Cheat-Proof Distributed Power Control in Full-Duplex Small Cell Networks: A Repeated Game With Imperfect Public Monitoring

Semasinghe, Prabodini; Hossain, Ekram

doi:10.1109/tcomm.2017.2785765

Cited by 8 publications

(4 citation statements)

References 27 publications

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“…As an application of leader-follower network aggregative game, we study the power allocation of small cell networks proposed in [6]. Consider a network consisting of N small cells, all of which underlay a macrocell with a macrocell base station (MBS).…”

Section: Simulation Resultsmentioning

confidence: 99%

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Leader–Follower Network Aggregative Game With Stochastic Agents’ Communication and Activeness

Shokri

Kebriaei

2020

IEEE Trans. Automat. Contr.

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This technical note presents a leader-follower scheme for network aggregative games. The followers and leader are selfish cost minimizing agents. The cost function of each follower is affected by strategy of leader and aggregated strategies of its neighbors through a communication graph. The leader infinitely often wakes up and receives the aggregated strategy of the followers, updates its decision value and broadcasts it to all the followers. Then, the followers apply the updated strategy of the leader into their cost functions. The establishment of information exchange between each neighboring pair of followers, and the activeness of each follower to update its decision at each iteration are both considered to be drawn from two arbitrary distributions. Moreover, a distributed algorithm based on subgradient method is proposed for updating the strategies of leader and followers. The convergence of the proposed algorithm to the unique generalized Nash equilibrium point of the game is proven in both almost sure and mean square senses.

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Section: Simulation Resultsmentioning

confidence: 99%

“…summation or weighted sum), the network game is known as network aggregative game (NAG) [3]. Many applications can be studied via this framework including, power system [4], opinion dynamics [5], communication system [6], provision of public goods [7] and criminal networks [8].…”

Section: Introductionmentioning

confidence: 99%

Leader–Follower Network Aggregative Game With Stochastic Agents’ Communication and Activeness

Shokri

Kebriaei

2020

IEEE Trans. Automat. Contr.

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“…Distributed optimization and computational game theory for large-scale multi-agent systems have been strong recent research areas in systems and control [1] with a variety of applications, e.g. in wireless communication [2], transmission networks [3], social networks [4] and smart grids [5].…”

Section: Introductionmentioning

confidence: 99%

“…Our motivation is that reaching all agents with broadcast signals may be impossible in large-scale systems, especially in geographically distributed or heterogeneously-networked systems, e.g. PEV parking lots, wireless networks [2], transportation networks [18]. On the other hand, a peer-to-peer communication network between selfish agents is typically not available or affordable, especially in engineering applications [19]- [21].…”

Section: Introductionmentioning

confidence: 99%

Multipopulation Aggregative Games:Equilibrium Seeking via Mean-Field Control and Consensus

Kebriaei

Sadati-Savadkoohi

Shokri

et al. 2021

IEEE Trans. Automat. Contr.

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In this paper, we extend the theory of deterministic mean-field/aggregative games to multi-population games. We consider a set of populations, each managed by a population coordinator (PC), of selfish agents playing a global non-cooperative game, whose cost functions are affected by an aggregate term across all agents from all populations. In particular, we impose that the agents cannot exchange information between themselves directly; instead, only a PC can gather information on its own population and exchange local aggregate information with the neighboring PCs. To seek an equilibrium of the resulting (partialinformation) game, we propose an iterative algorithm where each PC broadcasts a mean-field signal, namely, an estimate of the overall aggregative term, to its own population only. In turn, we let the local agents react with a best response and the PCs cooperate for estimating the aggregative term. Our main technical contributions are to cast the proposed scheme as a fixed-point iteration with errors, namely, the interconnection of a Krasnoselskij-Mann iteration and a linear consensus protocol, and, under a non-expansiveness condition, to show convergence towards an ε-Nash equilibrium, where ε is inversely proportional to the population size.

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Distributed generalized Nash equilibrium seeking: A singular perturbation-based approach

Lin

Chen

et al. 2022

Neurocomputing

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Cheat-Proof Distributed Power Control in Full-Duplex Small Cell Networks: A Repeated Game With Imperfect Public Monitoring

Cited by 8 publications

References 27 publications

Leader–Follower Network Aggregative Game With Stochastic Agents’ Communication and Activeness

Leader–Follower Network Aggregative Game With Stochastic Agents’ Communication and Activeness

Multipopulation Aggregative Games:Equilibrium Seeking via Mean-Field Control and Consensus

Distributed generalized Nash equilibrium seeking: A singular perturbation-based approach

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