Adaptive Demodulation in Class a Impulse Noise Channels

Hägglund, Kristoffer; Axell, Erik

doi:10.1109/globecom38437.2019.9013968

Cited by 4 publications

(2 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, in power line communication (PLC), the impulsive noise can be characterized by the Bernoulli–Gaussian model [ 19 , 20 ] or the Middleton Class-A model [ 21 , 22 ]. Research in [ 23 , 24 ] proposed some algorithms for adaptive demodulation in impulse noise channels. The proposed methods compute appropriate LLRs based on four previously established parameter estimation techniques of symmetric

-stable noise and the classification or parameter estimation of Middleton’s Class A noise.…”

Section: Introductionmentioning

confidence: 99%

Improving Log-Likelihood Ratio Estimation with Bi-Gaussian Approximation under Multiuser Interference Scenarios

Yang

2021

Entropy

View full text Add to dashboard Cite

Accurate estimation of channel log-likelihood ratio (LLR) is crucial to the decoding of modern channel codes like turbo, low-density parity-check (LDPC), and polar codes. Under an additive white Gaussian noise (AWGN) channel, the calculation of LLR is relatively straightforward since the closed-form expression for the channel likelihood function can be perfectly known to the receiver. However, it would be much more complicated for heterogeneous networks where the global noise (i.e., noise plus interference) may be dominated by non-Gaussian interference with an unknown distribution. Although the LLR can still be calculated by approximating the distribution of global noise as Gaussian, it will cause performance loss due to the non-Gaussian nature of global noise. To address this problem, we propose to use bi-Gaussian (BG) distribution to approximate the unknown distribution of global noise, for which the two parameters of BG distribution can easily be estimated from the second and fourth moments of the overall received signals without any knowledge of interfering channel state information (CSI) or signaling format information. Simulation results indicate that the proposed BG approximation can effectively improve the word error rate (WER) performance. The gain of BG approximation over Gaussian approximation depends heavily on the interference structure. For the scenario of a single BSPK interferer with a 5 dB interference-to-noise ratio (INR), we observed a gain of about 0.6 dB. The improved LLR estimation can also accelerate the convergence of iterative decoding, thus involving a lower overall decoding complexity. In general, the overall decoding complexity can be reduced by 25 to 50%.

show abstract

-stable noise and the classification or parameter estimation of Middleton’s Class A noise.…”

Section: Introductionmentioning

confidence: 99%

Improving Log-Likelihood Ratio Estimation with Bi-Gaussian Approximation under Multiuser Interference Scenarios

Yang

2021

Entropy

View full text Add to dashboard Cite

show abstract

“…In addition, atmospheric and solar static signals caused by the sunspots and thunderstorms can also be represented by IN and it is expected to degrade the communication quality in mmWave bands [9,10]. Recently, great research interest is growing to model IN behavior and it is observed that the Middleton Class A model [11] is a widely accepted and realistic model to express the mixture noise model for wireless communication channels [12][13][14][15]. Besides, it is shown that the presence of IN is affecting the performance of the system negatively for the applications operating in the mmWave frequencies [16][17][18][19][20] and the degradation of the performance of massive MIMO systems under IN is investigated in [21].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Decoder with an Adaptive Fuzzy Logic Filter for Single-User Millimeter Wave Systems Under Impulsive Noise

Mulla

Rızaner

Ulusoy

2021

Preprint

View full text Add to dashboard Cite

The conventional millimeter wave systems are mostly designed to operate only for the Gaussian noise model. Although this model simplifies the noise removal problem, recent research findings state that a mixture noise model with additive impulsive noise is a more realistic approximation for millimeter wave channels. In this paper, we propose a novel approach to eliminate the impulsive noise effects on single-user millimeter wave massive multiple-input-multiple-output system using an adaptive fuzzy logic filter. Hence, a fuzzy median filter is applied to the system and it is aimed to minimize the effects of the impulsive noise by ordering samples based on fuzzy rank. Simulation results show that the proposed filter successfully eliminates the impulsive noise effects and achieves a better bit error rate and spectral efficiency performance than the competing methods in the literature while also working efficiently in Gaussian noise.

show abstract

Fuzzy Logic Based Decoder for Single-User Millimeter Wave Systems Under Impulsive Noise

Mulla

Rızaner

Ulusoy

2021

Wireless Pers Commun

View full text Add to dashboard Cite

Adaptive Demodulation in Class a Impulse Noise Channels

Cited by 4 publications

References 18 publications

Improving Log-Likelihood Ratio Estimation with Bi-Gaussian Approximation under Multiuser Interference Scenarios

Improving Log-Likelihood Ratio Estimation with Bi-Gaussian Approximation under Multiuser Interference Scenarios

Hybrid Decoder with an Adaptive Fuzzy Logic Filter for Single-User Millimeter Wave Systems Under Impulsive Noise

Fuzzy Logic Based Decoder for Single-User Millimeter Wave Systems Under Impulsive Noise

Contact Info

Product

Resources

About