Transmission Error Correction Research Articles

Theory and practice of hull dynamic deformation law and heading angle transfer error correction

In order to meet the demand of high-precision heading angle transmission in the transfer alignment of inertial navigation system on moving base, the analytical function relationship between the hull deformation and the turning angular velocity and angular acceleration was derived by using the classical beam theory based on the analysis of the equivalent load exerted by the hydrodynamic force and inertia force on the hull structure during the turning process under the combined action of the steering rudder moment and wave force. The objective law between the angular motion and the azimuth deformation angle of the hull under the combined action of maneuvering and sea waves was revealed. Finally, the correction coefficients were determined according to the left turn and right turn motions of the hull by using the measured data of the ship in the sea trial during the S-shape maneuvering navigation, and the azimuth deformation angle correction was completed. The results indicated that the application of the Qu's bending deformation correction formula could greatly reduce the influence of the hull flexural deformation on the heading angle accuracy, meet the needs of high-precision heading angle transmission, and fully verify the correctness of the hull azimuth deformation law and the heading angle transmission error correction theory. This theory and method provided technical support for establishing high-precision distributed digital reference in the field of transfer alignment of inertial navigation on moving base and the application of heading angle transfer of other shipborne equipment.

Secure and Efficient Video Transmission in VANET

Currently, vehicular communications have become a reality used by various applications, especially applications that broadcast video in real time. However, the video quality received is penalized by the poor characteristics of the transmission channel (availability, non-stationarity, the ration of signal-to-noise, etc.). To improve and ensure minimum video quality at reception, we propose in this work a mechanism entitled “Secure and Efficient Transmission of Videos in VANET (SETV)”. It's based on the "Quality of Experience (QoE)" and using hierarchical packet management. This last is based on the importance of the images of the stream video. To this end, the use of transmission error correction with uneven error protection has proven to be effective in delivering high quality videos with low network overhead. This is done based on the specific details of video encoding and actual network conditions such as signal to noise ratio, network density, vehicle position and current packet loss rate (PLR) not to mention the prediction of the future DPP.Machine learning models were developed on our work to estimate perceived audio-visual quality. The protocol previously gathers information about its neighbouring vehicles to perform distributed jump reinforcement learning. The simulation results obtained for several types of realistic vehicular scenarios show that our proposed mechanism offers significant improvements in terms of video quality on reception and end-to-end delay compared to conventional schemes. The results prove that the proposed mechanism has showed 11% to 18% improvement in video quality and 9% load gain compared to ShieldHEVC.

Secure and Efficient Video Transmission in VANET

Currently, vehicular communications have become a reality used by various applications, especially applications that broadcast video in real time. However, the video quality received is penalized by the poor characteristics of the transmission channel (availability, non-stationarity, the ration of signal-to-noise, etc.). To improve and ensure minimum video quality at reception, we propose in this work a mechanism entitled “Secure and Efficient Transmission of Videos in VANET (SETV)”. It's based on the Quality of Experience (QoE) and using hierarchical packet management. This last is based on the importance of the images of the stream video. To this end, the use of transmission error correction with uneven error protection has proven to be effective in delivering high quality videos with low network overhead. This is done based on the specific details of video encoding and actual network conditions such as signal to noise ratio, network density, vehicle position and current packet loss rate (PLR) not to mention the prediction of the future DPP. Machine learning models were developed on our work to estimate perceived audio-visual quality. The protocol previously gathers information about its neighbouring vehicles to perform distributed jump reinforcement learning. The simulation results obtained for several types of realistic vehicular scenarios show that our proposed mechanism offers significant improvements in terms of video quality on reception and end-to-end delay compared to conventional schemes. The results prove that the proposed mechanism has showed 11% to 18% improvement in video quality and 9% load gain compared to ShieldHEVC.

Analysis of the interaction between linear cyclic error correcting codes and self-synchronous payload scramblers

In order to protect public network data transmission from potential Layer 1 attacks by malicious users, self-synchronous scramblers have come into widespread use. Such networks include those using ATM, packet over SONET (POS), and the new generic framing procedure (GFP). Unfortunately, feedback taps inherent in self-synchronous descramblers cause multiplication of transmission errors, which in turn degrades the performance of most linear cyclic error detection/correction codes. This paper analyzes this scrambler/code interaction with respect to the resulting probability of undetectable errors and transmission error correction capability. The theoretical criteria are derived for a linear cyclic code to maintain its error detection and correction performance in the presence of the scramblers. A novel approach for improving the error correction capabilities is also presented.

Network protocols

While the construction of Hamming Codes that can detect and correct 1-bit transmission errors has been illustrated [1], Hamming Codes that will detect and correct transmission errors of more than 1 bit remain yet to be constructed. In this paper, how to build Group Codes that can correct transmission errors of up to 2 bits will be shown. Note that transmission control protocols such as TCP/IP rely upon the notion of checksums", a variation of Hamming Codes, for their transmission error correction. The ease and efficiency with which the group codes can be built will then be compared to those of Hamming Codes and Cyclic Redundancy Checking, the transmission error detection/correction schemes discussed in [1].

