Resource Allocation Optimization for Delay-Sensitive Traffic in Fronthaul Constrained Cloud Radio Access Networks

Li, Jian; Peng, Mugen; Cheng, Aolin; Yu, Yu-Ling; Wang, Chonggang

doi:10.1109/jsyst.2014.2364252

Cited by 64 publications

(49 citation statements)

References 23 publications

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“…To achieve the flexible tradeoff between cooperation gain and fronthaul consumption, a hybrid CoMP scheme is designed in [117] for the downlink transmission in C-RANs with capacity-limited fronthaul links and delay-sensitive traffic. To maintain the low traffic delay, the delay-aware power and rate allocation with fronthaul capability and RRH power constraints are then formulated as an infinite horizon constrained MDP in [117], where the linear approximation, online learning of value functions and stochastic gradient algorithm are presented to obtain a low-complexity and parallel solution.…”

Section: B Dynamic Crra With Queue-awarenessmentioning

confidence: 99%

“…To maintain the low traffic delay, the delay-aware power and rate allocation with fronthaul capability and RRH power constraints are then formulated as an infinite horizon constrained MDP in [117], where the linear approximation, online learning of value functions and stochastic gradient algorithm are presented to obtain a low-complexity and parallel solution. However, the online learning of value functions may suffer from slow convergence and lack of insight.…”

Section: B Dynamic Crra With Queue-awarenessmentioning

confidence: 99%

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Recent Advances in Cloud Radio Access Networks: System Architectures, Key Techniques, and Open Issues

Peng

Sun

et al. 2016

IEEE Commun. Surv. Tutorials

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356

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Abstract-As a promising paradigm to reduce both capital and operating expenditures, the cloud radio access network (C-RAN) has been shown to provide high spectral efficiency and energy efficiency. Motivated by its significant theoretical performance gains and potential advantages, C-RANs have been advocated by both the industry and research community. This paper comprehensively surveys the recent advances of C-RANs, including system architectures, key techniques, and open issues. The system architectures with different functional splits and the corresponding characteristics are comprehensively summarized and discussed. The state-of-the-art key techniques in C-RANs are classified as: the fronthaul compression, large-scale collaborative processing, and channel estimation in the physical layer; and the radio resource allocation and optimization in the upper layer. Additionally, given the extensiveness of the research area, open issues and challenges are presented to spur future investigations, in which the involvement of edge cache, big data mining, socialaware device-to-device, cognitive radio, software defined network, and physical layer security for C-RANs are discussed, and the progress of testbed development and trial test are introduced as well.

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Section: B Dynamic Crra With Queue-awarenessmentioning

confidence: 99%

Section: B Dynamic Crra With Queue-awarenessmentioning

confidence: 99%

Recent Advances in Cloud Radio Access Networks: System Architectures, Key Techniques, and Open Issues

Peng

Sun

et al. 2016

IEEE Commun. Surv. Tutorials

Self Cite

356

205

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show abstract

“…Figure 3 briefly describes the system's components that contribute to the total end-to-end delay. That is, all network components in CC-to-EC segment 5 , EC-to-RU segment 6 , and RU-to-UE segment 7 . This delay model is related to the distribution or/and centralization of the communication functions processing.…”

Section: Delay Model Based On Function Splitmentioning

confidence: 99%

“…In a separated data and control planes architecture, they proposed a usercentric decision on whether to retransmit or not based on some simple feedback from the RU. In CRAN settings, authors of [5] have proposed a queue-aware power and rate allocation for delay-sensitive traffic and formulate it as a Markov decision process. On the other hand, the authors of [6] have evaluated the impact of function splits on the energy and cost savings of the CRAN network.…”

Section: Introductionmentioning

confidence: 99%

Delay-aware green hybrid CRAN

Alabbasi

Çavdar

2017

2017 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

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Abstract-As a potential candidate architecture for 5G systems, cloud radio access network (CRAN) enhances the system's capacity by centralizing the processing and coordination at the central cloud. However, this centralization imposes stringent bandwidth and delay requirements on the fronthaul segment of the network that connects the centralized baseband processing units (BBUs) to the radio units (RUs). Hence, hybrid CRAN is proposed to alleviate the fronthaul bandwidth requirement. The concept of hybrid CRAN supports the proposal of splitting/virtualizing the BBU functions processing between the central cloud (central office that has large processing capacity and efficiency) and the edge cloud (an aggregation node which is closer to the user, but usually has less efficiency in processing). In our previous work, we have studied the impact of different split points on the system's energy and fronthaul bandwidth consumption. In this study, we analyze the delay performance of the end user's request. We propose an end-to-end (from the central cloud to the end user) delay model (per user's request) for different function split points. In this model, different delay requirements enforce different function splits, hence affect the system's energy consumption. Therefore, we propose several research directions to incorporate the proposed delay model in the problem of minimizing energy and bandwidth consumption in the network. We found that the required function split decision, to achieve minimum delay, is significantly affected by the processing power efficiency ratio between processing units of edge cloud and central cloud. High processing efficiency ratio (≈ 1) leads to significant delay improvement when processing more base band functions at the edge cloud.Index Terms-5G, network architecture, cloud RAN, end-toend delay, network function split, virtualized cloud RAN.

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“…Considering the individual data rate requirement and transmit power of each BS, energyefficient CoMP precoding was proposed [12]. And EEoriented resource allocation algorithm was also proposed in CoMP-enabled heterogeneous network, considering of Moreover, in C-RAN with non-ideal fronthaul network, delay-sensitive services can benefit from the efficient strategy proposed in [29]. And multicore fiber media (MCF) has been investigated for the future optical fronthaul [31].…”

Section: Introductionmentioning

confidence: 99%

Efficient resource allocation for passive optical fronthaul-based coordinated multipoint transmission

Wang

et al. 2016

J Wireless Com Network

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The centralized processing in cloud radio access network enables cooperation between baseband processing units (BBUs) like inter-cell interference (ICI) cancellation on the basis of coordinated multipoint (CoMP). Large amounts of the sharing data will be transmitted through fronthaul transport network. In the paper, both integer non-linear programming (INLP) optimization model and adaptive genetic algorithm (GA) are explored to release the capacity pressure of the fronthaul transport network when CoMP is introduced. We also consider the resource allocation problem of the passive optical fronthaul network. The proposed algorithm tries to reduce the downlink bandwidth and improve the optical resource allocation efficiency of the optical fronthaul with minimal influence on the fronthaul topology. During the simulations, three critical factors are considered: (1) the number of cell edge users, (2) the average traffic demand of cell edge users, (3) the size of cell cluster used to enable the CoMP. The simulation results show that the most efficient bandwidth saving and optical resource allocation can be achieved with INLP, while the proposed adaptive GA nearly has the same performance with low computational complexity and fast convergence, which is more applicable for the large-scale fronthaul network. Furthermore, the load difference of the fronthaul transport network can be further reduced.

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Resource Allocation Optimization for Delay-Sensitive Traffic in Fronthaul Constrained Cloud Radio Access Networks

Cited by 64 publications

References 23 publications

Recent Advances in Cloud Radio Access Networks: System Architectures, Key Techniques, and Open Issues

Recent Advances in Cloud Radio Access Networks: System Architectures, Key Techniques, and Open Issues

Delay-aware green hybrid CRAN

Efficient resource allocation for passive optical fronthaul-based coordinated multipoint transmission

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