Noisy Transmission Channels Research Articles

Adaptive Hybrid Bivariate Double Density Discrete and Complex Wavelet for Image Denoising

Image denoising is an important step in eliminating any noise impact in any image transmission process. Recently we presented two approaches for Bivariate based image denoising. They were Double Density Discrete Wavelet Transform (DD DWT) and Double Density Dual Tree Complex Wavelet Transform (DD CWT). In both techniques we decomposed noisy images with either DD DWT or DD CWT decompositions and then applied the Bivariate based denoising technique for noise removal. In this paper we propose an adaptive hybrid technique for Bivariate based image denoising that is based on the synthesis of DD-DWT bands or DD-CWT bands but with different weights, to deliver enhanced image features with less denoising impact especially around image edges, which is the most effected by noisy transmission channels. This proposed technique has been also enhanced by edge sharpening and Eigen analysis, as two separate stages. Simulation result comparisons have been performed between the proposed hybrid band adaptive DD-DWT and DD-CWT technique and the two primary techniques DD-DWT, DD- CWT, as well as other superior literature techniques such the original bivariate denoising technique with both original Complex Wavelet Transform and Double Density decompositions. This work in specific compares between Double Density DWT and Double Density CWT decompositions, proposes new filter design that suits each of them and proposes a hybrid technique between as will be shown.

Information reconstruction from noisy channel using ghost imaging method with spectral multiplexing in visible range

The ghost imaging technique allows us to recover information about an object in conditions of noisy transmission channels, commensurate with the intensity of the speckle structures involved in the reconstruction. One of the main disadvantages of this technique is relatively slow reconstruction speed. This limits its applicability for study of dynamic processes or fast-moving objects. In this paper, we propose a modification of the computational ghost imaging technique that allows us to overcome this limitation. It is shown that the spectral multiplexing of the speckle patterns speeds up the image reconstruction. Increase in the number of spectral channels from 4 to 10 leads to the increase of the signal-tonoise ratio by the factor of 6. Simultaneously, under the same conditions and with the same number of measurements classical monochrome ghost imaging does not reconstruct the picture at all. This makes the proposed technique attractive for high-speed demanding applications such as communications and remote sensing.

Basic Principles of Creating Control Algorithms for a Remotely Piloted Sea Vessel to Improve the Information Security of Noisy Data Transmission Channels

Basic Principles of Creating Control Algorithms for a Remotely Piloted Sea Vessel to Improve the Information Security of Noisy Data Transmission Channels

Teaching and Learning in Uncertainty

We investigate a simple model for social learning with two agents: a teacher and a student. The teacher's goal is to teach the student the state of the world; however, the teacher himself is not certain about the state of the world and needs to simultaneously learn this parameter and teach it to the student. We model the teacher's and student's uncertainties via noisy transmission channels, and employ two simple decoding strategies for the student. We focus on two teaching strategies: a “low-effort” strategy of simply forwarding information, and a “high-effort” strategy of communicating the teacher's current best estimate of the world at each time instant, based on his own cumulative learning. Using tools from large deviation theory, we calculate the exact learning rates for these strategies and demonstrate regimes where the low-effort strategy outperforms the high-effort strategy. Finally, we present a conjecture concerning the optimal learning rate for the student over all joint strategies between the student and the teacher.

Analyzing the decoding rate of circular coding in a noisy transmission channel

Embedding information into a printed image is useful in many aspects, in which reliable channel encoding/decoding systems are crucial, since there is information loss and error propagation during transmission. Circular coding is a general twodimensional channel coding method that allows data recovery with only a cropped portion of the code, and without the knowledge of the carrier image. While some traditional methods add redundancy bits to extend the length of the original massage length, this method embeds message into image rows in a repeated and shifted manner with redundancy, then uses the majority votes of the redundancy bits for recovery. In this paper, we developed a closed-form formula to predict its decoding success rate in a noisy channel under various transmission noise levels, using probabilistic modeling. The theoretical result is validated with simulations. This result enables the optimal parameter selection in the encoder and decoder system design, and decoding rate prediction with different levels of transmission error.

