Impulse noise

About: Impulse noise is a research topic. Over the lifetime, 4816 publications have been published within this topic receiving 63970 citations.

Robust and high-bit rate communications over PLC channels: a bit-loading multi-carrier spread-spectrum solution

Abstract: In this paper, we present a finite-granularity loading algorithm for multicarrier spread-spectrum modulation systems. The proposed scheme attempts to give a robust solution to the power line communication challenging task. Throughout the paper, the particular case of an adapted version of multi-carrier code-division-multiple-access (MC-CDMA) is considered, which is currently called spread-spectrum multicarrier multiple-access (SS-MC-MA). The presented algorithm assigns subcarriers, spreading codes, bits and energy per code to each user of the network in order to maximize the minimum data rate at a target symbol error rate (SER) and for a given power spectral density (PSD). Simulation results of the new scheme are presented for different measured PLC channels with impulsive noise and are compared with those of the classical discrete multitone modulation (DMT) approach. Then, it is shown that the proposed scheme offers higher throughput than DMT or less sensitiveness to impulse noise effects.

Methods and systems for adaptive communication

Abstract: One embodiment of the present invention relates to a method of transferring data in a communication system. In the method, an initial impulse noise protection value is determined. A number of redundancy bits is added to blocks of data to form codewords as a function of the initial impulse noise protection value, where the impulse noise protection value corresponds to a number of consecutive symbols that can be corrected. The number of symbols that can be correctly transmitted is changed by changing only the number of redundancy bits added to each block of data.

Iterative median filtering for restoration of images with impulsive noise

Abstract: Iterative median filtering for restoration of images corrupted by impulsive noise is considered. A modified version of median filtering that can be also applied iteratively is also proposed. The methods are compared with an iterative method suggested by Marvasti for images with high pixel loss. The results show that applying the median filter iteratively results in well sighted resulting images. Moreover, despite the implementation simplicity, the proposed modified median filtering scheme provides a considerably higher convergence speed which intends a lower numerical complexity.

Excess noise generation during spectral broadening in a microstructured fiber

Abstract: We observe that nanojoule femtosecond pulses that are spectrally broadened in a microstructured fiber acquire excess noise. The excess noise is manifested as an increase in the noise floor of the rf spectrum of the photocurrent from a photodetector illuminated by the pulse train from the laser oscillator. Measurements are made of the intensity dependence of the excess noise for both 100 fs and sub-10 fs pulses. The excess noise is very strong for 100 fs pulses, but barely measurable for sub-10 fs pulses. A rigorous quantum treatment of the nonlinear propagation of ultrashort pulses predicts that, for a fixed generated bandwidth, the amount of excess noise decreases with pulse duration, in agreement with the experimental results.

On the Development of a New Adaptive Channel Equalizer using Bacterial Foraging Optimization Technique

Abstract: High speed data transmission over communication channels distort the transmitted signals in both amplitude and phase due to presence of inter symbol interference (ISI) Other impairments like thermal noise, impulse noise and cross talk also cause further distortions to the received symbols Adaptive equalization of the digital channels at the receiver removes/reduces the effects of such ISIs and attempts to recover the transmitted symbols The multilayer perceptron (MLP), fuzzy logic (FL) and radial basis function (RBF) based equalizers are relatively new soft computing based equalizers which aim to minimize the ISI present in the channels particularly for nonlinear channels However they suffer from long training time and undesirable local minima In the present paper we propose a new adaptive channel equalizer using a novel bacterial foraging optimization (BFO) technique which is essentially a derivative free optimization tool This algorithm has been suitably used to update the weights of the equalizer The performance of the proposed equalizer has been evaluated and has been compared with its LMS based counter part It is observed that the new equalizer offers improved performance both in terms of rate of convergence as well as bit-error-rate