, Technical specification group radio access networks, study on evaluation methodology of new vehicle-to-everything (V2X) use cases for LET and NR, Rel. 16; Sophia-Antipolis: Valbonne, France, 2018.
Daniel, K., Jakob, E., Michael, B., & Laura, B. (2012). Recent development and applications of SUMO-simulation of urban mobility. International Journal on Advances in Systems and Measurements, 5, 128–138
3GPP. TR 22.886, Technical specification group radio access networks, study on enhancement of 3GPP support for 5G V2X Services, Rel. 15; Sophia-Antipolis: Valbonne, France, 2017.
YooSeung, S., & Hyungkyun, C. (2017). Analysis of V2V broadcast performance limit for WAVE communication systems using two-ray path loss model. ETRI Journal, 39, 213–221
3GPP. TR 36.872, Technical specification group radio access network, small cell enhancements for E-UTRA and E-UTRAN Physical Layer Aspects, Rel. 11; Sophia-Antipolis: Valbonne, France, 2013.
Khaled, S.H., Engy, M.M. (2013). Device-to-device communication distance analysis in interference limited cellular networks. In: Proceedings of the ISWCS 2013; The tenth international symposium on wireless communication systems, Ilmenau, Germany, 27–30 August 2013; pp. 1–5.
Seok, B., Sicato, J. C. S., Erzhena, T., Xuan, C., Pan, Y., & Park, J. H. (2020). Secure D2D communication for 5G IoT network based on lightweight cryptography. Applied Sciences, 10, 217
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Sachan, S., Sharma, R. & Sehgal, A. SINR Based Energy Optimization Schemes for 5G Vehicular Sensor Networks. Wireless Pers Commun 127, 1023–1043 (2022). https://doi.org/10.1007/s11277-021-08561-6
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11277-021-08561-6