Resource Allocation Energy Efficient Algorithm for H-CRAN in 5G
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Abstract
In today's generation, the demand for data rates has also increased due to the rapid surge in the number of users. With this increasing growth, there is a need to develop the next fifth generation network keeping in mind the need to replace the current 4G cellular network. The fifth generation (5G) design in mobile communication technology has been developed keeping in mind all the communication needs of the users. Heterogeneous Cloud Radio Access Network (H-CRAN) has emerged as a capable architecture for the newly emerging network infrastructure for energy efficient networks and high data rate enablement. It is considered as the main technology. Better service quality has been achieved by developing small cells into macro cells through this type of network. In addition, the reuse of radio resources is much better than that of homogeneous networks. In the present paper, we propose the H-CRAN energy-efficient methods. This energy-efficient algorithm incorporates an energy efficient resource allocation management design to deal to heterogeneous cloud radio access networks in 5G. System throughput fulfillment is elevating by incorporating an efficient resource allocation design by the energy consumption model. The simulation results have been demonstrated by comparing the efficiency of the introduced design with the existing related design.
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Wypiór, D., M. Klinkowski, and I. Michalski, Open RAN—Radio Access Network Evolution, Benefits and Market Trends. Applied Sciences, 2022. 12(1): p. 408.
Shaheen, H., et al., Utility-Based Joint Power Control and Resource Allocation Algorithm for Heterogeneous Cloud Radio Access Network (H-CRAN). Wireless Communications and Mobile Computing, 2022. 2022.
Dangi, R., et al., Study and investigation on 5G technology: A systematic review. Sensors, 2021. 22(1): p. 26.
Labana, M. and W. Hamouda, Unsupervised deep learning approach for near optimal power allocation in CRAN. IEEE Transactions on Vehicular Technology, 2021. 70(7): p. 7059-7070.
Fourati, H., et al. An Energy Efficient Scheme Using Heuristic Algorithms for 5G H-CRAN. in International Conference on Advanced Information Networking and Applications. 2022. Springer.
Mourtzis, D., J. Angelopoulos, and N. Panopoulos, Smart Manufacturing and Tactile Internet Based on 5G in Industry 4.0: Challenges, Applications and New Trends. Electronics, 2021. 10(24): p. 3175.
Israr, A., Q. Yang, and A. Israr, Power consumption analysis of access network in 5G mobile communication infrastructures—An analytical quantification model. Pervasive and Mobile Computing, 2022. 80: p. 101544.
Pana, V.S., O.P. Babalola, and V. Balyan, 5G radio access networks: A survey. Array, 2022: p. 100170.
Ayanampudi, H. and R. Dhuli, Performance analysis of Heterogeneous Cloud-Radio Access Networks: A user-centric approach with network scalability. Computer Communications, 2022. 194: p. 202-212.
Zhang, X., et al., An energy efficient resource allocation scheme based on cloud-computing in H-CRAN. IEEE Internet of Things Journal, 2019. 6(3): p. 4968-4976.
Arnob, S.S., et al. Dual-order resource allocation in 5G H-CRAN using matching theory and ant colony optimization algorithm. in IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society. 2020. IEEE.
Chughtai, N.A., et al., Energy efficient resource allocation for energy harvesting aided H-CRAN. IEEE Access, 2018. 6: p. 43990-44001.
Liu, Q., et al., On designing energy-efficient heterogeneous cloud radio access networks. IEEE Transactions on Green Communications and Networking, 2018. 2(3): p. 721-734.
Tyagi, S.K.S., et al., Computing resource optimization of big data in optical cloud radio access networked industrial Internet of Things. IEEE Transactions on Industrial Informatics, 2021. 17(11): p. 7734-7742.
Nabati, M., M. Maadani, and M.A. Pourmina, AGEN-AODV: an intelligent energy-aware routing protocol for heterogeneous mobile ad-hoc networks. Mobile Networks and Applications, 2022. 27(2): p. 576-587.
Jaffer, S.S., et al., A low cost PON-FSO based fronthaul solution for 5G CRAN architecture. Optical Fiber Technology, 2021. 63: p. 102500.
Sulaiman, M., Analysis of RAN and Comparing with C-RAN for LTE-Networks. 2021.
Bharath Raj, D. and D. Singh, Energy Efficiency in Mobility Management for 5G Heterogeneous Cloud Radio Access Network.
Kanwal, A., et al. Advantages of Co-Deployment of C-RAN and MEC in 5G. in 2021 International Bhurban Conference on Applied Sciences and Technologies (IBCAST). 2021. IEEE.
Weinberger, K., et al., Synergistic benefits in IRS-and RS-enabled C-RAN with energy-efficient clustering. IEEE Transactions on Wireless Communications, 2022.
Zhu, M., et al., Delay-aware energy-saving strategies for BBU pool in C-RAN: modeling and optimization. IEEE Access, 2021. 9: p. 63257-63266.
Yue, X., et al. Beamforming design and BBU computation resource allocation for power minimization in green C-RAN. in ICC 2021-IEEE International Conference on Communications. 2021. IEEE.
Datsika, E., et al., SDN-enabled resource management for converged Fi-Wi 5G Fronthaul. IEEE Journal on Selected Areas in Communications, 2021. 39(9): p. 2772-2788.
Iqbal, A., M.-L. Tham, and Y.C. Chang, Double deep Q-network-based energy-efficient resource allocation in cloud radio access network. IEEE Access, 2021. 9: p. 20440-20449.