On Hypothesis Testing Against Conditional Independence With Multiple Decision Centers

A distributed binary hypothesis testing problem is studied with one observer and two decision centers. Achievable type-II error exponents are derived for testing against conditional independence when the observer communicates with the two decision centers over one common and two individual noise-free bit pipes and when it communicates with them over a noisy broadcast channel. The results are based on a coding and testing scheme that splits the observations into subblocks, so that transmitter and receivers can independently apply to each subblock either Gray-Wyner coordination coding with side-information or hybrid joint source-channel coding with side-information, followed by a Neyman-Pearson test over the subblocks at the receivers. This approach allows to avoid introducing further error exponents that one would expect from the receivers’ decoding operations related to binning or the noisy transmission channel. The derived exponents are shown to be optimal in some special cases when communication is over noise-free links. The results reveal a tradeoff between the type-II error exponents at the two decision centers.

Low Complexity Parity Check Code for Futuristic Wireless Networks Applications

The Internet of Things refers to the aptitude of remotely connecting and monitoring anything, anytime, and anywhere via futuristic wireless networks. Due to the unreliable wireless links, broadcast nature of wireless transmissions, interference and noisy transmission channels, frequent topology changes, and the various quality of wireless channel, there are challenges in providing high data rate service, high throughput, high packet delivery ratio, low end-to-end delay, and reliable services. In wireless network and real time application systems, low complexity and shorter codeword length in channel coding scheme are preferred. Consequently, in order to address these challenges, we propose a novel error detection and correction codes called the low-complexity parity-check (LCPC) codes with short codeword lengths for futuristic wireless networks applications. The proposed codes have less complexity and lower memory requirement in comparison to turbo and low-density parity-check (LDPC) codes. Simulation results demonstrated that the proposed LCPC codes outperform the Hamming and Reed–Solomon codes, in addition to the renowned LDPC codes. It offers up to 3-dB coding gain.

Composition Check Codes

We present composition check codes for noisy storage and transmission channels with unknown gain and/or offset. In the proposed composition check code, like in systematic error correcting codes, the encoding of the main data into a constant composition code is completely avoided. To the main data, a coded label is appended that carries information regarding the composition vector of the main data. Slepian’s optimal detection technique of codewords that are taken from a constant composition code is applied for detection. A first Slepian detector detects the label and subsequently restores the composition vector of the main data. The composition vector, in turn, is used by a second Slepian detector to optimally detect the main data. We compute the redundancy and error performance of the new method, and results of computer simulations are presented.

Best binary equivocation code construction for syndrome coding

Traditionally, codes are designed for an error correcting system to combat noisy transmission channels and achieve reliable communication. These codes can be used in syndrome coding, but it is shown in this study that the best performance is achieved with codes specifically designed for syndrome coding. In the view of the security of the communication, the best codes are the codes, which have the highest value of an information secrecy metric, the equivocation rate, for a given code length and code rate and are well packed codes. A code design technique is described, which produces the best binary linear codes for the syndrome coding scheme. An efficient recursive method to determine the equivocation rate for the binary symmetric channel and any linear binary code is also presented. A large online database of best equivocation codes for the syndrome coding scheme has been produced using the code design technique with some examples presented in the study. The presented results show that the best equivocation codes produce a higher level of secrecy for the syndrome coding scheme than almost all best known error correcting codes. Interestingly, it is unveiled that some outstanding best known error correcting codes are also best equivocation codes.

