Performance Optimization and Architectural Advancements in Cloud Radio Access Networks (C-RAN) for 5G and Beyond

Authors

  • Qutaiba I. Ali

    Computer Engineering Department, University of Mosul, Mosul 41002, Iraq

DOI:

https://doi.org/10.30564/jeis.v7i1.9960
Received: 11 February 2025 | Revised: 1 March 2025 | Accepted: 23 March 2025 | Published Online: 1 April 2025

Abstract

As the demand for high-speed, low-latency, and energy-efficient mobile communications continues to surge with the proliferation of IoT, AR/VR, and ultra-reliable applications, traditional Distributed Radio Access Network (D-RAN) architectures face critical limitations. Cloud Radio Access Network (C-RAN) emerges as a promising alternative that centralizes baseband processing to improve scalability, resource utilization, and operational flexibility. This paper presents a comprehensive evaluation of C-RAN architecture, focusing on structural models, fronthaul technologies, and cloud-based service logic. A detailed mathematical modeling framework is developed to assess key performance indicators, including latency, spectral efficiency, energy efficiency, and fronthaul capacity. Extensive results demonstrate that C-RAN achieves up to 45% gains in energy efficiency, a 35% improvement in spectral efficiency, and latency reductions of over 40% compared to D-RAN. Additional results reveal enhanced handover success rates, better BBU pool utili-zation, and increased reliability, with packet loss rates reduced to under 0.5%. Despite increased fronthaul bandwidth requirements, optical solutions such as DWDM and PON mitigate the bottleneck effectively. The findings confirm that C-RAN offers a robust, scalable, and cost-efficient solution for 5G and future mobile networks, enabling dynamic resource allocation, advanced interference management, and centralized network intelligence. The paper also addresses implementation challenges, including fronthaul provisioning and security, and outlines future research directions such as virtualization, AI-driven orchestration, and edge-cloud integration to fully harness the potential of C-RAN in ultra-dense and heterogeneous network environments.

Keywords:

Cloud Radio Access Network (C-RAN); 5G Architecture; Virtualization; Energy Efficiency; Fronthaul Network; Spectral Efficiency; Baseband Unit Pool (BBU Pool)

References

[1] Ali, Q.I., 2009. Performance evaluation of WLAN internet sharing using DCF & PCF modes. The International Arab Journal of Information Technology. 1(1), 38–45.

[2] Cisco, Visual Networking , 2013. Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2012–2017. Available from: website: https://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/white_paper_c11-520862.html (cited 15 January 2025).

[3] Hwang, I., Song, B., Soliman, S.S., 2013. A Holistic view on Hyper-Dense Heterogeneous and Small Cell Networks. IEEE Communications Magazine. 51(6), 20–27.

[4] Gozalvez, J., 2015. Tentative 3GPP Timeline for 5G [Mobile Radio]. IEEE Vehicular Technology Magazine. 10(3), 12–18. DOI: https://doi.org/10.1109/MVT.2015.2453573

[5] IMT-2020 (5G) Promotion Group, 2015. 5G White Paper. Available from: https://wenku.baidu.com/view/2a32635a0066f5335b81215a.html(cited 15 January 2025).

[6] Checko, A., Christiansen, H.L., Yan, Y., et al., 2015. Cloud RAN for Mobile Networks—A Technology Overview. IEEE Communications Surveys & Tutorials. 17(1), 405–426.

[7] Kumaran, S., 2015. A Perspective of the Cellular Network of the Future: Cloud-RAN. Proceedings of the First International Afro-European Conference for Industrial Advancement AECIA 2014; November 17–November 19, 2014; Addis Ababa, Ethiopia. pp. 27–41.

[8] Liu, C, Sundaresan, K, Jiang, M, et al., 2013. The case for re-configurable backhaul in cloud-RAN based small cell networks. Proceedings of 2013 Proceedings IEEE INFOCOM; April 14–April 19, 2013; Turin, Italy. pp. 1124–1132.

[9] Peng, M., Wang, C., Lau, V., et al., 2015. Fronthaul-Constrained Cloud Radio Access Networks: Insights and Challenges. IEEE Wireless Communications. 22(2), 126–135.

[10] Miyanabe, K., Suto, K., Fadlullah, Z.M., et al., 2015. A cloud radio access network with power over fiber toward 5G networks: QoE-guaranteed design and operation. IEEE Wireless Communications. 22(4), 58–64.

