Error Control Mechanism Based on Reed-Solomon Code for Wireless Networks

The reliability of information transmission has a significant influence on network performance, so it has attracted extensive attention from researchers. Many error control mechanisms have been designed and proposed in order to improve the reliability of transmission. However, during transmission in wireless networks, high bit error rate and burst errors often occur, which poses great challenges in the design of error control mechanisms. The existing mechanisms suffer from a problem of either poor error correction ability or waste of network resources. The primary aim of this study is to develop an error control mechanism based on Reed-Solomon (RS) codes, which encodes packets using RS codes, and a re-encoding algorithm is designed for reducing the coded packet length. The proposed error control mechanism can not only reduce the number of redundant bits in the transmission process but also improve the error correction ability as much as possible when burst errors occur. Therefore, both the error correction ability and the network utility are considered in this work. The proposed mechanism was verified by experiments using the NS2 simulator. The experimental results verified the error control ability and throughput performance of the proposed mechanism.

An Optimal Transport Based Transferable System for Detection of Erroneous Somato-Sensory Feedback from Neural Signals

This study is aimed at the detection of single-trial feedback, perceived as erroneous by the user, using a transferable classification system while conducting a motor imagery brain–computer interfacing (BCI) task. The feedback received by the users are relayed from a functional electrical stimulation (FES) device and hence are somato-sensory in nature. The BCI system designed for this study activates an electrical stimulator placed on the left hand, right hand, left foot, and right foot of the user. Trials containing erroneous feedback can be detected from the neural signals in form of the error related potential (ErrP). The inclusion of neuro-feedback during the experiments indicated the possibility that ErrP signals can be evoked when the participant perceives an error from the feedback. Hence, to detect such feedback using ErrP, a transferable (offline) decoder based on optimal transport theory is introduced herein. The offline system detects single-trial erroneous trials from the feedback period of an online neuro-feedback BCI system. The results of the FES-based feedback BCI system were compared to a similar visual-based (VIS) feedback system. Using our framework, the error detector systems for both the FES and VIS feedback paradigms achieved an F1-score of 92.66% and 83.10%, respectively, and are significantly superior to a comparative system where an optimal transport was not used. It is expected that this form of transferable and automated error detection system compounded with a motor imagery system will augment the performance of a BCI and provide a better BCI-based neuro-rehabilitation protocol that has an error control mechanism embedded into it.

Error Control Mechanism Based on Reed-Solomon Code for Wireless Networks

The reliability of information transmission has a significant influence on network performance, so it has attracted extensive attention from researchers. Many error control mechanisms have been designed and proposed in order to improve the reliability of transmission. However, during transmission in wireless networks, high bit error rate and burst errors often occur, which poses great challenges in the design of error control mechanisms. The existing mechanisms suffer from a problem of either poor error correction ability or waste of network resources. The primary aim of this study is to develop an error control mechanism based on Reed-Solomon (RS) codes, which encodes packets using RS codes, and a re-encoding algorithm is designed for reducing the coded packet length. The proposed error control mechanism can not only reduce the number of redundant bits in the transmission process but also improve the error correction ability as much as possible when burst errors occur. Therefore, both the error correction ability and the network utility are considered in this work. The proposed mechanism was verified through theoretic analysis and by experiments using the NS2 simulator. The experimental results verified the error control ability and throughput performance of the proposed mechanism.

Cross Layer Design based Hybrid Error Control for Packet Aggregation over WSN

In general sensor networks have a wide range of application and also play a major role in developing precision and timely information. Mostly it deals with real world applications and in many cases the data sensed by the nodes should deliver within the time constriction. Meeting the deadlines is mandate for the applications and the data should be processed as soon as possible and without major data losses. The objective of this scheme is to collect data with high accuracy and low latency. Collecting and processing the data by means of aggregation will greatly reduce the congestion data rate. Cross Layer Design based Hybrid Error Control (CLDHEC) mechanism is proposed for reducing error rate occurred in sensor network which includes formation of network, data aggregation and transmission. Error control technique named Adaptive Forward Error Correction is used to defend the video transmission by recovering source information losses. FEC mechanism along with packet range control greatly increases the FEC efficiency in wireless networks. The service quality for different kind of data can be improved by lessening error rate using adaptive error control mechanism with cross layered design during packet aggregation.

Literature Review on High Definition Image Error Concealment

This paper is give us a overview of Error control method used in image or video transmission. Data in transmission is lost due to link failure or due to congestion and loss in packets, so the aim of this method is to protect data from these errors. Error detection coding and Error correction coding are two types of error control mechanism. Some of the error control mechanisms are Retransmission, Forward error correction, error concealment and error resilience. We are discussing a summary of three methods and Error Concealment in details.

Heuristic Localization Algorithm with a Novel Error Control Mechanism for Wireless Sensor Networks with Few Anchor Nodes

A novel iterative localization algorithm with high accuracy and low anchor node dependency for large-scale wireless sensor networks is proposed in this paper. At each iteration, blind nodes are located using a weighted linear least squares-based algorithm. To prevent errors in the blind nodes from propagating and accumulating throughout the network, an anchor geometric feature-based error control mechanism is used to select the nodes that participate in the localization and to estimate the localization confidence. The simulation results show that the algorithm can be used when only a few anchor nodes are involved. This algorithm is more advanced than traditional methods, which often require a large number of well-placed anchor nodes to operate appropriately. By optimizing the decision parameter v of the algorithm, the average localization error of the algorithm is approximately 0.43 meters. When the ratio of anchor nodes (the ratio of the number of anchor nodes to the number of sensor nodes in the network) is 1.25% (i.e., 5 anchor nodes for 400 sensor nodes), the received signal strength indicator (RSSI) variance is 8 dBm, and the radio range is 50 meters. A comparison of the proposed algorithm with global localization methods, including multidimensional scaling (MDS), semidefinite programming (SDP), and shortest-path access (SPA), shows that the proposed algorithm achieves higher location accuracy and stability when the number of anchor nodes is varied. The efficiency of the proposed localization algorithm is evaluated in a real sensor network, and the accuracy is high and robust to radio channel variance.