Threshold Detection in Narrow-Band Non-Gaussian Noise

Vastola, K.S.

doi:10.1109/tcom.1984.1096037

Cited by 147 publications

(68 citation statements)

References 26 publications

(8 reference statements)

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“…This non-Gaussian noise [1] which is prevalent because of either man made noise sources or natural phenomena can be momentous in many applications and must be taken into consideration to improve system performance. Automobile ignitions, neon lights and many other electronic devices are the common source of man made noise.…”

Section: N Various Communication Environments the Gaussian Noisementioning

confidence: 99%

“…Automobile ignitions, neon lights and many other electronic devices are the common source of man made noise. On the other hand, lightning discharges, impulsive interference in power line channels or in undersea communication systems noisy aquatic animals or surrounding acoustical noises due to ice cracking in arctic regions are the innate means of the occurrence of impulsive noise [1].…”

Section: N Various Communication Environments the Gaussian Noisementioning

confidence: 99%

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Performance analysis of turbo codes over Rician fading channels with impulsive noise

Ali

Ince

2007

2007 IEEE International Conference on Telecommunications and Malaysia International Conference on Communications

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Abstract-The statistical characteristics of impulsive noise differ greatly from those of Gaussian noise. Hence, the performance of conventional decoders, optimized for additive white Gaussian noise (AWGN) channels is not promising in non-Gaussian environments. In order to achieve improved performance in impulsive environments the decoder structure needs to be modified in accordance with the impulsive noise model. This paper provides performance analysis of turbo codes over fully interleaved Rician fading channels with Middleton's additive white Class-A impulsive noise (MAWCAIN). Simulation results for the memoryless Rician fading channels using coherent BPSK signaling for both the cases of ideal channel state information (ICSI) and no channel state information (NCSI) at the decoder are provided. An eight state turbo encoder having (1, 13/15, 13/15) generator polynomial is used throughout the analysis. The novelty of this work lies in the fact that this is an initial attempt to provide a detailed analysis of turbo codes over Rician fading channels with impulsive noise rather than AWGN.Index Terms-Channel reliability, ideal channel state information, Middleton's additive white Class-A impulsive noise channel, no channel state information, Rician fading channel, turbo codes.

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Section: N Various Communication Environments the Gaussian Noisementioning

confidence: 99%

Section: N Various Communication Environments the Gaussian Noisementioning

confidence: 99%

Performance analysis of turbo codes over Rician fading channels with impulsive noise

Ali

Ince

2007

2007 IEEE International Conference on Telecommunications and Malaysia International Conference on Communications

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“…The mixing parameter regulates the contribution of the non-Gaussian component. Usually it varies between 0:01 to 0:25 [7].…”

Section: Filtering In Non-gaussian Noisementioning

confidence: 99%

“…When a Gaussian density with large variance is used to emulate the non-Gaussian dominant component, the ratio of the dominant to nominal density variances k is on the order of 10 to 10; 000 [7], [8]. Due to its flexibility, many different naturally occurring noise distribution shapes can be approximated using the , mixture approach.…”

Section: Filtering In Non-gaussian Noisementioning

confidence: 99%

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Narrowband interference suppression via nonlinear estimation

Plataniotis

Venetsanopoulos

Proceedings Third IEEE Symposium on Computers and Communications. ISCC'98. (Cat. No.98EX166)

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Broadband and Narrow‐Band Noise Modeling in Powerline Communications

Shongwe

Ferreira

Vinck

2015

Wiley Encyclopedia of Electrical and Electronics Engineering

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This article gives an overview of noise modeling of the two most problematic types of noise in powerline communications (PLC), namely, impulse noise (broadband noise) and frequency disturbers (narrow‐band interference (NBI)). The models for these two types of noise are studied for orthogonal frequency‐division multiplexing (OFDM) systems. The first part of the article looks at several impulse noise models in the literature. A demonstration of the effects of impulse noise on OFDM, using the Middleton Class A model, is given. Methods of combating impulse noise are also studied. In the second part, of the article, we focus on narrow‐band interference modeling and also show how NBI affects OFDM systems. The main focus of NBI is on presenting a detailed NBI model because NBI modeling has not been given much attention in the literature. In our discussion of the NBI model, we show that, with some assumptions, the NBI model and the Middleton Class A model can be similar.

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Threshold Detection in Narrow-Band Non-Gaussian Noise

Cited by 147 publications

References 26 publications

Performance analysis of turbo codes over Rician fading channels with impulsive noise

Performance analysis of turbo codes over Rician fading channels with impulsive noise

Narrowband interference suppression via nonlinear estimation

Broadband and Narrow‐Band Noise Modeling in Powerline Communications

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