1,015 research outputs found
Optimal Scanning Bandwidth Strategy Incorporating Uncertainty about Adversary's Characteristics
In this paper we investigate the problem of designing a spectrum scanning
strategy to detect an intelligent Invader who wants to utilize spectrum
undetected for his/her unapproved purposes. To deal with this problem we model
the situation as two games, between a Scanner and an Invader, and solve them
sequentially. The first game is formulated to design the optimal (in maxmin
sense) scanning algorithm, while the second one allows one to find the optimal
values of the parameters for the algorithm depending on parameters of the
network. These games provide solutions for two dilemmas that the rivals face.
The Invader's dilemma consists of the following: the more bandwidth the Invader
attempts to use leads to a larger payoff if he is not detected, but at the same
time also increases the probability of being detected and thus fined.
Similarly, the Scanner faces a dilemma: the wider the bandwidth scanned, the
higher the probability of detecting the Invader, but at the expense of
increasing the cost of building the scanning system. The equilibrium strategies
are found explicitly and reveal interesting properties. In particular, we have
found a discontinuous dependence of the equilibrium strategies on the network
parameters, fine and the type of the Invader's award. This discontinuity of the
fine means that the network provider has to take into account a human/social
factor since some threshold values of fine could be very sensible for the
Invader, while in other situations simply increasing the fine has minimal
deterrence impact. Also we show how incomplete information about the Invader's
technical characteristics and reward (e.g. motivated by using different type of
application, say, video-streaming or downloading files) can be incorporated
into scanning strategy to increase its efficiency.Comment: This is the last draft version of the paper. Revised version of the
paper was published in EAI Endorsed Transactions on Mobile Communications and
Applications, Vol. 14, Issue 5, 2014, doi=10.4108/mca.2.5.e6. arXiv admin
note: substantial text overlap with arXiv:1310.724
Comprehensive survey on quality of service provisioning approaches in cognitive radio networks : part one
Much interest in Cognitive Radio Networks (CRNs) has been raised recently by enabling unlicensed (secondary) users to utilize the unused portions of the licensed spectrum. CRN utilization of residual spectrum bands of Primary (licensed) Networks (PNs) must avoid harmful interference to the users of PNs and other overlapping CRNs. The coexisting of CRNs depends on four components: Spectrum Sensing, Spectrum Decision, Spectrum Sharing, and Spectrum Mobility. Various approaches have been proposed to improve Quality of Service (QoS) provisioning in CRNs within fluctuating spectrum availability. However, CRN implementation poses many technical challenges due to a sporadic usage of licensed spectrum bands, which will be increased after deploying CRNs. Unlike traditional surveys of CRNs, this paper addresses QoS provisioning approaches of CRN components and provides an up-to-date comprehensive survey of the recent improvement in these approaches. Major features of the open research challenges of each approach are investigated. Due to the extensive nature of the topic, this paper is the first part of the survey which investigates QoS approaches on spectrum sensing and decision components respectively. The remaining approaches of spectrum sharing and mobility components will be investigated in the next part
PLC for the smart grid: state-of-the-art and challenges
This paper aims to review systems and applications for power line communications (PLC) in the context of the smart grid. We discuss the main applications and summarise state-of-the-art PLC systems and standards. We report efforts and challenges in channel and noise modelling, as well as in state-of-the-art transmission technology approaches
Multiscale image denoising using goodness-of-fit test based on EDF statistics.
Two novel image denoising algorithms are proposed which employ goodness of fit (GoF) test at multiple image scales. Proposed methods operate by employing the GoF tests locally on the wavelet coefficients of a noisy image obtained via discrete wavelet transform (DWT) and the dual tree complex wavelet transform (DT-CWT) respectively. We next formulate image denoising as a binary hypothesis testing problem with the null hypothesis indicating the presence of noise and the alternate hypothesis representing the presence of desired signal only. The decision that a given wavelet coefficient corresponds to the null hypothesis or the alternate hypothesis involves the GoF testing based on empirical distribution function (EDF), applied locally on the noisy wavelet coefficients. The performance of the proposed methods is validated by comparing them against the state of the art image denoising methods
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