Interference pricing in 5G ultra‐dense small cell networks: a Stackelberg game approach

Wang, Zeng; Hu, Bo; Wang, Xin; Chen, Shanzhi

doi:10.1049/iet-com.2016.0116

Cited by 29 publications

(17 citation statements)

References 23 publications

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“…Thus the proposed scheme is useful for interference control. The same approach can be found in [107], but the followers are SBSs instead of the FUEs. Moreover, the channel allocation is jointly considered.…”

Section: Subchannels and Antennasmentioning

confidence: 99%

“…The aforementioned approaches, i.e., [107] and [108], assume that the channel gain information between the SBSs and their associated users is known by all SBSs. In practice, only the probability distribution of the information is typically available.…”

Section: Subchannels and Antennasmentioning

confidence: 99%

“…The issues such as interference management, power allocation, and channel allocation in [107] were also considered in [114]. However, in the considered model, the leader is the MNO instead of the MBS, and the followers are Unlicensed Users (UUs) of femtocells instead of the SBSs.…”

Section: Subchannels and Antennasmentioning

confidence: 99%

See 2 more Smart Citations

Applications of Economic and Pricing Models for Resource Management in 5G Wireless Networks: A Survey

Luong

Wang

Niyato

et al. 2019

IEEE Commun. Surv. Tutorials

100

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This paper presents a comprehensive literature review on applications of economic and pricing theory for resource management in the evolving fifth generation (5G) wireless networks. The 5G wireless networks are envisioned to overcome existing limitations of cellular networks in terms of data rate, capacity, latency, energy efficiency, spectrum efficiency, coverage, reliability, and cost per information transfer. To achieve the goals, the 5G systems will adopt emerging technologies such as massive Multiple-Input Multiple-Output (MIMO), mmWave communications, and dense Heterogeneous Networks (HetNets). However, 5G involves multiple entities and stakeholders that may have different objectives, e.g., high data rate, low latency, utility maximization, and revenue/profit maximization. This poses a number of challenges to resource management designs of 5G. While the traditional solutions may neither efficient nor applicable, economic and pricing models have been recently developed and adopted as useful tools to achieve the objectives. In this paper, we review economic and pricing approaches proposed to address resource management issues in the 5G wireless networks including user association, spectrum allocation, and interference and power management. Furthermore, we present applications of economic and pricing models for wireless caching and mobile data offloading. Finally, we highlight important challenges, open issues and future research directions of applying economic and pricing models to the 5G wireless networks.architecture and functionality needs of 5G. Horizon 2020 [2], the biggest EU Research and Innovation programme, provides funding for the 5G-Public Private Partnership (5G-PPP) to deliver solutions, architectures, technologies and standards for the ubiquitous 5G communications infrastructures.The primary technologies proposed for 5G are [3] massive Multiple-Input Multiple-Output (MIMO), dense Heterogeneous Networks (HetNets), mmWave communication, fullduplex communication, Device-to-Device (D2D) communication, energy-aware communication and energy harvesting, Cloud-Based Radio Access Networks (C-RANs), the virtualization of network resources, and so on. Compared to 4G cellular networks, 5G is expected to [3] (i) improve at least 1000 times of throughput, (ii) support higher network densification, (iii) reduce significantly latency, (iv) improve energy efficiency, and (vi) support a high density of mobile broadband users, D2D, ultra reliable, and massive Machine-Type-Communications (MTC).However, the adoption of the emerging technologies introduces challenges for the radio resource management such as user association, spectrum allocation, interference and power management. The reasons are (i) the heterogeneity and dense deployment of wireless devices, (ii) the heterogeneous radio resources, (iii) the coverage and traffic load imbalance of Base Stations (BSs), (iv) the high frequency of handovers, (v) the constraints of the fronthaul and backhaul capacities, and (vi) a large number of users and stakeholders wi...

