Advanced Blanking Nonlinearity for Mitigating Impulsive Interference in OFDM Systems

Epple, Ulrich; Schnell, Michael

doi:10.1109/tvt.2016.2535374

Cited by 18 publications

(23 citation statements)

References 25 publications

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“…Further, BER performance of both the proposed and blanking receivers converge around SINR = 0 dB due to low amplitude of impulse noise samples at these SINR values and hence, impulse noise behaves similar to Gaussian noise at SINR = 0 dB. Next, the BER performance of TH-BPSK UWB system in the presence of impulse noise using the proposed receiver and the blanking non-linearity based receiver in [3,16,17] is analyzed in AWGN and multipath IEEE 802.15.4a channel CM1 [12]. Results are shown in Fig.…”

Section: Simulation Results and Discussionmentioning

confidence: 91%

“…This section presents performance evaluation of the proposed receiver design compared to the conventional and the non-linear blanking based receivers. In [3,16,17], non-linear blanking receiver is analyzed for mitigating impulse noise effect in OFDM system. However, we use it for UWB system with suitable modification and parameter selection for the first time in UWB literature in order to mitigate impulse noise.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…To mitigate impulse noise effect, threshold T for the blanking based receiver in UWB system is selected such that false alarm and miss-detection probabilities are minimized. The optimal value of T is derived as [3,16,17] T opt = min…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…1 (top subfigure) and the desired signal s is completely buried within the impulse noise. In the blanking based receiver [3,16,17], high amplitude samples of impulse noise are blanked (assigned zero value), while low amplitude impulse samples are present at the output of blanking unit in signal as shown in Fig. 1 (middle Further, the mean square error (MSE) between desired multipath received signal s and CDA output signalŝ is calculated and defined as…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…The received signal r (at the top), blanking output signal y (using[3,16,17]) and signalŝ (at the bottom) at the output of the proposed CDA.…”

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confidence: 99%

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Impulse Noise Mitigation in IR-UWB Communication Using Signal Cluster Sparsity

2018

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In many applications, ultra-wide band (UWB) system experiences impulse noise due to surrounding physical noise sources. Therefore, a conventional receiver (correlator or matched filter) designed for additive Gaussian noise system is not optimum for an impulse noise affected communication channel.In this paper, we propose a new robust receiver design that utilizes the received UWB signal cluster sparsity to mitigate impulse noise. Further, multipath channel diversity enhances the signal-to-noise ratio, as compared to the single path after impulse noise removal in the proposed receiver design. The proposed receiver is analyzed in time hopping binary phase shift keying UWB system and is compared with popular blanking non-linearity based receiver in Bernoulli-Gaussian impulse noise over both single and multipath IEEE 802.15.4a channels. Unlike existing designs, the proposed receiver does not require any training sequence. The proposed receiver is observed to be robust with improved bit error rate performance as compared to a blanking receiver in the presence of impulse noise.

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Section: Simulation Results and Discussionmentioning

confidence: 91%

Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…The received signal r (at the top), blanking output signal y (using[3,16,17]) and signalŝ (at the bottom) at the output of the proposed CDA.…”

mentioning

confidence: 99%

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Impulse Noise Mitigation in IR-UWB Communication Using Signal Cluster Sparsity

2018

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The Capacity Performance of OFDM Systems with Nonlinear Pulse Blanking in Frequency Selective Fading Channels

Liu

Zhao

2018

Wireless Pers Commun

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Nonlinear pulse blanking is a widely applied method to mitigate the impulse interference of orthogonal frequency division multiplexing (OFDM) systems. To quantitatively analyze the capacity of the OFDM system with nonlinear pulse blanking, the analytical expressions of the instantaneous output signal-to-interference-plus-noise ratio of the OFDM system with ideal blanking, peak value blanking, and optimum threshold blanking are first derived. The probability density function of the instantaneous capacity of the OFDM system with nonlinear pulse blanking is then estimated by the finite mixture with the expectation-maximization algorithm. The ergodic capacity and the probability of the outage capacity of the OFDM system with nonlinear pulse blanking are obtained based on the estimated probability density function. Finally, the simulation results are provided to indicate its good agreement with the theoretical results.

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Joint Channel Estimation and Impulsive Noise Mitigation Method for OFDM Systems Using Sparse Bayesian Learning

et al. 2019

IEEE Access

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The impulsive noise can deteriorate sharply the performance of orthogonal frequency division multiplexing (OFDM) systems. In this paper, we propose a novel joint channel impulse response estimation and impulsive noise mitigation algorithm based on compressed sensing theory. In this algorithm, both the channel impulse response and the impulsive noise are treated as a joint sparse vector. Then, the sparse Bayesian learning framework is adopted to jointly estimate the channel impulse response, the impulsive noise, and the data symbols, in which the data symbols are regarded as unknown parameters. The Cramér-Rao Bound is derived for the benchmark. Unlike the previous impulsive noise mitigation methods, the proposed algorithm utilizes all subcarriers without any a priori information of the channel and impulsive noise. The simulation results show that the proposed algorithm achieves significant performance improvement on the channel estimation and bit error rate performance.INDEX TERMS Orthogonal frequency division multiplexing (OFDM), channel estimation, impulsive noise mitigation, sparse Bayesian learning (SBL), compressed sensing.

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Advanced Blanking Nonlinearity for Mitigating Impulsive Interference in OFDM Systems

Cited by 18 publications

References 25 publications

Impulse Noise Mitigation in IR-UWB Communication Using Signal Cluster Sparsity

Impulse Noise Mitigation in IR-UWB Communication Using Signal Cluster Sparsity

The Capacity Performance of OFDM Systems with Nonlinear Pulse Blanking in Frequency Selective Fading Channels

Joint Channel Estimation and Impulsive Noise Mitigation Method for OFDM Systems Using Sparse Bayesian Learning

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