Backhaul Traffic Minimization under Cache-Enabled CoMP Transmissions over 5G Cellular Systems

Yu, Ya-Ju; Tsai, Wei-Chieh; Pang, Ai‐Chun

doi:10.1109/glocom.2016.7841619

Cited by 19 publications

(15 citation statements)

References 12 publications

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“…where the objective function µ(C s , ϕ) = max λ λ| {Cs,ϕ} is the network capacity for the given SBS cache size C s and traffic steering ratio ϕ (i.e., the maximal traffic density that can be catered), ŘRAN and ŘBH denote the per user rate requirements for radio access and backhaul transmissions 3 , respectively. The cache size of MBSs C m can be determined with C s according to Eq.…”

Section: Capacity-optimal Caching Formulationmentioning

confidence: 99%

“…to meet the 1000× capacity enhancement in 5G networks and beyond [1], [2]. With network further densified, deploying ideal backhaul with unconstrained capacity for each small cell may be impractical, due the unacceptably high costs of deployment and operation [3], [4]. Thus, one of the key problems towards 5G is to reduce the required backhaul capacity while keeping the system capacity.…”

mentioning

confidence: 99%

“…The average transmission rate is adopted for QoS guarantee as the services suitable for pro-active caching are mostly elastic in practical networks, such as popular video streaming. Furthermore,3 In practical systems, the backhaul rate requirementŘBH is generally much higher than that of the radio access partŘRAN, considering the end-to-end delay and the serial transmission structure.…”

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confidence: 99%

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Cost-Effective Cache Deployment in Mobile Heterogeneous Networks

Zhang

Yang

et al. 2017

IEEE Trans. Veh. Technol.

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This paper investigates one of the fundamental issues in cache-enabled heterogeneous networks (HetNets): how many cache instances should be deployed at different base stations, in order to provide guaranteed service in a cost-effective manner. Specifically, we consider two-tier HetNets with hierarchical caching, where the most popular files are cached at small cell base stations (SBSs) while the less popular ones are cached at macro base stations (MBSs). For a given network cache deployment budget, the cache sizes for MBSs and SBSs are optimized to maximize network capacity while satisfying the file transmission rate requirements. As cache sizes of MBSs and SBSs affect the traffic load distribution, inter-tier traffic steering is also employed for load balancing. Based on stochastic geometry analysis, the optimal cache sizes for MBSs and SBSs are obtained, which are threshold-based with respect to cache budget in the networks constrained by SBS backhauls. Simulation results are provided to evaluate the proposed schemes and demonstrate the applications in cost-effective network deployment.

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Section: Capacity-optimal Caching Formulationmentioning

confidence: 99%

mentioning

confidence: 99%

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confidence: 99%

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Cost-Effective Cache Deployment in Mobile Heterogeneous Networks

Zhang

Yang

et al. 2017

IEEE Trans. Veh. Technol.

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“…Otherwise, coordinated beamforming (CB) CoMP is employed where only CSI is shared between BSs for joint precoding. A number of studies in the literature utilize cached data at the BS to optimize user-centric CoMP clusters to reduce BH traffic demand in isolation [27], [28]. A further user-centric clustering is studied in [29] where cached data at SCs are utilized to form optimum user-centric clusters to reduce BH traffic and increase network throughput for a given maximum cluster size (CS).…”

Section: A Literature Reviewmentioning

confidence: 99%

Radio & BH Load-Aware Multi-Objective Clustering in Multi-Cell MIMO Cooperative Networks

Bassoy

Jaber

Onireti

et al. 2021

IEEE Trans. Veh. Technol.

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Coordinated Multipoint (CoMP) is one of the key technologies identified for future wireless networks to mitigate inter-cell interference, especially in a dense deployment scenario. However, CoMP can't be realized for the whole network due to its computational complexity, synchronization between coordinating base stations (BSs) and high backhaul (BH) capacity requirement. BSs need to be clustered into smaller groups and CoMP can be activated within these smaller clusters. In this paper, we develop a multi-objective, dynamic clustering model for multi-user, jointtransmission CoMP to jointly optimize spectral efficiency (SE), radio access network (RAN) load and BH load. We formulate our load-aware model as two coalitional sub-games for small cell and user equipment clustering, respectively. Merge/split/transfer actions for each sub-game are defined and a complexity and stability analysis is provided. Extensive simulation results show that our model provides as good SE in low load when compared to a greedy model, and significantly better load balancing with a reduced number of unsatisfied users and increased throughput in high load scenario. On average 49% increase in the overall system throughput is observed in our simulations when compared to the greedy model.

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“…In [9], the user association problem is modeled as an one-to-many game problem, based on which algorithm is proposed to maximize the average download rate under a given content placement strategy. In [10], an user association algorithm under a given content distribution in a CoMP enabled network is proposed to minimize the backhaul load under a guaranteed rate requirements of UEs. In [11], the content caching and user association schemes are proposed on two different scales: The caching algorithm operates in a long time scale and the user association algorithm operates frequently.…”

Section: Introductionmentioning

confidence: 99%

Cross-Entropy Method for Content Placement and User Association in Cache-Enabled Coordinated Ultra-Dense Networks

Wang

et al. 2019

Entropy

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Due to the high splitting-gain of dense small cells, Ultra-Dense Network (UDN) is regarded as a promising networking technology to achieve high data rate and low latency in 5G mobile communications. In UDNs, each User Equipment (UE) may receive signals from multiple Base Stations (BSs), which impose severe interference in the networks and in turn motivates the possibility of using Coordinated Multi-Point (CoMP) transmissions to further enhance network capacity. In CoMP-based Ultra-Dense Networks, a great challenge is to tradeoff between the gain of network throughput and the worsening backhaul latency. Caching popular files on BSs has been identified as a promising method to reduce the backhaul traffic load. In this paper, we investigated content placement strategies and user association algorithms for the proactive caching ultra dense networks. The problem has been formulated to maximize network throughput of cell edge UEs under the consideration of backhaul load, which is a constrained non-convex combinatorial optimization problem. To decrease the complexity, the problem is decomposed into two suboptimal problems. We first solved the content placement algorithm based on the cross-entropy (CE) method to minimize the backhaul load of the network. Then, a user association algorithm based on the CE method was employed to pursue larger network throughput of cell edge UEs. Simulation were conducted to validate the performance of the proposed cross-entropy based schemes in terms of network throughput and backhaul load. The simulation results show that the proposed cross-entropy based content placement scheme significantly outperform the conventional random and Most Popular Content placement schemes, with with 50% and 20% backhaul load decrease respectively. Furthermore, the proposed cross-entropy based user association scheme can achieve 30% and 23% throughput gain, compared with the conventional N-best, No-CoMP, and Threshold based user association schemes.

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Backhaul Traffic Minimization under Cache-Enabled CoMP Transmissions over 5G Cellular Systems

Cited by 19 publications

References 12 publications

Cost-Effective Cache Deployment in Mobile Heterogeneous Networks

Cost-Effective Cache Deployment in Mobile Heterogeneous Networks

Radio & BH Load-Aware Multi-Objective Clustering in Multi-Cell MIMO Cooperative Networks

Cross-Entropy Method for Content Placement and User Association in Cache-Enabled Coordinated Ultra-Dense Networks

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