[11] Chanclou, P., Pizzinat, A., Le Clech, F., et al., 2013. Optical fiber solution for mobile fronthaul to achieve cloud radio access network. Proceedings of 2013 Future Network and Mobile Summit; July 3–July 5, 2013; Lisboa, Portugal. pp. 1–11.

[12] Oliva, A., Hernandez, J., Larrabeiti, D., et al., 2016. An overview of the CPRI specification and its application to C-RAN-based LTE scenarios. IEEE Communications Magazine. 54(2), 152–159. DOI: https://doi.org/10.1109/MCOM.2016.7402275

[13] European Telecommunications Standards Institute (ETSI), 2011. Open Radio equipment Interface (ORI); ORI Interface Specification; Part 1: Low Layers (Release 1). Available from: https://www.etsi.org/deliver/etsi_gs/ORI/001_099/00201/01.01.01_60/gs_ORI00201v010101p.pdf (cited 15 January 2025).

[14] Harada, H., 2009. Cognitive Wireless Cloud: A Network Concept to Handle Heterogeneous and Spectrum Sharing Type Radio Access Networks. Proceedings of IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications; September 13–September16, 2009; Tokyo, Japan. pp. 1–5.

[15] Harada, H., Murakami, H., Ishizu, K., et al., 2007. A Software Defined Cognitive Radio System: Cognitive Wireless Cloud. Proceedings of IEEE GLOBECOM 2007-IEEE Global Telecommunications Conference; November 26–November 30, 2007; Washington, DC, USA. pp. 294–299.

[16] Harada, H., Murakami, H., Ishizu, K., et al., 2009. Research and Development on Heterogeneous Type and Spectrum Sharing Type Cognitive Radio Systems. Proceedings of 4th International Conference on Cognitive Radio Oriented Wireless Networks and Communications; June 22–June 24, 2009; Hanover, Germany. pp. 1–7.

[17] Georgakopoulos, A., Karvounas, D., Stavroulaki, V., et al., 2012. Cognitive Cloud-Oriented Wireless Networks for the Future Internet. Proceedings of IEEE Wireless Communications and Networking Conference Workshops (WCNCW); April 1, 2012; Paris, France. pp. 431–435.

[18] Fiorani, M., Skubic, B., Mårtensson, J., et al., 2015. On the design of 5G transport networks. 30(3), 403–415.

[19] Common Public Radio Interface (CPRI), 2014. Interface Specification Version 6.1. Available from: extension://ngbkcglbmlglgldjfcnhaijeecaccgfi/https://www.cpri.info/downloads/CPRI_v_6_1_2014-07-01.pdf (cited 15 January 2025).

[20] FUJITSU Network Communications Inc., 2014. The Benefits of Cloud-RAN Architecture in Mobile Network Expansion. Available from: extension://ngbkcglbmlglgldjfcnhaijeecaccgfi/https://www.fujitsu.com/us/imagesgig5/CloudRANwp.pdf (cited 15 January 2025).

[21] Wu, J., Zhang, Z., Hong, Y., et al., 2015. Cloud radio access network (c-ran): A primer. IEEE Network. 29(1), 35–41.

[22] Peng, M., Sun, Y., Li, X., et al., 2016. Recent Advances in Cloud Radio Access Networks: System Architectures, Key Techniques, and Open Issues. IEEE Communications Surveys Tutorials. 18(3), 2282–2308.

[23] Simeone, O., Maeder, A., Peng, M., et al., 2016. Cloud Radio Access Network: Virtualizing Wireless Access for Dense Heterogeneous Systems. Journal of Communications and Networks. 18(2), 135–149.

[24] Hossain, E., Hasan, M., 2015. 5G Cellular: Key Enabling Technologies and Research Challenges. IEEE Instrumentation Measurement Magazine. 18(3), 11–21.

[25] Meerja, K.A., Shami, A., Refaey, A., 2015. Hailing Cloud Empowered Radio Access Networks. IEEE Wireless Communications. 22(1), 122–129.

[26] Panwar, N., Sharma, S., Singh, A.K., 2016. A survey on 5g: The next generation of mobile communication. Physical Communication. 18, 64–84.