PERFORMANCE AND ANALYSIS OF REED-SOLOMAN CODES FOR EFFICIENT COMMUNICATION SYSTE

In wireless communication systems reducing bit/frame/symbol error rate is critical. If bit error rates are high then in wireless communication system our aim is to minimize error by employing various coding methods on the data transferred. Various channel coding for error detection and correction helps the communication system designers to reduce the effects of a noisy data transmission channel. In this paper our focus is to study and analysis of the performance of Reed-Solomon code that is used to encode the data stream in digital communication. The performances were evaluated by applying to different phase sift keying (PSK) modulation scheme in Noisy channel. Reed-Solomon codes are one of the best for correcting burst errors and find wide range of applications in digital communications and data storage. Reed-Solomon codes are good coding technique for error correcting, in which redundant information is added to data so that it can be recovered reliably despite errors in transmission or retrieval. The error correction system used is based on a Reed-Solomon code. These codes are also used on satellite and other communications systems.Â

An Evaluation of Coded Wavelet for Multicarrier Modulation with OFDM

Orthogonal frequency division multiplexing (OFDM) is pronounced in wireless communication systems. Methods for improving the performance of the OFDM-based systems are mostly sought. A method of doing this involves error correction coding and another, a better multicarrier modulation kernel. In this work, convolutional error correction coding with interleaving is introduced in wavelet multicarrier modulation OFDM system (wavelet-OFDM) to improve the performance of multicarrier systems as the signal traverses the multipath and noisy transmission channels. This is compared with FFT-based multicarrier modulation (FFT-OFDM). Results show that coded wavelet-OFDM saves more than a half of the transmit power than the uncoded wavelet. Also it will be shown that, the interleaved and non-interleaved coded wavelet-OFDM well outperform interleaved coded and non-interleaved coded FFT-OFDM systems respectively.

A New Approach for Detecting and Correcting Errors in the Satellite Communications Based on Hamming Error Correcting Code

This paper presents a novel model to detect and correct Single Event Upsets in on-board implementations of the AES algorithm, which is based on Hamming error correcting code. The encrypted satellite data can get corrupted before reaching the ground station due to various faults. One major source of faults is the harsh radiation environment, Therefore any electronic systems used on-board satellites such as processors, memories etc. are very susceptible to faults induced by radiation. Single Even Upset (SEU) faults can occur on-board during encryption due to radiation. A detailed analysis of the effect of SEUs on the imaging data during on-board encryption using the modes of AES is carried out. Faults in the data can also occur during transmission to the ground station due to noisy transmission channels. In this paper the impact of these faults on the data is discussed and compared for all the five modes of AES. From five modes of AES, CRT mode is selected to encrypt satellite video and image links. A detailed analysis of the effect of SEUs on the imaging data during on-board encryption using the modes of AES is carried out.

State Reconstruction for Complex Dynamical Networks with Noises

The state reconstruction problem is addressed for complex dynamical networks coupled with states and outputs respectively, in a noisy transmission channel. By using Lyapunov stability theory and H∞ performance, two schemes of state reconstruction are proposed for the complex dynamical networks with the nodes coupled by states and outputs respectively, and the estimation errors are convergent to zeros with H∞ performance index. A numerical simulation demonstrates the effectiveness of the proposed observers.

Bit Error Rate Analysis of ReedSolomon Code for Efficient Communication System

wireless, satellite, and space communication systems, reducing error is critical. High bit error rates of the wireless communication system require employing various coding methods on the data transferred. Channel coding for error detection and correction helps the communication system designers to reduce the effects of a noisy transmission channel. The purpose of this paper is to study and investigate the performance of Reed-Solomon code that is used to encode the data stream in digital communication. The performances were evaluated by applying to binary phase sift keying modulation scheme in symmetric Additive White Gaussian Noise channel. Reed-Solomon codes are best for correcting burst errors and find wide range of applications in digital communications and data storage. Keywords-Solomon codes (RS), Forward Error Correction (FEC), Additive White Gaussian Noise (AWGN), Binary Phase Shift Keying (BPSK).

