Local altruistic coalition formation game for spectrum sharing and interference management in hyper‐dense cloud‐RANs

Sun, Youming; Wang, Jinlong; Sun, Fenggang; Zhang, Zongsheng

doi:10.1049/iet-com.2016.0094

Cited by 10 publications

(4 citation statements)

References 21 publications

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“…The matching algorithm studied in this paper belongs to the second-layer network-side optimization algorithm. For the channel allocation problem in the 5G environment, the existing research mainly uses a convex optimization algorithm [29], a greedy algorithm [30], and an algorithm based on game theory [31][32][33]. Among them, algorithms based on game theory are widely used.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Resource Allocation Method for Device-to-Device Communication in 5G Networks

Vu-Huu¹,

Le-Thanh²,

Nguyen-Xuan³

et al. 2022

Computers, Materials &Amp; Continua

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With the rapid development of the next-generation mobile network, the number of terminal devices and applications is growing explosively. Therefore, how to obtain a higher data rate, wider network coverage and higher resource utilization in the limited spectrum resources has become the common research goal of scholars. Device-to-Device (D2D) communication technology and other frontier communication technologies have emerged. Device-to-Device communication technology is the technology that devices in proximity can communicate directly in cellular networks. It has become one of the key technologies of the fifth-generation mobile communications system(5G). D2D communication technology which is introduced into cellular networks can effectively improve spectrum utilization, enhance network coverage, reduce transmission delay and improve system throughput, but it would also bring complicated and various interferences due to reusing cellular resources at the same time. So resource management is one of the most challenging and importing issues to give full play to the advantages of D2D communication. Optimal resource allocation is an important factor that needs to be addressed in D2D communication. Therefore, this paper proposes an optimization method based on the game-matching concept. The main idea is to model the optimization problem of the quality-of-experience based on user fairness and solve it through game-matching theory. Simulation results show that the proposed algorithm effectively improved the resource allocation and utilization as compared with existing algorithms.

show abstract

Section: Introductionmentioning

confidence: 99%

“…Among them, algorithms based on game theory are widely used. For example, non-cooperative game theory is often used to solve the resource allocation problem in D2D communication in a distributed manner [32][33][34][35][36], but the Nash equilibrium obtained from this model is unilaterally unstable. of.…”

Section: Introductionmentioning

confidence: 99%

Optimal Resource Allocation Method for Device-to-Device Communication in 5G Networks

Vu-Huu¹,

Le-Thanh²,

Nguyen-Xuan³

et al. 2022

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…In [7], the authors present a double auction method based on overlapping coalition game to solve the buyer's multiple needs and economic efficiency and other issues. In [8], the problem of spectrum sharing and interference management in ultra-dense C-RANS is modeled as a local coalition game. To obtain a stable partition, the authors also propose a distributed coalition formation algorithm.…”

Section: Introductionmentioning

confidence: 99%

Interference Management Algorithm Based on Coalitional Game for Energy-Harvesting Small Cells

Chen¹,

Zhu²,

Zhao³

2017

KSII TIIS

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For the downlink energy-harvesting small cell network, this paper proposes an interference management algorithm based on distributed coalitional game. The cooperative interference management problem of the energy-harvesting small cells is modeled as a coalitional game with transfer utility. Based on the energy harvesting strategy of the small cells, the time sharing mode of the small cells in the same coalition is determined, and an optimization model is constructed to maximize the total system rate of the energy-harvesting small cells. Using the distributed algorithm for coalition formation proposed in this paper, the stable coalition structure, optimal time sharing strategy and optimal power distribution are found to maximize the total utility of the small cell system. The performance of the proposed algorithm is discussed and analyzed finally, and it is proved that this algorithm can converge to a stable coalition structure with reasonable complexity. The simulations show that the total system rate of the proposed algorithm is superior to that of the non-cooperative algorithm in the case of dense deployment of small cells, and the proposed algorithm can converge quickly.

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“…There are some existing works which have studied resource allocation problems in 5G heterogeneous networks with convex optimization algorithm [10], greedy algorithm [9], clustering based approach [11], [12] and game based approach [13]- [15]. Among them, game based approach has been seen as one of the most important decision theoretic solutions for resource allocation in 5G communication system due to the distributed and autonomous decision process.…”

Section: Introductionmentioning

confidence: 99%

QoE-based Distributed Multichannel Allocation in 5G Heterogeneous Cellular Networks: A Matching-coalitional Game Solution

et al. 2016

IEEE Access

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We investigate the problem of multichannel allocation for small-cell users (SUs) in 5G heterogeneous cellular networks by taking users' quality of experience (QoE) into account. In most existing channel allocation approaches, they are assumed that each user can only transmit on one channel, and the optimization goal is the network throughput without considering users' QoE demands. Moreover, the individual QoE losses of macro-cell users (MUs), which are caused by the cross-tiered interference, are not considered. In this paper, considering SUs' QoE demands and the individual QoE losses of MUs, we propose a joint matching-coalitional game theoretical scheme to solve such a QoE-based multichannel allocation problem with individual cross-tiered interference constraint in each channel. Concretely, according to the different interference and competition relationships among users, we divide the complicated problem into two subproblems, i.e., Q1: intra-cell channel allocation for SUs, and Q2: inter-cell channel allocation for smallcell base stations. We formulate the intra-cell channel allocation as a many-to-one selfish matching game and formulate the inter-cell channel allocation subproblem as an altruistical coalitional game separately. Then, the complicated problem can be solved based on the two proposed games iteratively. We propose a joint channel allocation algorithm for the matching-coalitional game theoretical scheme. We prove that the proposed algorithm converges to a stable channel allocation profile. Simulation results show that the proposed algorithm achieves higher global SUs' satisfaction than the smallest interference channel selection and random allocation.

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Local altruistic coalition formation game for spectrum sharing and interference management in hyper‐dense cloud‐RANs

Cited by 10 publications

References 21 publications

Optimal Resource Allocation Method for Device-to-Device Communication in 5G Networks

Optimal Resource Allocation Method for Device-to-Device Communication in 5G Networks

Interference Management Algorithm Based on Coalitional Game for Energy-Harvesting Small Cells

QoE-based Distributed Multichannel Allocation in 5G Heterogeneous Cellular Networks: A Matching-coalitional Game Solution

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