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A Nonparametric SVM-Based REM Recapitulation Assisted by Voluntary Sensing Participants under Smart Contracts on Blockchain

机译:基于智能合约的自愿感知参与者协助基于SVM的非参数REM重现

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摘要

This paper proposes a blockchain-based automated frequency coordination system (BAFCS) for secure and reliable spectrum sharing without causing any harmful interference to an existing system. For the exact assessment of whether the incumbent is interfered with by the spectrum sharer, the received signal strength (RSS) associated with the incumbent should be measured with sufficient accuracy at every location within the area of interest. However, since it requires brute force to carry out empirical measurements around an entire region, to lessen the burden, only the confined portion of the RSSs associated with the incumbent as a kind of primary user are observed and the omitted residuals are conventionally estimated by carrying out the well-known Kriging interpolation with regard to the geostatistical characteristics. This paper proposes a frequency coordination system capable of identifying whether a requested frequency band can be eligible for spectrum sharing while exchanging adequate information over blockchain network to confirm the usability. This paper proposes the Support Vector Machine (SVM)-based Kriging interpolation for recapitulating the radio environment map (REM) when only a fraction of the RSS measurements is acquired by the voluntary sensing participant (VSP). The nonparametric modeling approach for variograms proposed in this paper was determined to have a vital role in making a confident decision regarding spectrum sharing. The simulation result confirmed the effectiveness and the superiority of the proposed BAFCS with several affirmative features, such as enabling the consensus-based approval of spectrum sharing, the secure transaction of the information, and reliable assurance of no harmful interference.
机译:本文提出了一种基于区块链的自动频率协调系统(BAFCS),以实现安全可靠的频谱共享,而不会对现有系统造成任何有害干扰。为了精确评估频谱共享器是否干扰了运营者,应在感兴趣区域内的每个位置以足够的精度测量与运营者相关的接收信号强度(RSS)。但是,由于需要蛮力就整个区域进行经验测量,以减轻负担,因此,仅观察到与作为主要用户的在位用户相关的RSS的受限部分,并且通常通过携带来估计遗漏的残差在地统计特征方面,我们可以找到著名的Kriging插值法。本文提出了一种频率协调系统,该系统能够识别请求的频段是否适合频谱共享,同时在区块链网络上交换足够的信息以确认可用性。本文提出了基于支持向量机(SVM)的Kriging插值法,用于在自愿感测参与者(VSP)仅获得RSS测量的一小部分时,概括了无线电环境图(REM)。确定了本文提出的用于变异函数的非参数建模方法,该方法对于做出有关频谱共享的自信决策具有至关重要的作用。仿真结果证实了所提出的BAFCS具有几种肯定性特征的有效性和优越性,例如能够实现基于共识的频谱共享批准,信息的安全交易以及对无有害干扰的可靠保证。

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