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Section: Subchannels and Antennasmentioning

confidence: 99%

Section: Subchannels and Antennasmentioning

confidence: 99%

See 1 more Smart Citation

Applications of Economic and Pricing Models for Resource Management in 5G Wireless Networks: A Survey

Luong

Wang

Niyato

et al. 2019

IEEE Commun. Surv. Tutorials

100

View full text Add to dashboard Cite

show abstract

“…With the advancement of massive multiple-input multiple-output [4] and millimeter wave communication technologies, small cells were suggested to be densely deployed in all cellular network deployment scenarios [5]. So, the ultradense HCN, which has a much higher SBS density than ever, was viewed as one of the most promising paradigms to meet the 1000x wireless traffic volume increment in the next decade [6][7][8][9][10][11]. However, along with the increase of SBS density, the energy consumption of ultradense HCNs will inevitably increase [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Stochastic Geometry Analysis of Downlink Spectral and Energy Efficiency in Ultradense Heterogeneous Cellular Networks

Lei

Chen

Zhao

2018

Mobile Information Systems

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The energy efficiency (EE) is a key metric of ultradense heterogeneous cellular networks (HCNs). Earlier works on the EE analysis of ultradense HCNs by using the stochastic geometry tool only focused on the impact of the base station density ratio and ignored the function of different tiers. In this paper, a two-tier ultradense HCN with small-cell base stations (SBSs) and user equipments (UEs) densely deployed in a traditional macrocell network is considered. Firstly, the performance of the ultradense HCN in terms of the association probability, average link spectral efficiency (SE), average downlink throughput, and average EE is theoretically analyzed by using the stochastic geometry tool. Then, the problem of maximizing the average EE while meeting minimum requirements of the average link SE and average downlink throughput experienced by UEs in macrocell and small-cell tiers is formulated. As it is difficult to obtain the explicit expression of average EE, impacts of the SBS density ratio and signal-to-interference-plus-noise ratio (SINR) threshold on the network performance are investigated through numerical simulations. Simulation results validate the accuracy of theoretical results and demonstrate that the maximum value of average EE can be achieved by optimizing the SBS density ratio and the SINR threshold.

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“…[9] studied the performance of a power control algorithm based on Stackelberg Gaming under incomplete channel state information. Authors in [10] also utilize a Stackelberg Gaming model and a penalty price to set up an interference management strategy in ultra-dense network. [11] proposed a set of joint solutions for throughput promotion in DenseNet, which consists of femtocell clustering, resource allocation and power allocation.…”

Section: Introductionmentioning

confidence: 99%

An Iterative Power Allocation Algorithm Aimed at Maximization of System Capacity in Two-Tier Cellular Network

Shi¹,

Song²,

Dong³

et al. 2017

dtcse

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Abstract. To fulfill the urgent requirement for ubiquitous information exchange, the infrastructure of the next-generation mobile system is developing toward a densely distributed cellular network with multiple tiers of base stations and access technologies serving users with different mobility styles and bandwidth demands. Therefore, the need for an advanced power control and interference mitigation strategy is even more prominent. This paper proposes an iterative power allocation algorithm for mobile users within a two-tier mobile network infrastructure. The algorithm is based on Newton's method and is aimed at maximizing system capacity of the whole system. Simulation results prove that, compared to the traditional power control scheme, the proposed scheme remarkably improves utilization of latent system capacity and effectively reduces user power consumptions, and the algorithm possesses a favorable performance of convergence.

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Interference pricing in 5G ultra‐dense small cell networks: a Stackelberg game approach

Cited by 29 publications

References 23 publications

Applications of Economic and Pricing Models for Resource Management in 5G Wireless Networks: A Survey

Applications of Economic and Pricing Models for Resource Management in 5G Wireless Networks: A Survey

Stochastic Geometry Analysis of Downlink Spectral and Energy Efficiency in Ultradense Heterogeneous Cellular Networks

An Iterative Power Allocation Algorithm Aimed at Maximization of System Capacity in Two-Tier Cellular Network

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