Joint Access Point Selection and Power Allocation for Uplink Wireless Networks

Mei, Hong; García, Alfredo; Barrera, Jorge; Wilson, Stephen G.

doi:10.1109/tsp.2013.2253772

Cited by 18 publications

(16 citation statements)

References 29 publications

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“…In addition to AP selection, [21] considers the hotspot problem and aims to ensure high resource availability to combat any unexpected traffic growth in the network. In [22], the joint AP selection and power allocation problem is considered in a multicarrier wireless network with multiple APs and mobile users. The APs operate on nonoverlapping spectrum bands, each of which is divided into parallel channels.…”

Section: Related Workmentioning

confidence: 99%

A Framework for Dynamic Network Architecture and Topology Optimization

Shafigh

Lorenzo

Glisic

et al. 2016

IEEE/ACM Trans. Networking

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Abstract-A new paradigm in wireless network access is presented and analyzed. In this concept, certain classes of wireless terminals can be turned temporarily into an access point (AP) anytime while connected to the Internet. This creates a dynamic network architecture (DNA) since the number and location of these APs vary in time. In this paper, we present a framework to optimize different aspects of this architecture. First, the dynamic AP association problem is addressed with the aim to optimize the network by choosing the most convenient APs to provide the quality-of-service (QoS) levels demanded by the users with the minimum cost. Then, an economic model is developed to compensate the users for serving as APs and, thus, augmenting the network resources. The users' security investment is also taken into account in the AP selection. A preclustering process of the DNA is proposed to keep the optimization process feasible in a high dense network. To dynamically reconfigure the optimum topology and adjust it to the traffic variations, a new specific encoding of genetic algorithm (GA) is presented. Numerical results show that GA can provide the optimum topology up to two orders of magnitude faster than exhaustive search for network clusters, and the improvement significantly increases with the cluster size.

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Section: Related Workmentioning

confidence: 99%

A Framework for Dynamic Network Architecture and Topology Optimization

Shafigh

Lorenzo

Glisic

et al. 2016

IEEE/ACM Trans. Networking

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“…Apart from the classical approach, in which the AP is selected based on signal strength, different studies have proposed other metrics to achieve a more efficient AP association, such as the packet error rate, the throughput and the bandwidth per user [30]- [32]. Other approaches, such as [33], consider the load balancing problem under max-min fairness considerations, whereas in [34]- [37], game theory concepts are considered for the association of UEs to APs. However, none of the above works assumes the scenario in which the APs can be used to relay traffic from the UEs to the cellular infrastructure, as considered in this work.…”

Section: Related Workmentioning

confidence: 99%

Power-Efficient Resource Allocation in a Heterogeneous Network With Cellular and D2D Capabilities

Perez-Romero

Sánchez–González

Agustí

et al. 2016

IEEE Trans. Veh. Technol.

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Abstract-This paper focuses on a heterogeneous scenario in which cellular and wireless local area technologies coexist and in which mobile devices are enabled with device-to-device communication capabilities. In this context, this paper assumes a network architecture in which a given user equipment (UE) can receive mobile service either by connecting directly to a cellular base station or by connecting through another UE that acts as an access point and relays the traffic from a cellular base station. The paper investigates the optimization of the connectivity of different UEs with the target to minimize the total transmission power. An optimization framework is presented, and a distributed strategy based on Q-learning and softmax decision making is proposed as a means to solve the considered problem with reduced complexity. The proposed strategy is evaluated under different conditions, and it is shown that the strategy achieves a performance very close to the optimum. Moreover, significant transmission power reductions of approximately 40% are obtained with respect to the classical approach, in which all UEs are connected to the cellular infrastructure. For multi-cell scenarios, in which the optimum solution cannot be easily known a priori, the proposed approach is compared against a centralized genetic algorithm. The proposed approach achieves similar performance in terms of total transmitted power, while exhibiting much lower computational requirements.

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“…9 because a zero transmission power level means that the relevant channel has not been assigned [145]. Note that [144] also discussed BS selection, and further discussion can be found in [75]. The joint transmission power and bandwidth assignment problem for relay networks was discussed in [3].…”

Section: Multi-channel Systemsmentioning

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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Joint Access Point Selection and Power Allocation for Uplink Wireless Networks

Cited by 18 publications

References 29 publications

A Framework for Dynamic Network Architecture and Topology Optimization

A Framework for Dynamic Network Architecture and Topology Optimization

Power-Efficient Resource Allocation in a Heterogeneous Network With Cellular and D2D Capabilities

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

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