Distributed Power Allocation for Wireless Sensor Network Localization: A Potential Game Approach

Ke, Mingxing; Li, Ding; Tian, Shengfeng; Zhang, Yuli; Tong, Kaixiang; Xu, Yuhua

doi:10.3390/s18051480

Cited by 7 publications

(3 citation statements)

References 35 publications

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“…The nature quality of Potential Game (PG): the motivation of all players to change their strategies can be expressed as a global function [33], which could exactly meet this need. Some studies have applied the potential game to solve the spatial spectrum access problem [34] and power allocation problem [35]. We can also find this game method widely used in resource allocation, especially cooperating with other methods in some complex situations.…”

Section: Related Workmentioning

confidence: 99%

A QoE-Oriented Uplink Allocation for Multi-UAV Video Streaming

Xie

Tian

2019

Sensors

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Video streaming has become a kind of main information carried by Unmanned Aerial Vehicles (UAVs). Unlike single transmission, when a cluster of UAVs execute the real-time video shooting and uploading mission, the insufficiency of wireless channel resources will lead to bandwidth competition among them and the competition will bring bad watching experience to the audience. Therefore, how to allocate uplink bandwidth reasonably in the cluster has become a crucial problem. In this paper, an intelligent and distributed allocation mechanism is designed for improving users’ video viewing satisfication. Each UAV in a cluster can independently adjust and select its video encoding rate so as to achieve flexible uplink allocation. This choice relies neither on the existence of the central node, nor on the large amount of information interaction between UAVs. Firstly, in order to distinguish video service from ordinary data, a utility function for the overall Quality of Experience (QoE) is proposed. Then, a potential game model is built around the problem. By a distributed self-learning algorithm with low complexity, all UAVs can iteratively update their own bandwidth strategy in a short time until equilibria, thus achieving the total quality optimization of all videos. Numeric simulation results indicate, after a few iterations, that the algorithm converges to a set of correlation equilibria. This mechanism not only solves the uplink allocation problem of video streaming in UAV cluster, but also guarantees the wireless resource providers in distinguishing and ensuring network service quality.

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Section: Related Workmentioning

confidence: 99%

A QoE-Oriented Uplink Allocation for Multi-UAV Video Streaming

Xie

Tian

2019

Sensors

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“…To select the most informative agent‐agent links, the benefit from the coalition can be employed by the localisation accuracy and the cost can be reflected by the number of links. Therefore, similar with [33, 34], the objective of each coalition is to minimise the SPEB of each agent node penalised by the number of links in the coalition. Based on above information, we define the utility function of each coalition as

\begin{matrix} true \\ right U^{false(k false)} = - true{P_{m}^{false(k false)} + \sum_{n \in C_{m}} P_{n}^{false(k false)} true} - β \cdot true{L_{m}^{false(k false)} + \sum_{n \in C_{m}} L_{n}^{false(k false)} true} . \end{matrix}

The first term in the right side characterises the localisation information of agent nodes in the coalition, which represents the benefit of agent node m obtained from the coalition

C_{m}

.…”

Section: Cooperative Approaches and Problem Formulationmentioning

confidence: 99%

“…To select the most informative agent-agent links, the benefit from the coalition can be employed by the localisation accuracy and the cost can be reflected by the number of links. Therefore, similar with [33,34], the objective of each coalition is to minimise the SPEB of each agent node penalised by the number of links in the coalition. Based on above information, we define the utility function of each coalition as…”

Section: Problem Formulationmentioning

confidence: 99%

An EKF based overlapping coalition formation game for cooperative wireless network navigation

Tian

Tong

et al. 2021

IET Communications

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The problem of efficient link selections for cooperative navigation is investigated in dynamic wireless networks, using an extended Kalman filter based overlapping coalition formation (OCF) game approach. Due to the densely deployment of nodes without proper link selections, the conventional cooperative navigation approaches usually yield high time‐frequency resources as the existing resource management methods only work properly in static localisation systems. A new link selection mechanism which is reliable with limited resources in dynamic positioning scenarios is proposed. The varying topological structure and states of every node will be taken into consideration while each node abandons a considerable number of unnecessary links. Firstly, the state of every mobile node will be estimated in real‐time. Then a selection criterion is applied to determine whether nodes are well navigated. If the criterion is satisfied, an OCF game will be employed to construct the effective link selection. Otherwise, a re‐link mechanism will be used to obtain precise state information of each node. Numerical results show that the cooperative navigation algorithm can significantly improve the positioning accuracy and the proposed OCF game approach can build a cooperative network with limited number of links at the cost of appropriate performance degradation.

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Joint Node Selection and Power Allocation for Cooperative Positioning Based on Bidding Auction in VANET

et al. 2023

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Due to buildings blocking GPS and Wi-Fi signals, traditional techniques can’t offer the user’s required positioning accuracy in resource-constrained underground parking, but the cooperation of agent nodes can provide the exact localization information to improve the positioning accuracy. However, some well-localized agents may not be willing to sacrifice additional power to improve the others’ positioning accuracy. To encourage cooperation among nodes and allocate transmission power reasonably, this paper proposes a bidding-auction-based cooperative localization (BACL) algorithm to improve the positioning accuracy of agent nodes by joint node selection incentive and power allocation strategy. Firstly, the contribution of channel parameters and prior localization information of agent nodes for positioning accuracy are quantified and an incentive mechanism of cooperative localization from an economic perspective is proposed. Secondly, a virtual currency incentive rule is developed to compensate agent nodes of cooperative localization reasonably due to the consumption of energy for transmitting their location information. Finally, the simulation results have shown that the proposed BACL algorithm has excellent performance in terms of localization accuracy in resource-constrained scenarios. Compared with the full-power cooperative localization (FPCL) and non-cooperative localization (NCL) algorithms, the proposed BACL algorithm improved the positioning accuracy by 10% and 65%, respectively. Meanwhile, compared with the FPCL algorithm, the proposed algorithm reduced resource consumption by 50%.

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Distributed Power Allocation for Wireless Sensor Network Localization: A Potential Game Approach

Cited by 7 publications

References 35 publications

A QoE-Oriented Uplink Allocation for Multi-UAV Video Streaming

A QoE-Oriented Uplink Allocation for Multi-UAV Video Streaming

An EKF based overlapping coalition formation game for cooperative wireless network navigation

Joint Node Selection and Power Allocation for Cooperative Positioning Based on Bidding Auction in VANET

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