A Novel Coalitional Structure Generation Algorithm for Interference Mitigation in Small Cell Networks

Yang, Guang; Esmailpour, Amir; Cao, Ye

doi:10.1109/glocom.2016.7841525

Cited by 3 publications

(6 citation statements)

References 11 publications

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“…That is, we assumed that the coverage of an SBS was 50 m. In addition, we assumed that these SBSs were omnidirectional. The transmission power of the SBSs was set to 20 dBm, and each SBS was assigned four sub‐channels, to separately serve four SUE units , , . The total number of available sub‐channels was set to N = 20.…”

Section: Simulation Results and Analysismentioning

confidence: 99%

“…The denser the SBS deployments become, the better the cooperative model can improve the network. Our previously proposed SDN‐based cooperative network model is based on the traditional network architecture. In this work, the cooperation among SBSs is based on the SDN architecture, as illustrated in Fig.…”

Section: Sdn‐based Hierarchical Agglomerative Clustering Formation Fomentioning

confidence: 99%

“…The formulation of an appropriate similarity criterion to cluster SBSs is an important consideration. Therefore, we introduce a suitability function based on the value v ( C l ) .…”

Section: Sdn‐based Hierarchical Agglomerative Clustering Formation Fomentioning

confidence: 99%

“…To improve the spectral efficiency of UD‐SCNs, the authors in introduced a bargaining cooperative game algorithm to investigate potential cooperation gains. The authors in proposed a novel cooperative approach among adjacent small cells, which was formulated as a coalitional structure generation with characteristic forms. This method is particularly applicable to massive small cell deployment scenarios.…”

Section: Introductionmentioning

confidence: 99%

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SDN-Based Hierarchical Agglomerative Clustering Algorithm for Interference Mitigation in Ultra-Dense Small Cell Networks

Yang¹,

Cao²,

Esmailpour³

et al. 2018

ETRI Journal

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Ultra‐dense small cell networks (UD‐SCNs) have been identified as a promising scheme for next‐generation wireless networks capable of meeting the ever‐increasing demand for higher transmission rates and better quality of service. However, UD‐SCNs will inevitably suffer from severe interference among the small cell base stations, which will lower their spectral efficiency. In this paper, we propose a software‐defined networking (SDN)‐based hierarchical agglomerative clustering (SDN‐HAC) framework, which leverages SDN to centrally control all sub‐channels in the network, and decides on cluster merging using a similarity criterion based on a suitability function. We evaluate the proposed algorithm through simulation. The obtained results show that the proposed algorithm performs well and improves system payoff by 18.19% and 436.34% when compared with the traditional network architecture algorithms and non‐cooperative scenarios, respectively.

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Section: Simulation Results and Analysismentioning

confidence: 99%

Section: Sdn‐based Hierarchical Agglomerative Clustering Formation Fomentioning

confidence: 99%

“…The formulation of an appropriate similarity criterion to cluster SBSs is an important consideration. Therefore, we introduce a suitability function based on the value v ( C l ) .…”

Section: Sdn‐based Hierarchical Agglomerative Clustering Formation Fomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

SDN-Based Hierarchical Agglomerative Clustering Algorithm for Interference Mitigation in Ultra-Dense Small Cell Networks

Yang¹,

Cao²,

Esmailpour³

et al. 2018

ETRI Journal

Self Cite

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“…One member is not joined to more than one cluster so that f ∈ C l and C l ∩ C m = φ are maintained; one member has to join one of the clusters so that U C l ∈CS C l = F is reinforced. The relative definitions of coalitional structure generation are introduced from references [25]- [27].…”

Section: All Members Are Denoted By a Set Of All Sbssmentioning

confidence: 99%

A Hierarchical Clustering Algorithm for Interference Management in Ultra-Dense Small Cell Networks

et al. 2020

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Ultra-dense small cell networks (UD-SCNs) will be an integral part of next generation network (NGN). How to deal with serious interference is one of the important challenges in a UD-SCN. In this paper, the cooperative interference management problem for a UD-SCN is explored by allowing small cell base stations (SBSs) to collaborate with their neighbors. The proposed coalitional structure generation among SBSs can mitigate the co-tier interference within a coalition, thus improving the network capacity. Specifically, a cooperative scheme among the neighboring SBSs is formulated as a coalitional structure generation with characteristic forms. Furthermore, the relative sub-channel resources are allocated in the process of cluster generation. Compared with the existing SBS cooperative schemes, the novelty of the proposed SBS cooperation method, which uses a hierarchical clustering algorithm (SC-HCA) to compute the pairs of members, is demonstrated. The computation can enhance the efficiency of the proposed algorithm and is especially suitable for UD-SCN scenarios with tens and even hundreds of cells. The simulation results show that the proposed SC-HCA achieves a 422.13% system data rate improvement relative to that of the non-cooperative scheme in a UD-SCN scenario. INDEX TERMS Coalitional structure generation, hierarchical clustering, interference management, ultra-dense small cell networks.

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An Abortion Based Search Method for Optimal Coalition Structure Generation

2022

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A Novel Coalitional Structure Generation Algorithm for Interference Mitigation in Small Cell Networks

Cited by 3 publications

References 11 publications

SDN-Based Hierarchical Agglomerative Clustering Algorithm for Interference Mitigation in Ultra-Dense Small Cell Networks

SDN-Based Hierarchical Agglomerative Clustering Algorithm for Interference Mitigation in Ultra-Dense Small Cell Networks

A Hierarchical Clustering Algorithm for Interference Management in Ultra-Dense Small Cell Networks

An Abortion Based Search Method for Optimal Coalition Structure Generation

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