233 research outputs found

    SMART: Coordinated Double-Sided Seal Bid Multiunit First Price Auction Mechanism for Cloud-Based TVWS Secondary Spectrum Market

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    Spectrum trading is an important aspect of television white space (TVWS) and it is driven by the failure of spectrum sensing techniques. In spectrum trading, the primary users lease their unoccupied spectrum to the secondary users for a market fee. Although spectrum trading is considered as a reliable approach, it is confronted with a spectrum transaction completion time problem, which negatively impacts on end-users Quality of Service and Quality of Experience metrics. Spectrum transaction completion time is the duration to successfully conduct TVWS spectrum trading. To address this issue, this paper proposes simple mechanism auction reward truthful (SMART), a fast and iterative machine learning-assisted spectrum trading model to address this issue. Simulated results indicate thatSMART out-performs referenced VERUM algorithm in three key performance indicators: bit-error rate, instantaneous throughput, and probability of dropped packets by 10%, 5%, and 15%, respectively

    Fractional frequency reused based interference mitigation in irregular geometry multicellular networks

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    Recent drastic growth in the mobile broadband services specifically with the proliferation of smart phones demands for higher spectrum capacity of wireless cellular systems. Due to the scarcity of the frequency spectrum, cellular systems are seeking aggressive frequency reuse, which improve the network capacity, however, at the expense of increased Inter Cell Interference (ICI). Fractional Frequency Reuse (FFR) scheme has been acknowledged as an effective ICI mitigation scheme, however, in literature FFR has been used mostly in perfect geometry network. In realistic deployment, the cellular geometry is irregular and each cell experiences varying ICI. The main objective of this thesis is to develop ICI mitigation scheme that improves spectrum efficiency and throughput for irregular geometry multicellular network. Irregular Geometry Sectored-Fractional Frequency Reuse (IGS-FFR) scheme is developed that comprises of cell partitioning and sectoring, and dynamic spectrum partitioning. The cell-partitioning and sectoring allows full frequency reuse within an irregular geometry cell. Nevertheless, the sub-regions in an irregular cell have varying coverage areas and thus demands diverse spectrum requirements. The IGSFFR scheme is designed to dynamically allocate the spectrum resources according to the traffic demands of each sub-region. An enhanced IGS-FFR has been developed to optimally allocate the spectrum resources to individual users of each sub-region. Enhanced IGS-FFR has been realized using two different approaches, Auction based Optimized IGS-FFR (AO-IGS-FFR) and Hungarian based Optimized IGS-FFR (HO-IGS-FFR). The results show that IGS-FFR has significantly improved the cell throughput by 89%, 45% and 18% and users’ satisfaction by 112%, 65.8% and 38% compared to Reuse-1, Strict-FFR and FFR-3 schemes, respectively. The findings show that the ICI mitigation in IGS-FFR is reinforced by users’ satisfaction. As the number of sectors in IGS-FFR increases from 3 to 4 and 6, the cell throughput increase by 21% and 33% because of spatial diversity exploitation along with orthogonal sub-band allocation. AO-IGS-FFR and HO-IGS-FFR have further improved the cell throughput of the basic FFR-3 by 65% and 72.2%, respectively. HO-IGS-FFR performs 7% better than the AO-IGS-FFR at the expense of 26.7% decrease in the users’ satisfaction and excessive complexity. Although, AO-IGS-FFR compromises sub-optimal bandwidth allocation, it is a low complexity scheme and can mitigate ICI with high users’ satisfaction. The enhanced IGS-FFR can be deployed in future heterogeneous irregular geometry multicellular OFDMA networks

    Game theory for cooperation in multi-access edge computing

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    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

    Blockchain-based distributive auction for relay-assisted secure communications

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    Physical layer security (PLS) is considered as a promising technique to prevent information eavesdropping in wireless systems. In this context, cooperative relaying has emerged as a robust solution for achieving PLS due to multipath diversity and relatively lower transmission power. However, relays or the relay operators in the practical environment are unwilling for service provisioning unless they are incentivized for their cost of services. Thus, it is required to jointly consider network economics and relay cooperation to improve system efficiency. In this paper, we consider the problem of joint network economics and PLS using cooperative relaying and jamming. Based on the double auction theory, we model the interaction between transmitters seeking for a particular level of secure transmission of information and relay operators for suitable relay and jammer assignment, in a multiple source-destination networks. In addition, theoretical analyses are presented to justify that the proposed auction mechanism satisfies the desirable economic properties of individual rationality, budget balance, and truthfulness. As the participants in the traditional centralized auction framework may take selfish actions or collude with each other, we propose a decentralized and trustless auction framework based on blockchain technology. In particular, we exploit the smart contract feature of blockchain to construct a completely autonomous framework, where all the participants are financially enforced by smart contract terms. The security properties of the proposed framework are also discussed

    Integration of Blockchain and Auction Models: A Survey, Some Applications, and Challenges

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    In recent years, blockchain has gained widespread attention as an emerging technology for decentralization, transparency, and immutability in advancing online activities over public networks. As an essential market process, auctions have been well studied and applied in many business fields due to their efficiency and contributions to fair trade. Complementary features between blockchain and auction models trigger a great potential for research and innovation. On the one hand, the decentralized nature of blockchain can provide a trustworthy, secure, and cost-effective mechanism to manage the auction process; on the other hand, auction models can be utilized to design incentive and consensus protocols in blockchain architectures. These opportunities have attracted enormous research and innovation activities in both academia and industry; however, there is a lack of an in-depth review of existing solutions and achievements. In this paper, we conduct a comprehensive state-of-the-art survey of these two research topics. We review the existing solutions for integrating blockchain and auction models, with some application-oriented taxonomies generated. Additionally, we highlight some open research challenges and future directions towards integrated blockchain-auction models
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