Joint Power Coordination for Spectral-and-Energy Efficiency in Heterogeneous Small Cell Networks: A Bargaining Game-Theoretic Perspective

Yang, Chungang; Li, Jiandong; Anpalagan, Alagan; Guizani, Mohsen

doi:10.1109/twc.2015.2489215

Cited by 63 publications

(43 citation statements)

References 37 publications

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“…User scheduling and almost blank resource block allocation is proposed in [18]. The authors of [21] focus on a game theoretical approach for joint spectral and energy efficiency, and in [22] transmit power allocation and user scheduling is considered.…”

Section: A Background and Related Workmentioning

confidence: 99%

“…Singularities in own cell utilities may occur when some of the power variables p i vanish, or when precoding happens towards a null-space of a user, which is possible if rank H (m) i,k < N T . These singularities can be avoided by redefining P of (20) and Q of (21). When proving the convergence of NLGS, we shall need convexity of the feasible sets.…”

Section: Appendix: Convergence Proofsmentioning

confidence: 99%

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Self-Organizing Algorithms for Interference Coordination in Small Cell Networks

Ahmed

Dowhuszko

Tirkkonen

2017

IEEE Trans. Veh. Technol.

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This paper discusses novel joint (intra-cell and inter-cell) resource allocation algorithms for self-organized interference coordination in multi-carrier multiple-input multipleoutput (MIMO) small cell networks (SCNs). The proposed algorithms enable interference coordination autonomously, over multiple degrees of freedom, such as base station transmit powers, transmit precoders, and user scheduling weights. A generic α-fair utility maximization framework is considered to analyze performance-fairness trade-off, and to quantify the gains achievable in interference-limited networks. The proposed scheme involves limited inter-base station signaling in the form of two step (power and precoder) pricing. Based on this decentralized coordination, autonomous power and precoder update decision rules are considered, leading to algorithms with different characteristics in terms of user data rates, signaling load, and convergence speed. Simulation results in a practical setting show that the proposed pricing-based self-organization can achieve up to 100% improvement in cell-edge data rates, when compared to baseline optimization strategies. Furthermore, the convergence of the proposed algorithms is also proved theoretically.Index Terms-Self-organizing networks, autonomous algorithms, interference coordination, resource allocation, multipleinput multiple-output, co-channel interference, small cell networks, network utility maximization.

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Section: A Background and Related Workmentioning

confidence: 99%

Section: Appendix: Convergence Proofsmentioning

confidence: 99%

Self-Organizing Algorithms for Interference Coordination in Small Cell Networks

Ahmed

Dowhuszko

Tirkkonen

2017

IEEE Trans. Veh. Technol.

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“…Furthermore, numbers of solutions and strategies from other areas in communication networks can inspire the scholars to solve the caching difficulties [24][25][26][27][28][29][30]. In this paper, we focus on the IP-based caching architecture which is a research hot point in recent years [31][32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

Caching Efficiency Enhancement at Wireless Edges with Concerns on User’s Quality of Experience

Lam

Wang

et al. 2018

Wireless Communications and Mobile Computing

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Content caching is a promising approach to enhancing bandwidth utilization and minimizing delivery delay for new-generation Internet applications. The design of content caching is based on the principles that popular contents are cached at appropriate network edges in order to reduce transmission delay and avoid backhaul bottleneck. In this paper, we propose a cooperative caching replacement and efficiency optimization scheme for IP-based wireless networks. Wireless edges are designed to establish a one-hop scope of caching information table for caching replacement in cases when there is not enough cache resource available within its own space. During the course, after receiving the caching request, every caching node should determine the weight of the required contents and provide a response according to the availability of its own caching space. Furthermore, to increase the caching efficiency from a practical perspective, we introduce the concept of quality of user experience (QoE) and try to properly allocate the cache resource of the whole networks to better satisfy user demands. Different caching allocation strategies are devised to be adopted to enhance user QoE in various circumstances. Numerical results are further provided to justify the performance improvement of our proposal from various aspects.

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“…Accordingly, the deployment of heterogeneous networks (HetNets) has been recognized as an essential technology to deal with the aforementioned issues for next-generation wireless networks. [1][2][3][4] Therefore, cellular networks are gravitating toward increasing heterogeneity, especially through the deployment of small-cell base stations (SBSs). 5 The examples of SBSs are microcells, picocells, and femtocells, which differ primarily in maximum transmit power, coverage range, backhaul, ease of deployment, and cost of installation and maintenance.…”

Section: Introductionmentioning

confidence: 99%

A distributed learning–based user association for heterogeneous networks

Arani

Omidi

Mehbodniya

et al. 2017

Trans Emerging Tel Tech

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The coexistence of various base stations (BSs) in heterogeneous networks (HetNets) has emerged as a promising approach to meet the ever increasing network capacity. In these networks, one of the important issues is the problem of associating user equipments (UEs) to BSs. In this paper, we investigate the UE association (UEA) problem in heterogeneous networks and propose a load-aware UEA mechanism based on the BSs' estimated load and signal-to-interference-and-noise ratio. The proposed mechanism can capture the trade-off between UE's quality-of-service requirement and delay. We model this strategic UE-BS association as a noncooperative game. To solve the game, we develop a fully distributed algorithm inspired by machine learning techniques, whereby the proposed UEA scheme corresponds to a Markov chain.In the proposed scheme, each UE senses its environment and decides which BS to select based on the satisfaction technique. Therefore, it achieves a high level of satisfaction for UEs. Furthermore, use of historical information helps UEs select BSs with better long-term performance. Simulation results show that the proposed mechanism reduces fractional transfer time and the number of unsatisfied UEs, respectively, up to about 46% and 52.3% and improves BS throughput up to about 15.4% compared to a benchmark algorithm that is based on the received signal strength and the BS's estimated load.

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Joint Power Coordination for Spectral-and-Energy Efficiency in Heterogeneous Small Cell Networks: A Bargaining Game-Theoretic Perspective

Cited by 63 publications

References 37 publications

Self-Organizing Algorithms for Interference Coordination in Small Cell Networks

Self-Organizing Algorithms for Interference Coordination in Small Cell Networks

Caching Efficiency Enhancement at Wireless Edges with Concerns on User’s Quality of Experience

A distributed learning–based user association for heterogeneous networks

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