Robustness of OFDM signal against temporally localized impulsive noise

Budsabathon, Montree; Hara, Shinsuke

doi:10.1109/vtc.2001.956484

Cited by 11 publications

(5 citation statements)

References 6 publications

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“…Last but not least, we conjecture that the performance of MED and ED under the implementation-oriented model can be improved if the known normalization gains before the ADC are taken into account for the design of new test statistics and for producing the estimate of the thermal noise power in each cognitive radio. ED has a stronger demand for such improvement, since it simply The number of CRs under cooperation resulting from the CR elimination IN countermeasure will be the random variable W =    X, X ≥ 2 0, otherwise (10) The average number of CRs under cooperation, m E , is the expected value of W, which is given by Equation (8)…”

Section: Discussionmentioning

confidence: 99%

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Performance of Cooperative Eigenvalue Spectrum Sensing with a Realistic Receiver Model under Impulsive Noise

Guimarães

Souza

Barreto

2013

JSAN

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In this paper we present a unified comparison of the performance of four detection techniques for centralized data-fusion cooperative spectrum sensing in cognitive radio networks under impulsive noise, namely, the eigenvalue-based generalized likelihood ratio test (GLRT), the maximum-minimum eigenvalue detection (MMED), the maximum eigenvalue detection (MED), and the energy detection (ED). We consider two system models: an implementation-oriented model that includes the most relevant signal processing tasks realized by a real cognitive radio receiver, and the theoretical model conventionally adopted in the literature. We show that under the implementation-oriented model, GLRT and MMED are quite robust under impulsive noise, whereas the performance of MED and ED is drastically degraded. We also show that performance under the conventional model can be too pessimistic if impulsive noise is present, whereas it can be too optimistic in the absence of this impairment. We also discuss the fact that impulsive noise is not such a severe problem when we take into account the more realistic implementation-oriented model

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Section: Discussionmentioning

confidence: 99%

“…Impulsive noise in wireless systems may arise from several different sources, such as lightning, electrical switches, motors, vehicle ignition circuits, and reflections from sea waves, and it is known that it can severely degrade the performance of communications systems [9,10].…”

Section: Impulsive Noisementioning

confidence: 99%

Performance of Cooperative Eigenvalue Spectrum Sensing with a Realistic Receiver Model under Impulsive Noise

Guimarães

Souza

Barreto

2013

JSAN

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“…Also the most basic sensing method the ED is reasonably sensitive to the accuracy of the expected noise variance [29]. We considered the effect of impulsive noise repetitive or non-repetitive pulses with a random inte duration and occurrence for investigating the performance of the eigenvalue-based spectrum sensing scheme in perspective of spectrum sensing [30][31].…”

Section: And Csfd [21 Technique Is Unique In Itself and Possessing Cementioning

confidence: 99%

Performance Evaluation of Spectrum Sensing in Cognitive Radio for Conventional Discrete-time Memoryless MIMO Fading Channel Model

Patil

Wadhai²

2014

Proceedings of the 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing

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Spectrum sensing is the crucial task of a cognitive radio. Cognitive Radio (CR) have been advanced as a technology for the opportunistic use of underutilized spectrum where secondary users sense the presence of primary users and use the spectrum if it is empty, without affecting their performance. Spectrum sensing in CR is challenged by a number of uncertainties, which degrade the sensing. The discrete-time memory less multiple inputs multiple output (MIMO) fading channel conventional model is implemented to appraise the performance of different spectrum sensing techniques. The signal detection in CR networks under a non parametric multisensory detection scenario is considered for performance comparison under the presence of impulsive noise. The examination focuses on performance evaluation of five different spectrum sensing mechanisms namely energy detection (ED), Generalized Likelihood Ratio Test (GLRT), Roy's largest Root Test (RLRT), Maximum Eigenvalue detection (MED) and Cyclostationary feature detection (CSFD). The analysis of the result indicates that, the sensing performance is improved in GLRT method for conventional model also it can be concluded that the performance under the conventional model can be too pessimistic in absence of impulsive noise.

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“…When used with rectangular pulse shaping, multi-carrier modulation and detection are efficiently implemented using the Fast Fourier Transform and the Inverse Fast Fourier Transformation (FFT/IFFT). The IFFT/FFT modulator/demodulator pair of the so-obtained Orthogonal Frequency Division Multiplexing (OFDM) scheme enables channel equalization in the frequency-domain, thus eliminating the need for potentially complex timedomain equalization of a single-carrier system [2]. For this reason, OFDM has found application in a number of systems.…”

Section: System Modelmentioning

confidence: 99%

Impulsive noise suppression in DFT-SOFDM system

Shen

Sun

Cheng

et al. 2009

2009 International Conference on Test and Measurement

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The basic idea underlying OFDM systems is the division of the available frequency spectrum into several sub-carriers. To obtain a high spectral efficiency, the frequency responses of the sub-carriers are overlapping but orthogonal [4][5].Consider block diagram of the DFT-SOFDM transmission system shown in Fig.l. noise. The longer symbol duration provides an advantage, since the impulsive noise energy is spread among simultaneously transmitted sub-carriers. However, it was recently recognized that this advantage turns into disadvantage, if impulse noise energy exceed a certain threshold [3].A simple but effective method of reducing the adverse effect of impulsive noise is to precede conventional OFDM demodulator with nonlinearity methods. In this paper, blanking nonlinearity and clipping nonlinearity are applied in underwater acoustic DFT-SOFDM system. This method is widely used in practice since it is very simple to implement and provides an improvement in impulsive noise channels. The study was based on the experimental results in real underwater acoustic channel.The rest of this paper is organized as follows. In Section II , the signal processing operations in DFT-SOFDM system was described. Impulsive noise cancellation was described in Section III.The experiment results in shallow water near the seaside of Xiamen were given in Section N. Figure 1_ the block diagram of the DFT-spread OFDM system AddCP

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Robustness of OFDM signal against temporally localized impulsive noise

Cited by 11 publications

References 6 publications

Performance of Cooperative Eigenvalue Spectrum Sensing with a Realistic Receiver Model under Impulsive Noise

Performance of Cooperative Eigenvalue Spectrum Sensing with a Realistic Receiver Model under Impulsive Noise

Performance Evaluation of Spectrum Sensing in Cognitive Radio for Conventional Discrete-time Memoryless MIMO Fading Channel Model

Impulsive noise suppression in DFT-SOFDM system

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