Cloud radio access network (C-RAN) has been widely regarded as a promising techniques for 5G cellular mobile communication. By decoupling radio and baseband processing from all-in-one macro base station into remote radio head (RRH) and baseband unit (BBU) pool, C-RAN can significantly improve the flexibility and scalability of cellular mobile system with less ownership cost and operational expenditure. In 5G systems, the delay tolerance is very strict and usually limited within 5ms; while applications hold different quality-of-service (QoS) towards providing proper service. In terms of this, we classify mobile applications with different priorities, each of which holds a specified delay constraint. Based on network calculus, a theory for deterministic queuing systems, we propose an analysis method revealing delay and backlog upper-bounds for applications with different priorities, indicating the minimum required processing capacity of the C-RAN system. Numerical analysis and experiments driven by real data trace are conducted to validate the derived upper-bounds. Experiment results show that the proposed bounds for both delay and backlog in C-RAN hold great potential to guide the mobile network operator for C-RAN deployment and operation.
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Cisco Visual Networking Index (2017) Global mobile data traffic forecast update, 2016-2021. Cisco, Tech. Rep.
Fortes S, Aguilar-García A, Barco R, Barba FB, Fernández-Luque JA, Fernández-Durán A (2015) Management architecture for location-aware self-organizing lte/lte-a small cell networks. IEEE Commun Mag 53(1):294–302
Choi L-U, Murch RD (2004) A transmit preprocessing technique for multiuser mimo systems using a decomposition approach. IEEE Trans Wirel Commun 3(1):20–24
Larsson EG, Edfors O, Tufvesson F, Marzetta TL (2014) Massive mimo for next generation wireless systems. IEEE Commun Mag 52(2):186–195
Rappaport TS, Sun S, Mayzus R, Zhao H, Azar Y, Wang K, Wong GN, Schulz JK, Samimi M, Gutierrez F Jr (2013) Millimeter wave mobile communications for 5g cellular: it will work!. IEEE Access 1 (1):335–349
C-RAN: the road towards green RAN. China Mobile, Tech. Rep. (2011)
Lin Y, Shao L, Zhu Z, Wang Q, Sabhikhi RK (2010) Wireless network cloud: architecture and system requirements. IBM J Res Dev 54(1):4–1
Li Y, Jiang T, Luo K, Mao S (2017) Green heterogeneous cloud radio access networks: potential techniques, performance trade-offs, and challenges. IEEE Commun Mag 55(11):33– 39
Li S, Xu LD, Zhao S (2018) 5g internet of things: a survey. J Indust Inf Integr 10:1–9. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S2452414X18300037
Sundaresan K, Arslan MY, Singh S, Rangarajan S, Krishnamurthy SV (2016) Fluidnet: a flexible cloud-based radio access network for small cells. IEEE/ACM Trans Network 24(2):915– 928
Dahrouj H, Douik A, Dhifallah O, Al-Naffouri TY, Alouini M (2015) Resource allocation in heterogeneous cloud radio access networks: advances and challenges. IEEE Wirel Commun 22(3):66–73
Peng M, Zhang K, Jiang J, Wang J, Wang W (2015) Energy-efficient resource assignment and power allocation in heterogeneous cloud radio access networks. IEEE Trans Veh Technol 64(11):5275–5287
Huawei (2011) Cloud RAN introduction. In: The 4th CJK international workshop - technology evolution and spectrum
ZTE green technology innovations white paper, ZET, Tech Rep. (2011)
Peng M, Yan S, Poor HV (2014) Ergodic capacity analysis of remote radio head associations in cloud radio access networks. IEEE Wireless Commun Lett 3(4):365–368
Liao Y, Song L, Li Y, Zhang YA (2017) How much computing capability is enough to run a cloud radio access network? IEEE Commun Lett 21(1):104–107
Li J, Peng M, Cheng A, Yu Y, Wang C (2017) Resource allocation optimization for delay-sensitive traffic in fronthaul constrained cloud radio access networks. IEEE Syst J 11(4):2267– 2278
Tang J, Tay WP, Quek TQS (2015) Cross-layer resource allocation with elastic service scaling in cloud radio access network. IEEE Trans Wirel Commun 14(9):5068–5081
Zhao L, Sun W, Shi Y, Liu J (2018) Optimal placement of cloudlets for access delay minimization in sdn-based internet of things networks. IEEE Internet Things J 5(2):1334– 1344
Liu J, Kato N, Ma J, Sakano T (2014) Throughput and delay tradeoffs for mobile ad hoc networks with reference point group mobility. IEEE Trans Wirel Commun 14(3):1266–1279
Xiong J, Guo H, Liu J (2019) Task offloading in uav-aided edge computing: bit allocation and trajectory optimization. IEEE Commun Lett 23(3):538–541
Wang J, Zhao L, Liu J, Kato N (2019) Smart resource allocation for mobile edge computing: a deep reinforcement learning approach. In: IEEE Transactions on emerging topics in computing
Cruz R (1991) A calculus for network delay. I. Network elements in isolation. IEEE Trans Inf Theory 37(1):114– 131
Cruz R (1991) A calculus for network delay. II. Network analysis. IEEE Trans Inf Theory 37(1):132–141
Parekh AK, Gallagher RG (1994) A generalized processor sharing approach to flow control in integrated services networks: the multiple node case. IEEE/ACM Trans Network (ToN) 2(2):137–150
Boudec JL (1998) Application of network calculus to guaranteed service networks. IEEE Trans Inf Theory 44(3):1087– 1096
Checko A, Christiansen HL, Yan Y, Scolari L, Kardaras G, Berger MS, Dittmann L (2015) Cloud RAN for mobile networks—a technology overview. IEEE Commun Surveys Tutor 17(1):405–426
Ding Z, Poor HV (2013) The use of spatially random base stations in cloud radio access networks. IEEE Signal Process Lett 20(11):1138–1141
Yang Z, Ding Z, Fan P (2016) Performance analysis of cloud radio access networks with uniformly distributed base stations. IEEE Trans Veh Technol 65(1):472–477
Zhan SC, Niyato D (2016) A coalition formation game for remote radio heads cooperation in cloud radio access network. IEEE Trans Veh Technol PP(99):1–1
Chen X, Jin Y, Siwei Qiang WH, Jiang K (2015) Analyzing and modeling spatio-temporal dependence of cellular traffic at city scale. In: 2015 IEEE international conference on communications (ICC)
This research was supported by the Ministry of Education and China Mobile Research Foundation under Grant No. MCM20170307, and the NSF of China under Grant Nos. 61772480, 61602199, 61672474, 61402425.
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Xiong, M., Gu, L., Liu, H. et al. A Network Calculus Based Delay and Backlog Analysis for Cloud Radio Access Networks. Mobile Netw Appl 26, 1172–1181 (2021). https://doi.org/10.1007/s11036-019-01349-w
- Network calculus
- Performance analysis