Efficient strategy for sharing entanglement via noisy channels with doubly entangled photon pairs

Polarization-entangled photon pairs are easily perturbed in noisy channels. We propose an efficient strategy for sharing polarization-entangled photon pairs (PEPPs) using the additional frequency labels of polarization-frequency doubly entangled photon pairs (DEPPs). The DEPPs are used in transmission, followed by a two-step operation. In the first step, all the bit-flip noises are wiped off efficiently. In the second step, the frequency labels of the DEPPs are erased and the phase-flip noises are wiped off; thus PEPPs in the desired state are extracted. Theoretical analysis shows that this strategy has intrinsically high efficiency, which demonstrates that it has great potential in sharing entanglement via noisy transmission channels.

Codeword distinguishability in minimum diversity decoding

We re-take a coding-theoretic notion which goes back to Cl. Shannon: codeword distinguishability. This notion is standard in zero-error information theory, but its bearing is definitely wider and it may help to better understand new forms of coding, e.g., DNA word design. In our approach, the underlying decoding principle is very simple and very general: one decodes by trying to minimise the diversity (in the simplest case the Hamming distance) between a codeword and the output sequence observed at the end of the noisy transmission channel. Symmetrically and equivalently, one may use maximum-similarity decoders and codeword confusabilities. The operational meaning of codeword distinguishability is made clear by a reliability criterion, which generalises the well-known criterion on minimum Hamming distances for error-correction codes. We investigate the formal properties of distinguishabilities versus diversities; these two notions are deeply related, and yet essentially different. An encoding theorem is put forward; as a case study, we examine a channel of cryptographic interest.

Adaptive kernel-based equalization for non-stationary digital communications channels

It is well known that the optimal symbol decision equalizer for noisy digital transmission channels is generally non-linear. A previous work demonstrated the performance of the so-called Kernel Adaline non-linear classifier in application to these channels, whilst pointing out that the Kernel Adaline is not an adaptive machine and thus would suffer in use on non-stationary channels. Here, we review Kernel-LMS, an adaptive extension of the Kernel Adaline, and introduce Fast Kernel-LMS, a low-complexity approximation to the same. The algorithm is augmented to implement decision feedback, and the performance of the fast algorithm in solving some synthetic non-stationary channel equalization problems is then investigated.

Continuous variable teleportation as a quantum channel

A quantum channel consisting of continuous variable quantum teleportation based on the standard protocol is investigated. It is shown that a quantum channel for continuous variable teleportation by an aribitrary entangled state is equivalent to a generalized thermalizing channel. We also study the transmission of nonclassical states by a teleportation channel with a two-mode squeezed-vacuum state in a noisy environment. The transmisson performance is evaluated by using the Glauber-Sudarshan P function and the nonclassical depth. Finally, we compare the results obtained to those of a noisy direct transmission channel. It is shown that the teleportation channel performs better than the direct transmission channel in a certain region.

Selective pressures on genomes in molecular evolution

We describe the evolution of macromolecules as an information transmission process and apply tools from Shannon information theory to it. This allows us to isolate three independent, competing selective pressures that we term compression, transmission, and neutrality selection. The first two affect genome length: the pressure to conserve resources by compressing the code, and the pressure to acquire additional information that improves the channel, increasing the rate of information transmission into each offspring. Noisy transmission channels (replication with mutations) give rise to a third pressure that acts on the actual encoding of information; it maximizes the fraction of mutations that are neutral with respect to the phenotype. This neutrality selection has important implications for the evolution of evolvability. We demonstrate each selective pressure in experiments with digital organisms.

Entropy Analysis of Noise Contaminated Sequences

The entropy analysis of symbol sequences created by symbolic dynamics reveals temporal correlations present in the stationary dynamics. We investigate how noise, introduced in different ways, affects temporal correlations found in the logistic map at the period doubling accumulation point. The deterministic system under consideration yields a highly structured spectrum of conditional entropies. We will discuss how additive noise, parametric noise, a fluctuating cell boundary and a noisy transmission channel modify the unperturbed entropy spectrum.