Detection and correction of transmission errors in JPEG images

The detection and correction approach to transmission errors in JPEG images using the sequential discrete cosine transform (DCT)-based mode of operation is proposed. The objective is to eliminate transmission errors in JPEG images. Here a transmission error may be either a single-bit error or a burst error containing N successive error bits. For an entropy-coded JPEG image, a single transmission error in a codeword will not only affect the underlying codeword, but may also affect subsequent codewords. Consequently, a single error in an entropy-coded system may result in a significant degradation. To cope with the synchronization problem, in the proposed approach the restart capability of JPEG images is enabled, i.e., the eight unique restart markers (synchronization codewords) are periodically inserted into the JPEG compressed image bitstream. Transmission errors in a JPEG image are sequentially detected both when the JPEG image is under decoding and after the JPEG image has been decoded. When a transmission error or equivalently a corrupted restart interval is detected, the proposed error correction approach simply performs a sequence of bit inversions and redecoding operations on the corrupted restart interval and selects the "best" feasible redecoding solution by using a proposed cost function for error correction. The proposed approach can recover high-quality JPEG images from the corresponding corrupted JPEG images at bit error rates (BERs) up to approximately 0.4%. This shows the feasibility of the proposed approach.

Detection and correction of transmission errors in pyramid images

Detection and correction of transmission errors in pyramid images

Detection and correction of transmission errors in facsimile images

Today, facsimile is recognized as the primary communication tool for both printed and written materials. Most facsimile machines operating on public switched telephone networks use the Group 3 (G3) facsimile compression standards, in which images are entropy-coded. Although the synchronization codeword end of line (EOL) is employed, a transmission error in a codeword may cause the current codeword, the subsequent codewords in the current line, even the codewords in the subsequent lines to be misinterpreted, resulting in a great degradation of the received image. The objective of the proposed error detection and correction approaches is to completely or partially eliminate transmission errors in G3 facsimile images, requiring no extra transmission bit rate and without changing the transmitter and the receiver. The proposed approaches are based on the error checking conditions derived from the relationship between the current line and the previous line as well as the constraints on compressed image data. A corrupted line is detected if any of the error checking conditions is satisfied. When a corrupted line is detected, a sequence of bit inversions and redecoding operations are performed on the current corrupted line and/or its previous lines so that at least one possible (feasible) redecoding solution can be found. Then, the best solution is selected by using some selection criterion. Based on simulation results, the proposed approaches can recover the original or high-quality facsimile images from their corresponding corrupted facsimile images. This shows the feasibility of the proposed approaches.

Detection and correction of transmission errors in DPCM images

A new approach to detection and correction of transmission errors in DPCM images is proposed. Here each transmission error (streak noise) is detected via a sequence of the Wilcoxon-Mann-Whitney (WMW) rank-sum tests performed on a sliding window using four particularly designed grouping schemes. Instead of four possible patterns used by Kundu and Wu (1990), in the proposed approach 18 possible detection patterns represented as a decision tree are identified. The transmission error detection procedure is equivalent to tracing the decision tree. The estimated gray level shift of a detected streak noise is used to locate the streak origin. Then instead of using previous line replacement, each streak noise can be almost deleted by compensating the corrupted pixels with the estimated gray level shift. Experimental results show the feasibility of the proposed approach.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Neural network error corrector for binary messages on hydro-acoustic channels

An application of neural networks for the identification and correction of transmission errors in binary messages is described. The network is used as a classifier of detected hydroacoustic signals. It converts the signals into one of a possible alphabet of symbols. The algorithm used is a Hamming-type neural network classifier associated with the transmission of a Hamming code. This system can detect and correct all transmission errors if the number of errors is less than or equal to half the Hamming distance between transmitted symbols minus one. Symbols to be transmitted are chosen and associated to messages, assuring that bit-to-bit nonsimilarities result on the prescribed Hamming distance. The auto-associative error correcting scheme can be used to generate a teaching signal to a supervised learning equalizer tracking the channel nonstationary characteristics. The proposed system is intended for use in hydroacoustic communication applications and is undergoing sea tests. >

DPCM with Forced Updating and Partial Correction of Transmission Errors

A speech signal is dpcm (differential pulse code modulation) encoded at the sampling rate f <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</inf> and also pcm encoded at a rate f <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</inf> /W. Blocks of W dpcm words and one pcm word are transmitted. The receiver compares the decoded dpcm signal at the end of every block with the decoded pcm sample. If the difference is above a threshold, it is assumed that one error exists within the block, and a search is made for the erroneous dpcm code word. Correction is accomplished by inverting the bits in this code word until the difference is below the threshold. Whether or not the error is corrected, the dpcm signal at the end of the block is forced to the value of the pcm sample, thereby preventing error propagation outside the block. The system improves segmental s/n ratio by 7 dB for W = 64 and bit error rates between 0.1 and 0.5 percent Larger improvements are available with smaller block sizes. In the absence of transmission errors, there is no perceptible distortion due to the correction system.

Adaptive difference detection and correction system for partial correction of transmission errors in linear p.c.m.

An adaptive version of the difference detection and correction system for the partial removal of transmission errors in linear p.c.m. speech without the use of channel coding is presented. The improvement in s.n.r. compared to the nonadaptive system is approximately 3 dB for transmission bit error-rates between 0.5 and 5%.

Partial correction of transmission errors in Walsh transform image without recourse to error correction coding

A sequency difference detection and correction (s.d.d.c.) system is described which enables the partial correction of transmission errors in a Walsh-Hadamard transform image to be achieved without channel coding. Using a first-order two-dimensional random Gaussian Markov field as the image, the percentage mean-square error in the recovered signal is reduced with the aid of the s.d.d.c. system by two orders of magnitude for transmission error rates <3%.

Partial correction of transmission errors in d.p.c.m. without recourse to error correction coding

A method for partially correcting transmission errors in a 1st-order d.p.c.m. system, without recourse to channel coding, is described. A simple detection algorithm based on the statistical properties of a sequence of differences between adjacent samples of a modified decoded sequence is used to identify the erroneous samples. Three different correcting algorithms are described. Substantial improvements in the decoded waveform are achieved, and, for a Markov input process, an error rate of 0.04% in the first and second most significant digits, an improvement in s.n.r. of 7dB is achieved.