Exploring Channel Diversity in HF Communication Systems： A Matching-Potential Game Approach

This paper investigates the channel diversity problem in high frequency(HF) communication systems. Due to the limited HF spectrum resources, a HF communication system with shared channels is considered, where each user equipment(UE) has individual communication demand. In order to maximize the communication probability of the whole system, a matching-potential game framework is designed. In detail, the channel diversity problem is decomposed into two sub-problems. One is channel-transmitter matching problem, which can be formulated as a many-to-one matching game. The other is the transmitter allocation problem which decides the transmission object that each transmitter communicates with under channel-transmitter matching result, and this sub-problem can be modeled as a potential game. A multiple round stable matching algorithm(MRSMA) is proposed, which obtains a stable matching result for the first sub-problem, and a distributed BR-based transmitter allocation algorithm(DBRTAA) is designed to reach Nash Equilibrium(NE) of the second sub-problem. Simulation results verify the effectiveness and superiority of the proposed method.

Matching mechanism in global public goods games:a case of climate protection

In the setting of dealing with climate change, this article designs a matching mechanism for global public goods provision with the aggregative game approach. Given endowment and the technology of each country, we propose the conditions under which the matching mechanism is able to guarantee full participation and Pareto efficient provision, respectively, in the cases with certain and uncertain preference information. These conditions cannot only be adopted in international negotiation and cooperation, but also refines the theory of matching game. In comparative static analyses, we discover that: First, changes of initial stock of climate goods produce a wealth effect and the crowd-out effect is less than 1. Second, climate tax policies affect the supply and welfare of each country only when they produce wealth effects, and if tax revenue is transferred into climate goods with more advanced technology, they will produce positive wealth effects. Third, modifying matching plans dynamically and appropriately can urge countries to improve technology, and especially given a Pareto optimal mechanism, adjusting the matching plan to keep marginal rates of transformation unchanged as technology changes is still able to ensure full participation and efficient supply of climate goods.

Resource Allocation Strategy Based on Matching Game

With the development of satellite communication technology,the traditional resource allocation strategies are difficult to meet the requirements of resource utilization efficiency.In order to solve the optimization problem of resource allocation for multi-layer satellite networks in multi-user scenarios,we propose a new resource allocation scheme based on the many-to-many matching game.This scheme is different from the traditional resource allocation strategies that just consider a trade-off between the new call blocking probability and the handover call failure probability.Based on different preference lists among different layers of medium earth orbit(MEO) satellites,low earth orbit(LEO) satellites,base stations and users,we propose the corresponding algorithms from the perspective of quality of experience(QoE).The simulation results show that the many-to-many matching game scheme can effectively improve both the resource utilization efficiency and QoE,compared with the one-to-one and many-to-one matching algorithms.

A Caching Strategy Based on Many-to-Many Matching Game in D2D Networks

Wireless edge caching has been proposed to reduce data traffic congestion in backhaul links, and it is being envisioned as one of the key components of next-generation wireless networks. This paper focuses on the influences of different caching strategies in Device-to-Device(D2D) networks. We model the D2D User Equipments(DUEs) as the Gauss determinantal point process considering the repulsion between DUEs, as well as the caching replacement process as a many-to-many matching game. By analyzing existing caching placement strategies, a new caching strategy is proposed, which represents the preference list of DUEs as the ratio of content popularity to cached probability. There are two distinct features in the proposed caching strategy.(1) It can cache other contents besides high popularity contents.(2) It can improve the cache hit ratio and reduce the latency compared with three caching placement strategies: Least Recently Used(LRU), Equal Probability Random Cache(EPRC), and the Most Popular Content Cache(MPC). Meanwhile, we analyze the effect of caching on the system performance in terms of different content popularity factors and cache capacity. Simulation results show that our proposed caching strategy is superior to the three other comparison strategies and can significantly improve the cache hit ratio and reduce the latency.

Optimization of energy exchange in microgrid networks: a coalition formation approach

In this paper, we elaborate a new strategy based on cooperative game theory models to encourage and manage the interactions in a MicroGrid network. The proposed strategy optimizes the cooperation and the energy exchange in a distributed μGrid network. The strategy consists of a two stage algorithm: Coalition formation algorithm which was specifically created to approximate the optimal set of coalitions that return considerable savings. And the Matching game to manage the energy exchange inside each coalition. The performance of our strategy was verified through simulations. These latter show that the losses can be considerably decreased by the use of the proposed strategy: the rate of the loss reduction can reach up to 20% if the two stages are applied on the network. Moreover, the strategy proved to have a fast convergence which makes it operational for real implemented networks.