Design of Soft Viterbi Algorithm Decoder Enhanced With Non-Transmittable Codewords for Storage Media

Viterbi Algorithm Decoder Enhanced with Non-transmittable Codewords is one of the best decoding algorithm which effectively improves forward error correction performance. HoweverViterbi decoder enhanced with NTCs is not yet designed to work in storage media devices. Currently Reed Solomon (RS) Algorithm is almost the dominant algorithm used in correcting error in storage media. Conversely, recent studies show that there still exist low reliability of data in storage media while the demand for storage media increases drastically. This study proposes a design of the Soft Viterbi Algorithm decoder enhanced with Non-transmittable Codewords (SVAD-NTCs) to be used in storage media for error correction. Matlab simulation was used in this design in order to investigate behavior and effectiveness of SVAD-NTCs in correcting errors in data retrieving from storage media.Sample data of one million bits are randomly generated, Additive White Gaussian Noise (AWGN) was used as data distortion model and Binary Phase- Shift Keying (BPSK) was applied for simulation modulation. Results show that,behaviors of SVAD-NTC performance increase as you increase the NTCs, but beyond 6NTCs there is no significant change and SVAD-NTCs design drastically reduce the total residual error from 216,878 of Reed Solomon to 23,900

Bandwidth Aware FEC Algorithms for Wireless Communication Systems

Forward Error Correction (FEC) codes used by receivers to correct transmission errors without retransmission add a considerable amount of redundant bits to data bits. The addition of redundant bits lowers the overall network throughput, thus increasing the demand for more required bandwidth. In this paper we investigate and discuss various techniques used in FEC and show their effects to data communication in terms of bandwidth utilization. Additionally we propose improvement of (2, 1, 2) Convolutional encoder to (3, 2, 3) encoder. The proposed improvements increase the code rate from 1/2 to 2/3 hence reducing error control information and increasing bit rate. The received codeword can be decoded by Soft-Output Viterbi Algorithm. Keywords: FEC, Bandwidth, Convolutional Codes, Code Rate, Soft Output Viterbi Algorith

Performance of Soft Viterbi Decoder enhanced with Non-Transmittable Codewords for storage media

The introduction of Non-Transmittable Codewords (NTCs) into Viterbi Algorithm Decoder has emerged as one of the best ways of improving performance of the Viterbi Algorithm Decoder. However, the performance has been tested only in hard decision Viterbi Decoder in telecommunication systems, but not in soft decision Viterbi Decoder and storage media. Most storage media use Reed Solomon (RS) Algorithm Decoder. Yet, the field experience still shows failure of the algorithm in correcting burst errors in reading data from the storage media; leading into data loss. This paper introduces the Soft Viterbi Algorithm Decoding enhanced with Non-Transmittable Codewords for storage media. Matlab software was used to simulate the algorithm and the performance was measured by comparing residual errors in a data length of one million bits. Additive White Gaussian Noise model was applied to distort the stored data. The performance comparison was made against the Reed Solomon code, Normal Soft Viterbi and Hard decision Viterbi enhanced with NTCs. The results showed that the Soft Viterbi Algorithm enhanced with NTCs performed remarkably better by 88.98% against RS, 84.31% against Normal Soft Viterbi and 67.26% against Hard Viterbi enhanced with NTCs

Forward Error Correction for Storage Media: An Overview

Research Article published byInternational Journal of Computer Science and Information Security (IJCSIS), Vol. 13, No. 12, December 2015As the adoption of Information and Communication Technology (ICT) tools in production and service rendering sectors increases, the demand for digital data storage with large storage capacity also increases. Higher storage media systems reliability and fault tolerance are among the key factors that the existing systems sometimes fail to meet and therefore, resulting into data loss. Forward error correction is one of the techniques applied to reduce the impact of data loss problem in digital data storage. This paper presents a survey conducted in different digital data storage companies in Dar es Salam, Tanzania. Data were collected and analyzed using Statistical Package for Social Sciences (SPSS). Secondary data were captured from user and manufacturer technical reports. It was revealed that data loss is still a predominant challenge in the digital data storage industry. Therefore, the study proposes the new storage media FEC model using locked convolutional encoder with the enhanced NTCViterbi decoder

A review on deep learning aided pilot decontamination in massive MIMO

AbstractIn multi-antenna systems, advanced techniques such as massive multiple-input multiple-output (MIMO), beamforming, and beam selection depend heavily on the accurate acquisition of the channel state. However, pilot contamination (PC) can be a major source of interference which degrades they are performance. Moreover, the severity of PC increases as more pilots are reused between users in the wireless systems. Researchers have shown that PC can be mitigated by using deep learning (DL) approaches. Nevertheless, when minimizing PC, the examination that identifies the applications and factors that distinguish these DL approaches is still limited. This paper reviews these DL approaches and the improvements needed to enhance their performance. Simulation results confirm that DL networks that learn to predict the channels directly have superior performance under PC