Applications of Repeated Games in Wireless Networks: A Survey

A repeated game is an effective tool to model interactions and conflicts for players aiming to achieve their objectives in a long-term basis. Contrary to static noncooperative games that model an interaction among players in only one period, in repeated games, interactions of players repeat for multiple periods; and thus the players become aware of other players' past behaviors and their future benefits, and will adapt their behavior accordingly. In wireless networks, conflicts among wireless nodes can lead to selfish behaviors, resulting in poor network performances and detrimental individual payoffs. In this paper, we survey the applications of repeated games in different wireless networks. The main goal is to demonstrate the use of repeated games to encourage wireless nodes to cooperate, thereby improving network performances and avoiding network disruption due to selfish behaviors. Furthermore, various problems in wireless networks and variations of repeated game models together with the corresponding solutions are discussed in this survey. Finally, we outline some open issues and future research directions.Comment: 32 pages, 15 figures, 5 tables, 168 reference

A Survey on Dynamic Spectrum Access Techniques in Cognitive Radio Networks

The idea of Cognitive Radio (CR) is to share the spectrum between a user called primary, and a user called secondary. Dynamic Spectrum Access (DSA) is a new spectrum sharing paradigm in cognitive radio that allows secondary users to access the abundant spectrum holes in the licensed spectrum bands. DSA is an auspicious technology to alleviate the spectrum scarcity problem and increase spectrum utilization. While DSA has attracted many research efforts recently, in this paper, a survey of spectrum access techniques using cooperation and competition to solve the problem of spectrum allocation in cognitive radio networks is presented

ECONOMIC APPROACHES AND MARKET STRUCTURES FOR TEMPORAL-SPATIAL SPECTRUM SHARING

In wireless communication systems, economic approaches can be applied to spectrum sharing and enhance spectrum utilization. In this research, we develop a model where geographic information, including licensed areas of primary users (PUs) and locations of secondary users (SUs), plays an important role in the spectrum sharing system. We consider a multi-price policy and the pricing power of noncooperative PUs in multiple geographic areas. Meanwhile, the value assessment of a channel is price-related and the demand from the SUs is price-elastic. By applying an evolutionary procedure, we prove the existence and uniqueness of the optimal payoff for each PU selling channels without reserve. In the scenario of selling channels with reserve, we predict the channel prices for the PUs leading to the optimal supplies of the PUs and hence the optimal payoffs. To increase spectrum utilization, the scenario of spatial spectrum reuse is considered. We consider maximizing social welfare via on-demand channel allocation, which describes the overall satisfaction of the SUs when we involve the supply and demand relationship. We design a receiver-centric spectrum reuse mechanism, in which the optimal channel allocation that maximizes social welfare can be achieved by the Vickrey-Clarke-Groves (VCG) auction for maximal independent groups (MIGs). We prove that truthful bidding is the optimal strategy for the SUs, even though the SUs do not participate in the VCG auction for MIGs directly. Therefore, the MIGs are bidding truthfully and the requirement for social welfare maximization is satisfied. To further improve user satisfaction, user characteristics that enable heterogeneous channel valuations need to be considered in spatial spectrum reuse. We design a channel transaction mechanism for non-symmetric networks and maximize user satisfaction in consideration of multi-level flexible channel valuations of the SUs. Specifically, we introduce a constrained VCG auction. To facilitate the bid formation, we transform the constrained VCG auction to a step-by-step decision process. Meanwhile, the SUs in a coalition play a coalitional game with transferable utilities. We use the Shapley value to realize fair payoff distribution among the SUs in a coalition

Game theory for cooperation in multi-access edge computing

Cooperative strategies amongst network players can improve network performance and spectrum utilization in future networking environments. Game Theory is very suitable for these emerging scenarios, since it models high-complex interactions among distributed decision makers. It also finds the more convenient management policies for the diverse players (e.g., content providers, cloud providers, edge providers, brokers, network providers, or users). These management policies optimize the performance of the overall network infrastructure with a fair utilization of their resources. This chapter discusses relevant theoretical models that enable cooperation amongst the players in distinct ways through, namely, pricing or reputation. In addition, the authors highlight open problems, such as the lack of proper models for dynamic and incomplete information scenarios. These upcoming scenarios are associated to computing and storage at the network edge, as well as, the deployment of large-scale IoT systems. The chapter finalizes by discussing a business model for future networks.info:eu-repo/semantics/acceptedVersio

Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization

The Spectrum Shortage Problem: Channel Assignment and Cognitive Networks

Recent studies have shown that the proliferation of wireless applications and services, experienced in the last decade, is leading to the challenging spectrum shortage problem. We provide a general overview regarding the spectrum shortage problem from the point of view of different technologies. First, we propose solutions based on multi-radio multi-channel wireless mesh networks in order to improve the usage of unlicensed wireless resources. Then, we move our focus on cognitive networks in order to analyze issues and solutions to opportunistically use licensed wireless resources. In wireless mesh networks, the spectrum shortage problem is addressed equipping each device with multiple radios which are turned on different orthogonal channels. We propose G-PaMeLA, which splits in local sub-problems the joint channel assignment and routing problem in multi-radio multi-channel wireless mesh networks. Results demonstrate that G-PaMeLA significantly improves network performance, in terms of packet loss and throughput fairness compared to algorithms in the literature. Unfortunately, even if orthogonal channels are used, wireless mesh networks result in what is called spectrum overcrowding. In order to address the spectrum overcrowding problem, careful analysis on spectrum frequencies has been conducted. These studies identified the possibility of transmitting on licensed channels, which are surprisingly underutilized. With the aim of addressing the resources problem using licensed channels, cognitive access and mesh networks have been developed. In cognitive access networks, we identify as the major problem the self-coexistence, which is the ability to access channels on a non-interfering basis with respect to licensed and unlicensed wireless devices. We propose two game theoretic frameworks which differentiate in having non-cooperative (NoRa) and cooperative (HeCtor) cognitive devices, respectively. Results show that HeCtor achieves higher throughput than NoRa but at the cost of higher computational complexity, which leads to a smaller throughput in cases where rapid changes occur in channels' occupancy. In contrast, NoRa attains the same throughput independent of the variability in channels' occupancy, hence cognitive devices adapt faster to such changes. In cognitive mesh networks, we analyze the coordination problem among cognitive devices because it is the major concern in implementing mesh networks in environments which change in time and space. We propose Connor, a clustering algorithm to address the coordination problem, which establishes common local control channels. Connor, in contrast with existing algorithms in the literature, does not require synchronization among cognitive mesh devices and allows a fast re-clustering when changes occur in channel's occupancy by licensed users. Results show that Connor performs better than existing algorithms in term of number of channels used for control purposes and time to reach and stay on stable configurations