Energy-efficient capacity offload to smallcells with interference compensation

Yang, Chungang; Guo, Kun; Sheng, Min; Li, Jiangdong; Yue, Jian Feng

doi:10.1109/wcnc.2014.6952513

Cited by 6 publications

(5 citation statements)

References 14 publications

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“…That is, most of the small cells underlaying macrocells cannot be effectively associated due to the much larger downlink power and antenna gains of macrocells. During the past decades, various schemes for traffic offloading have been proposed or standardized, for instance, mobility load balancing (MLB) [2], CRE, capacity offloading [13], [14], and dynamic association.…”

Section: ) Technical Interference and Traffic Imbalance Challengesmentioning

confidence: 99%

“…The authors in [13] proposed an energy-aware traffic offloading method between multiple SeNBs and MeNB, which was modeled as a Nash bargaining game. To attain an optimal win-win for both SeNBs and MeNB, mutual interference compensation, interference-related right selected target-SeNB and an energy-aware trigger of source-MeNB were provided in [13], which helped to attain more dimensions of cooperation gains and diversity.…”

Section: B Inter-tier Traffic Offloadingmentioning

confidence: 99%

“…To attain an optimal win-win for both SeNBs and MeNB, mutual interference compensation, interference-related right selected target-SeNB and an energy-aware trigger of source-MeNB were provided in [13], which helped to attain more dimensions of cooperation gains and diversity. In [14], to model data offloading, a queuing-theoretic model was formulated with the elastic data flows notion, or more explicitly, cell range expansion together with inter-cell interference coordination.…”

Section: B Inter-tier Traffic Offloadingmentioning

confidence: 99%

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DISCO: Interference-Aware Distributed Cooperation with Incentive Mechanism for 5G Heterogeneous Ultra-Dense Networks

Yang

Xiao

et al. 2018

IEEE Commun. Mag.

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Abstract-Interference and traffic imbalance hinder the improved system performance in heterogeneous ultra-dense networks. Network cooperation becomes a promising paradigm with sophisticated techniques which can significantly enhance the performance. In this article, a coalition game-theoretic framework is introduced to characterize the cooperative behaviors, and thus exploring these cooperative benefits and diversity gains. First, we introduce the basis of the coalition games, and then we survey its latest applications, in particular, the interference mitigation and traffic offloading. Different from most of the current applications, we concentrate on the cooperative incentive mechanism design since the node cooperation always means resource consumption and other costs. Moreover, for the incentive mechanism, a cooperative spectrum leasing is introduced. To mitigate the interference and balance traffic, we propose two schemes under the presented framework: interference alignment with spectrum leasing (IASL) and traffic offloading with spectrum leasing (TOSL). Simulation results show the improved performance of the cooperative gains using the proposed IASL and TOSL schemes.

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Section: ) Technical Interference and Traffic Imbalance Challengesmentioning

confidence: 99%

Section: B Inter-tier Traffic Offloadingmentioning

confidence: 99%

Section: B Inter-tier Traffic Offloadingmentioning

confidence: 99%

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DISCO: Interference-Aware Distributed Cooperation with Incentive Mechanism for 5G Heterogeneous Ultra-Dense Networks

Yang

Xiao

et al. 2018

IEEE Commun. Mag.

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“…When the macro BS is congested, then by mobile traffic offloading to femto cell either by co-operative game theory [46] or by markov`s queuing theory [82] the improvement of EE of the Macro BS and SE of the small BS can be obtained [48], [49][50][51][52][53]. By using Nash equilibrium game theory a trade-off relationship between the SE and EE efficiency can be established [44], [45]. Different types of path loss mechanisms like Rayleigh fading, Rician fading, Okumara hata, Friis transmission equation, shadowing, fading and lognormal shadowing [64]- [71].…”

Section: IImentioning

confidence: 99%

Coverage Probability of Hetnet Using Stochastic Geometry and Poisson Point Process

Sahu¹,

Pawar²

2018

IJCA

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The exponential growth in the number of cellular users along with their increasing demand of higher transmission rate, ultra low latency, guaranteed QoS and lower power consumption is of prime importance for the design of future generation networks. The spectral efficiency (SE) can be improved by better utilization of the network resources at the cost of reduction in the energy efficiency (EE) due to increase in the network power expenditure arising from densification of the network. One of the possible solution is to deploy Heterogeneous Network (HetNet) consisting of several tiers of small cell BSs overlaid within the coverage area of the macrocell. The HetNet can provide better coverage and data rate to the cell edge users in comparison to the macrocell only deployment. Therefore, optimal network planning is an important challenge for future heterogeneous network with high number of small cells. In order to tackle these challenges, here we focus on the random spatial modeling of Multi Tier Heterogeneous Network consisting of dense small cell access points using Poisson Point Process (PPP) with Vornoi Tessellation. Then we calculate the coverage and outage probability of the cellular network by using stochastic geometry.

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“…Some recent works indicate that the EE can be a significant requirement of future HetNets, especially when SeNBs/ MeNBs are densely deployed there for ensuring quality of experience. Several initial works on EE as well as traffic offloading and energy consumption tradeoff in HetNets can be found in our previous works [39][40][41], and reference therein.…”

Section: Heterogenous Network and Smallcellmentioning

confidence: 99%

Strategic bargaining in wireless networks: basics, opportunities and challenges

Yang

Anpalagan³

2014

IET Communications

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Strategic bargaining cooperative games have found extensive applications to resource management in wireless networks. In this survey, basics of a strategic bargaining game and solution concepts are firstly presented. Geometrical interpretations are introduced to better understand real meanings of them. Then, the authors survey the applications of various strategic bargaining games for the emerging wireless networks, where the authors concentrate on several interesting problems based on their previous systematic studies: (i) distributed resource management design for cognitive radio networks based on geometrical interpretation of the cooperative solution; (ii) asymmetric bargaining modelling for green communications; (iii) a unified utility tradeoff design between spectral and energy efficiency in heterogeneous cellular networks; (iv) the cooperative rate splitting game for Long Term Evolution-coordinated multi-point system; and (v) a general bargaining formulation with different tradeoffs between efficiency and fairness. In addition, the authors survey the applications of strategic bargaining games to cooperation incentive mechanism, bargaining game on capacity region of interference channel and multiuser and multimedia applications. Finally, challenges and potential research direction are summarised in this work.

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Energy-efficient capacity offload to smallcells with interference compensation

Cited by 6 publications

References 14 publications

DISCO: Interference-Aware Distributed Cooperation with Incentive Mechanism for 5G Heterogeneous Ultra-Dense Networks

DISCO: Interference-Aware Distributed Cooperation with Incentive Mechanism for 5G Heterogeneous Ultra-Dense Networks

Coverage Probability of Hetnet Using Stochastic Geometry and Poisson Point Process

Strategic bargaining in wireless networks: basics, opportunities and challenges

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