151 research outputs found

    On the Construction of Radio Environment Maps for Cognitive Radio Networks

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    The Radio Environment Map (REM) provides an effective approach to Dynamic Spectrum Access (DSA) in Cognitive Radio Networks (CRNs). Previous results on REM construction show that there exists a tradeoff between the number of measurements (sensors) and REM accuracy. In this paper, we analyze this tradeoff and determine that the REM error is a decreasing and convex function of the number of measurements (sensors). The concept of geographic entropy is introduced to quantify this relationship. And the influence of sensor deployment on REM accuracy is examined using information theory techniques. The results obtained in this paper are applicable not only for the REM, but also for wireless sensor network deployment.Comment: 6 pages, 7 figures, IEEE WCNC conferenc

    Comnet: Annual Report 2012

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    Spectrum Awareness in Cognitive Radio Systems

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    The paper addresses the issue of the Electromagnetic Environment Situational Awareness techniques. The main focus is put on sensing and the Radio Environment Map. These two dynamic techniques are described in detail. The Radio Environment Map is considered the essential part of the spectrum management system. It is described how the density and deployment of sensors affect the quality of maps and it is analysed which methods are the most suitable for map construction. Additionally, the paper characterizes several sensing methods

    Spectrum Awareness in Cognitive Radio Systems

    Get PDF
    The paper addresses the issue of the Electromagnetic Environment Situational Awareness techniques. The main focus is put on sensing and the Radio Environment Map. These two dynamic techniques are described in detail. The Radio Environment Map is considered the essential part of the spectrum management system. It is described how the density and deployment of sensors affect the quality of maps and it is analysed which methods are the most suitable for map construction. Additionally, the paper characterizes several sensing methods

    On the feasibility of unlicensed communications in the TV white space: Field measurements in the UHF band

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    In practical unlicensed communications in TV band, radio devices have to identify, at first, the transmission opportunities, that is, the portion of the spectrum licensed for broadcasting services unoccupied in a certain region at certain time, that is, the so-called TV white space. In this paper the outcome of field measurements in the UHF TV band (470-860 MHz) conducted in EU is presented. To obtain empirical values for the parameters upon which unlicensed radio devices are able to distinguish in a real scenario between empty and occupied TV channels, signal power measurements have been performed in Italy, Spain, and Romania on rural, suburban, and urban sites, at different heights over the ground by using different analysis bandwidths. The aim of this work is to provide a set of practical parameters upon which harmless unlicensed communication in the UHF TV white space is feasible. The results have been analyzed with respect to the hidden node margin problem, spectrum sensing bandwidth, and occupancy threshold

    Wideband frequency domain detection using Teager-Kaiser energy operator

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    International audienceThis paper addresses wireless microphone sensing in the TV white space and efficient detection of narrowband FM modulation signals. To this end, a wideband frequency domain analysis is proposed. The required Fast Fourier Transform for this operation may be shared between sensing analysis and modulation functions. A particular decision metric is then studied for the analysis of wireless microphone signals based on the Teager-Kaiser energy operator. Simulation results show that 6 dB of detection gain could be achieved when using a frequency domain analysis compared to time domain methods. The Teager-Kaiser detection leads to further improvement of 1.5 dB. This performance could be reached at no extra cost in term of complexity

    A Belief-Based Decision-Making Framework for Spectrum Selection in Cognitive Radio Networks

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    This paper presents a comprehensive cognitive management framework for spectrum selection in cognitive radio (CR) networks. The framework uses a belief vector concept as a means to predict the interference affecting the different spectrum blocks (SBs) and relies on a smart analysis of the scenario dynamicity to properly determine an adequate observation strategy to balance the tradeoff between achievable performance and measurement requirements. In this respect, the paper shows that the interference dynamics in a given SB can be properly characterized through the second highest eigenvalue of the interference state transition matrix. Therefore, this indicator is retained in the proposed framework as a relevant parameter to drive the selection of both the observation strategy and spectrum selection decision-making criterion. This paper evaluates the proposed framework to illustrate the capability to properly choose among a set of possible observation strategies under different scenario conditions. Furthermore, a comparison against other state-of-the-art solutions is presented

    Energy and bursty packet loss tradeoff over fading channels: a system-level model

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    Energy efficiency and quality of service (QoS) guarantees are the key design goals for the 5G wireless communication systems. In this context, we discuss a multiuser scheduling scheme over fading channels for loss tolerant applications. The loss tolerance of the application is characterized in terms of different parameters that contribute to quality of experience (QoE) for the application. The mobile users are scheduled opportunistically such that a minimum QoS is guaranteed. We propose an opportunistic scheduling scheme and address the cross-layer design framework when channel state information (CSI) is not perfectly available at the transmitter and the receiver. We characterize the system energy as a function of different QoS and channel state estimation error parameters. The optimization problem is formulated using Markov chain framework and solved using stochastic optimization techniques. The results demonstrate that the parameters characterizing the packet loss are tightly coupled and relaxation of one parameter does not benefit the system much if the other constraints are tight. We evaluate the energy-performance tradeoff numerically and show the effect of channel uncertainty on the packet scheduler design
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