[27] Suryaprakash, V., Rost, P., Fettweis, G., 2015. Are Heterogeneous Cloud-Based Radio Access Networks Cost Effective? IEEE Journal on Selected Areas in Communications. 33(10), 2239–2251.

[28] Barbarossa, S., Sardellitti, S., Lorenzo, P.D., 2014. Communicating While Computing: Distributed Mobile Cloud Computing over 5G Heterogeneous Networks. IEEE Signal Processing Magazine. 31(6), 45–55.

[29] Rost, P., Bernardos, C.J., Domenico, A.D., et al., 2014. Cloud Technologies for Flexible 5G Radio Access Networks. IEEE Communications Magazine. 52(5), 68–76.

[30] Cai, Y., Yu, F.R., Bu, S., 2014. Cloud Computing Meets Mobile Wireless Communications in Next Generation Cellular Networks. IEEE Network. 28(6), 54–59.

[31] ZTE Corporation, 2011. ZTE Green Technology Innovations, White Paper. Available from: extension://ngbkcglbmlglgldjfcnhaijeecaccgfi/https://www.zte.com.cn/content/dam/zte-site/www-zte-com-cn/mi_imgs/global/investor_relations/353156/P020120918593482919117.pdf (cited 15 January 2025).

[32] Hossain, M.F., Munasinghe, K.S., Jamalipour, A., 2013. Distributed Inter-BS Cooperation Aided Energy Efficient Load Balancing for Cellular Networks. IEEE Transactions on Wireless Communications. 12(11), 5929–5939.

[33] Alhumaima, R.S., Khan, M., Al-Raweshidy, H.S., 2016. Component and Parameterised Power Model for Cloud Radio Access Network. IET Communications. 10(7), 745–752.

[34] Bassoli, R., Renzo, M.D., Granelli, F., 2017. Analytical Energy-Efficient Planning of 5G Cloud Radio Access Network. Proceedings of IEEE International Conference on Communications (ICC); May 21–May 25, 2017; Paris, France. pp. 1–4.

[35] Tian, F., Zhang, P., Yan, Z., 2017. A Survey on C-RAN Security. IEEE Access. 5, 13372–13386.

[36] Ibrahim, Q., 2016. Enhanced power management scheme for embedded road side units. IET Computers & Digital Techniques. 10(4), 174–185.

[37] Kundu, L., Lin, X., Agostini, E., et al., 2023. Hardware Acceleration for Open Radio Access Networks: A Contemporary Overview. Available from: https://arxiv.org/abs/2305.09588 (cited 15 January 2025).

[38] Azariah, W., Bimo, F.A., Lin, C.-W., et al., 2024. A Survey on Open Radio Access Networks: Challenges, Research Directions, and Open Source Approaches. Sensors. 24(3), 1038. DOI: https://doi.org/10.3390/s24031038

[39] Chen, Y.-Z., Chen, T.Y.-H., Su, P.-J., et al., 2023. A Brief Survey of Open Radio Access Network (O-RAN) Security. Available from: https://arxiv.org/abs/2311.02311 (cited 15 January 2025).

[40] Alam, K., Habibi, M.A., Tammen, M., et al., 2024. A Comprehensive Tutorial and Survey of O-RAN: Exploring Slicing-aware Architecture, Deployment Options, Use Cases, and Challenges. Available from: https://arxiv.org/abs/2405.03555 (cited 15 January 2025).

[41] Alhabib, M.H., Ali, Q.I., 2023. Internet of autonomous vehicles communication infrastructure: a short review. Diagnostyka. 24(3), 1–9. DOI: https://doi.org/10.29354/diag/168310

[42] Talal, M., Anisi, M.H., Ngadi, M.A., et al., 2025. A comprehensive systematic review on machine learning application in the 5G-RAN architecture: Issues, challenges, and future directions. Journal of Network and Computer Applications. 233, 104041. DOI: https://doi.org/10.1016/j.jnca.2024.104041

[43] Polese, M., Dohler, M., Dressler, F., et al., 2023. Empowering the 6G Cellular Architecture with Open RAN. Available from: https://arxiv.org/abs/2312.02746 (cited 15 January 2025).

Downloads

How to Cite

Ali , Q. I. (2025). Performance Optimization and Architectural Advancements in Cloud Radio Access Networks (C-RAN) for 5G and Beyond. Journal of Electronic & Information Systems, 7(1), 22–38. https://doi.org/10.30564/jeis.v7i1.9960