Femtocell Access Strategies in Heterogeneous Networks using a Game Theoretical Framework

Lin, Jia-Shi; Feng, Kai-Ten

doi:10.1109/twc.2014.011514.121668

Cited by 31 publications

(21 citation statements)

References 24 publications

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“…Other problems that have been formulated in terms of potential games are found in routing [9], [97], [156], [157], [186], [203], BS/AP selection [98], [99], [112], [161], [172], cooperative transmissions [4], [139], secrecy rate maximization [11], code design for radar [146], broadcasting [35], spectrum market [87], network coding [115], [147], [148], data cashing [94], social networks [40], computation offloading [42], localization [79], and demand-side management in smart grids [77], [183]. …”

Section: Discussionmentioning

confidence: 99%

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

Yamamoto

2015

IEICE Trans. Commun.

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SUMMARY Potential games form a class of non-cooperative games where the convergent of unilateral improvement dynamics is guaranteed in many practical cases. The potential game approach has been applied to a wide range of wireless network problems, particularly to a variety of channel assignment problems. In this paper, the properties of potential games are introduced, and games in wireless networks that have been proven to be potential games are comprehensively discussed. key words: potential game, game theory, radio resource management, channel assignment, transmission power control IntroductionThe broadcast nature of wireless transmissions causes cochannel interference and channel contention, which can be viewed as interactions among transceivers. Interactions among multiple decision makers can be formulated and analyzed using a branch of applied mathematics called game theory [61], [131]. Game-theoretic approaches have been applied to a wide range of wireless communication technologies, including transmission power control for code division multiple access (CDMA) cellular systems [153] and cognitive radios [132]. For a summary of game-theoretic approaches to wireless networks, we refer the interested reader to [68] [189].In this paper, we focus on potential games [126], which form a class of strategic form games with the following desirable properties:• The existence of a Nash equilibrium in potential games is guaranteed in many practical situations [126] (Theorems 1 and 2 in this paper), but is not guaranteed for general strategic form games. Example 2 in Sect. 2. We provide an overview of problems in wireless networks that can be formulated in terms of potential games. We also clarify the relations among games, and provide simpler proofs of some known results. Problem-specific learning algorithms [92], [168] are beyond the scope of this paper.The remainder of this paper is organized as follows: In Sect. 2, 3, and 4, we introduce strategic form games, potential games, and learning algorithms, respectively. We then discuss various potential games in Sects. 5 to 18, as shown in Table 1. Finally, we provide a few concluding remarks in Sect. 19.The notation used here is shown in Table 2. Unless the context indicates otherwise, sets of strategies are denoted by calligraphic uppercase letters, e.g., A i , strategies are denoted by lowercase letters, e.g., a i ∈ A i , and tuples of strategies are denoted by boldface lowercase letters, e.g., a. Note that a i is a scalar variable when A i is a set of scalars or indices, a i is a vector variable when A i is a set of vectors, and a i is a set variable when A i is a collection of sets.We use R to denote the set of real numbers, R + to denote the set of nonnegative real numbers, R ++ to denote the set of positive real numbers, and C to denote the set of complex numbers. The cardinality of set A is denoted by |A|. The power set of A is denoted by 2 A . Finally, ½condition is the indicator function, which is one when condition is true and is zero otherwise.We treat many sy...

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Section: Discussionmentioning

confidence: 99%

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

Yamamoto

2015

IEICE Trans. Commun.

