Competition of Wireless Providers for Atomic Users

Huang

IEEE Trans. on Mobile Comput.

2021

Self Cite

Wireless power transfer (WPT) technology enables a cost-effective and sustainable energy supply in wireless networks. However, the broadcast nature of wireless signals makes them non-excludable public goods, which leads to potential free-riders among energy receivers. In this study, we formulate the wireless power provision problem as a public goods provision problem, aiming to maximize the social welfare of a system of an energy transmitter (ET) and all the energy users (EUs), while considering their private information and self-interested behaviors. We propose a two-phase all-or-none scheme involving a low-complexity Power And Taxation (PAT) mechanism, which ensures voluntary participation, truthfulness, budget balance, and social optimality at every Nash equilibrium (NE). We propose a distributed PAT (D-PAT) algorithm to reach an NE, and prove its convergence by connecting the structure of NEs and that of the optimal solution to a related optimization problem. We further extend the analysis to a multi-channel system, which brings a further challenge due to the non-strict concavity of the agents' payoffs. We propose a Multi-Channel PAT (M-PAT) mechanism and a distributed M-PAT (D-MPAT) algorithm to address the challenge. Simulation results show that, our design is most beneficial when there are more EUs with more homogeneous channel gains.

Section: Challengesmentioning

confidence: 99%

Section: Challengesmentioning

confidence: 99%

See 1 more Smart Citation

Wireless Power Transfer with Information Asymmetry: A Public Goods Perspective

Huang

IEEE Trans. on Mobile Comput.

2021

Self Cite

2015 International Conference on Applied Research in Computer Science and Engineering (ICAR)

“…Authors reveal the advantage for the primary operator to play before the secondary operator, particularly in a high-traffic regime. Furthermore, a two-stage multi-leader-follower game is used to model the interaction of a number of wireless providers and a group of atomic users in [10]. The providers announce the wireless resource prices in a first stage and the users announce their demand for the resource in the second stage.…”

Section: Background and Related Workmentioning

confidence: 99%

Comparison between access selection algorithms in multi-operator wireless networks

Farhat¹,

Samhat²,

Lahoud³

et al. 2015

International audienceIn fifth generation mobile network, Radio Access Network sharing is an attractive solution for operators to counter the traffic growth and build cost-effective networks in order to improve coverage and capacity at reasonable investments and operational costs. It consists of sharing radio access resources between two or more operators. In such multi-operator environment access selection decision is an important issue for the mobile user and his home operator which the user has contract with. In literature, the majority of access selection algorithms are based on game theory which is very complex for implementation and the decision is slower in comparison with Multiple Attributes Decision Making (MADM) methods. In this paper, we use Simple Additive Weighting (SAW) methods and Nearest Performance Handover (NPH) algorithm for the access selection in a multi-operator environment. These algorithms based on MADM were initially conceived for the selection decision in a single operator environment. In addition, we compare the performance of these algorithms with our previously proposed cost function for the access selection in a multi-operator sharing network. Performance analyses are made in terms of user blocking percentages and global achieved profit. Simulation results showed that our decision algorithm guarantee the lowest blocking probability for all operators, it prevents overloading operator's with high numbers of guest users which affect own clients acceptance. In addition, it improves global achieved profits for all cooperating operators. However, SAW methods showed better performance than NPH concerning users blocking percentages, but NPH guarantees higher profits than SAW methods for the operators with limited capacity

IEEE Trans. on Mobile Comput.

“…In general the game-theoretical modelling of wireless markets is performed either at a microscopic or at a macroscopic level: Microscopic approaches usually focus on specific technical aspects (e.g., protocol, network topology, technology) on a short spatial and temporal scale, often considering networks with a small number of base stations (BSs) and markets with a single provider [11,24,44,14,46,13,48]. The computational and scalability issues when analysing large (e.g., nation-wide) markets become prominent.…”

Section: Introductionmentioning

confidence: 99%

A Game-Theoretical Analysis of Wireless Markets Using Network Aggregation

Fortetsanakis

Dimitriou

Papadopouli

2017

New wireless access markets have emerged that are larger, more heterogeneous and diverse. Modelling such markets can be challenging due to the interplay of various business-and network-related aspects as well as the interdependencies among different entities (e.g., customers, providers). Existing models of wireless markets are either microscopic, focusing on a specific technical aspect (e.g., protocol, network topology, technology) at a fine scale or macroscopic modelling wireless markets at a large-scale, e.g., considering homogeneous user populations. In contrast to these approaches, this work develops a multi-layer game-theoretical framework, which allows providers to model users at multiple levels of detail by considering a different number of user sub-populations. It also models the mobility pattern, traffic demand, and networks of providers. A population game using Logit dynamics models the user selection of the appropriate dataplan and provider, capturing the diversity in customer profile and relaxing the assumption about the user rationality. It analytically computes the equilibriums of users and providers and numerically evaluates the performance of the market as a function of the traffic demand, the number of available dataplans, and the knowledge about customer population. Significant benefits in revenue can be achieved by a provider when it integrates more detailed information about the user population. The number of disconnected users also decreases. Moreover the availability of several dataplans further enhances the gains. The stronger the provider, the more prominent the benefits. However the benefits diminish when all the providers model the customer population at the same degree of detail due to an increased competition. The analysis highlights the development of different strategies of the providers depending on their capacity, level of knowledge about the customer population, and traffic conditions. It illustrates how a provider changes its strategy under different conditions, focusing potentially on different customer segments and also the pressure introduced by specific customer types.