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

The Question of Spectrum: Technology, Management, and Regime Change

There is general agreement that the traditional command-and-control regulation of radio spectrum by the FCC (and NTIA) has failed. There is no general agreement on which regime should succeed it. Property rights advocates take Ronald Coase's advice that spectrum licenses should be sold off and traded in secondary markets, like any other assets. Commons advocates argue that new technologies cannot be accommodated by a licensing regime (either traditional or property rights) and that a commons regime leads to the most efficient means to deliver useful spectrum to the American public. This article reviews the scholarly history of this controversy, outlines the revolution of FCC thinking, and parses the question of property rights vs. commons into four distinct parts: new technology, spectrum uses, spectrum management, and the overarching legal regime. Advocates on both sides find much to agree about on the first three factors; the disagreement is focused on the choice of overarching regime to most efficiently and effectively make spectrum and its applications available to the American public. There are two feasible regime choices: a property rights regime and a mixed licensed/commons regime subject to regulation. The regime choice depends upon four factors: dispute resolution, transactions costs, tragedies of the commons and anticommons, and flexibility to changing technologies and demands. Each regime is described and analyzed against these four factors. With regard to pure transactions costs, commons may hold an advantage but it appears quite small. For all other factors, the property rights regime holds very substantial advantages relative to the mixed regime. I conclude that the choice comes down to markets vs. regulation as mechanism for allocating resources.

Interference modelling and management for cognitive radio networks

Radio spectrum is becoming increasingly scarce as more and more devices go wireless. Meanwhile, studies indicate that the assigned spectrum is not fully utilised. Cognitive radio (CR) technology is envisioned to be a promising solution to address the imbalance between spectrum scarcity and spectrum underutilisation. It improves the spectrum utilisation by reusing the unused or underutilised spectrum owned by incumbent systems (primary systems). With the introduction of CR networks, two types of interference originating from CR networks are introduced. They are the interference from CR to primary networks (CR-primary interference) and the interference among spectrum-sharing CR nodes (CR-CR interference). The interference should be well controlled and managed in order not to jeopardise the operation of the primary network and to improve the performance of CR systems. This thesis investigates the interference in CR networks by modelling and mitigating the CR-primary interference and analysing the CR-CR interference channels. Firstly, the CR-primary interference is modelled for multiple CR nodes sharing the spectrum with the primary system. The probability density functions of CR-primary interference are derived for CR networks adopting different interference management schemes. The relationship between CR operating parameters and the resulting CRprimary interference is investigated. It sheds light on the deployment of CR networks to better protect the primary system. Secondly, various interference mitigation techniques that are applicable to CR networks are reviewed. Two novel precoding schemes for CR multiple-input multipleoutput (MIMO) systems are proposed to mitigate the CR-primary interference and maximise the CR throughput. To further reduce the CR-primary interference, we also approach interference mitigation from a cross-layer perspective by jointly considering channel allocation in the media access control layer and precoding in the physical layer of CR MIMO systems. Finally, we analyse the underlying interference channels among spectrum-sharing CR users when they interfere with each other. The Pareto rate region for multi-user MIMO interference systems is characterised. Various rate region convexification schemes are examined to convexify the rate region. Then, game theory is applied to the interference system to coordinate the operation of each CR user. Nash bargaining over MIMO interference systems is characterised as well. The research presented in this thesis reveals the impact of CR operation on the resulting CR-primary network, how to mitigate the CR-primary interference and how to coordinate the spectrum-sharing CR users. It forms the fundamental basis for interference management in CR systems and consequently gives insights into the design and deployment of CR networks

Radio Resource Management for Unmanned Aerial Vehicle Assisted Wireless Communications and Networking

In recent years, employing unmanned aerial vehicles (UAVs) as aerial communication platforms or users is envisioned as a promising solution to enhance the performance of the existing wireless communication systems. However, applying UAVs for information technology applications also introduces many new challenges. This thesis focuses on the UAV-assisted wireless communication and networking, and aims to address the challenges through exploiting and designing efficient radio resource management methods. Specifically, four research topics are studied in this thesis. Firstly, to address the constraint of network heterogeneity and leverage the benefits of diversity of UAVs, a hierarchical air-ground heterogeneous network architecture enabled by software defined networking is proposed, which integrates both high and low altitude platforms into conventional terrestrial networks to provide additional capacity enhancement and expand the coverage of current network systems. Secondly, to address the constraint of link disconnection and guarantee the reliable communications among UAVs as aerial user equipment to perform sensing tasks, a robust resource allocation scheme is designed while taking into account the dynamic features and different requirements for different UAV transmission connections. Thirdly, to address the constraint of privacy and security threat and motivate the spectrum sharing between cellular and UAV operators, a blockchain-based secure spectrum trading framework is constructed where mobile network operators and UAV operators can share spectrum in a distributed and trusted environment based on blockchain technology to protect users' privacy and data security. Fourthly, to address the constraint of low endurance of UAV and prolong its flight time as an aerial base station for delivering communication coverage in a disaster area, an energy efficiency maximization problem jointly optimizing user association, UAV's transmission power and trajectory is studied in which laser charging is exploited to supply sustainable energy to enable the UAV to operate in the sky for a long time

Leveraging intelligence from network CDR data for interference aware energy consumption minimization

Cell densification is being perceived as the panacea for the imminent capacity crunch. However, high aggregated energy consumption and increased inter-cell interference (ICI) caused by densification, remain the two long-standing problems. We propose a novel network orchestration solution for simultaneously minimizing energy consumption and ICI in ultra-dense 5G networks. The proposed solution builds on a big data analysis of over 10 million CDRs from a real network that shows there exists strong spatio-temporal predictability in real network traffic patterns. Leveraging this we develop a novel scheme to pro-actively schedule radio resources and small cell sleep cycles yielding substantial energy savings and reduced ICI, without compromising the users QoS. This scheme is derived by formulating a joint Energy Consumption and ICI minimization problem and solving it through a combination of linear binary integer programming, and progressive analysis based heuristic algorithm. Evaluations using: 1) a HetNet deployment designed for Milan city where big data analytics are used on real CDRs data from the Telecom Italia network to model traffic patterns, 2) NS-3 based Monte-Carlo simulations with synthetic Poisson traffic show that, compared to full frequency reuse and always on approach, in best case, proposed scheme can reduce energy consumption in HetNets to 1/8th while providing same or better Qo