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“…Unlike the statistical schemes, in the adaptive scheme, switched off BSs can also be turned on in real-time according to the environmental changes, e.g., sudden increase of traffic load. In general, the adaptive on-off power control scheme is applied to femto BSs (FBSs) whose transmission range is short [23][24][25][26]. Note that due to its possibility to improve the performance of MCS, the FBS has been studied extensively in recent days, especially in the view of resource allocation [24][25][26].…”

Section: On-off Power Control Schemes In Mcsmentioning

confidence: 99%

Energy-Efficient On–Off Power Control of Femto-Cell Base Stations for Cooperative Cellular Networks

Lee

Jung

2016

Applied Sciences

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Improving energy efficiency (EE) of mobile communication systems (MCSs) has been considered a key aim in recent years, and has been the subject of intense research interest. One of the simplest yet most powerful ways to increase the EE is to turn off redundant communication entities whose operation does not greatly affect the overall performance of the MCS. In this paper, we propose a novel on-off power control scheme for femto-cell base stations (FBSs) considering cooperative transmission in which multiple FBSs collaborate on the same data transmission. In the proposed scheme, the operation of the redundant FBSs is halted in an adaptive manner. For the proper determination of redundant FBSs with low computational complexity, we propose using the level of contribution (LOC), which specifies the importance of a given FBS in the cooperative transmission. Redundant FBSs are chosen based on their LOC value, and these FBSs are turned off in order to reduce the power consumption of MCSs while minimizing the degradation of the overall throughput of cooperative transmissions. The performance of the proposed scheme is verified through extensive simulations, which shows that near-optimal performance can be achieved without excessive computations.

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“…Then, flows perceive that MUs are still. This allows us to decompose the model defined by (17) in the previous section into two independent models. We refer to them as the fast time scale subsystem (FTSS) and the slow time scale subsystem (STSS).…”

Section: Decompositionmentioning

confidence: 99%

“…The level of interference perceived by SUs is influenced by the number of MUs allowed to connect to the SAP. Hence, besides using power control or spectrum management, the interference can also be managed by allowing strong MUs interferers to become associated to the SAP [16], [17].…”

Section: Introductionmentioning

confidence: 99%

“…the SUs, have access to the small cell (MUs cannot connect to the small cell); ii) open access, all users can make use of any small cell (in that sense, there are no differences between SUs and MUs); and iii) hybrid access, a limited amount of the small cell resources are available to MUs, while SUs have no restrictions. The hybrid access mode is proposed as a trade-off between open and closed access modes [18], [17], [19]. Depending on the system resources, users traffic profile, number of MUs and their mobility pattern, number of SUs, degree of interference and small cell backhaul capacity constraints, the RP in the hybrid access mode has to be carefully configured in order to guarantee a certain degree of QoS to the SUs.…”

Section: Introductionmentioning

confidence: 99%

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Performance Analysis of Two-Tier Wireless Networks With Dynamic Traffic, Backhaul Constraints, and Terminal Mobility

Bernal-Mor

Pla

Martínez-Bauset

et al. 2016

IEEE Trans. Veh. Technol.

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Bernal Mor, E.; Pla, V.; Martínez Bauset, J.; Luis Guijarro (2016) Abstract-During the last years, mobile cellular networks have witnessed an enormous growth in the carried data-traffic volume. The current networks' features are not enough to cope with this traffic trend and the concept of small cells has emerged as a feasible solution to increase the network capacity. However, the deployment of small cells introduces several technical challenges such as the cross-tier interference between the macrocell and the small cells, or the use of the subscriber land-line to send the backhaul data. In this paper, an analytical model is proposed to study the impact that the user traffic dynamics, the mobility of macrocell users, the scheme chosen to associate macrocell users to the small cells and the changing available capacity of the small cells backhaul have on the system performance. To make the solution of the model computationally feasible, we exploit the time-scale decomposition approach. In most practical scenarios, the arrival and departure rates of traffic flows are much larger than the rate of events associated with the mobility of macrocell users. Then, flows perceive that macrocell users are still. This model is applied to identify the scheme to associate macrocell users to the small cells which maximizes the performance perceived by the small cell users.

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Femtocell Access Strategies in Heterogeneous Networks using a Game Theoretical Framework

Cited by 31 publications

References 24 publications

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

Energy-Efficient On–Off Power Control of Femto-Cell Base Stations for Cooperative Cellular Networks

Performance Analysis of Two-Tier Wireless Networks With Dynamic Traffic, Backhaul Constraints, and Terminal Mobility

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