Visible to the public "Parallel secure turbo code for security enhancement in physical layer"Conflict Detection Enabled

Title"Parallel secure turbo code for security enhancement in physical layer"
Publication TypeConference Paper
Year of Publication2015
AuthorsA. Motamedi, M. Najafi, N. Erami
Conference Name2015 Signal Processing and Intelligent Systems Conference (SPIS)
Date PublishedDec
PublisherIEEE
ISBN Number978-1-5090-0139-2
Accession Number15824128
KeywordsBit error rate, buffering latency, channel coding, code words, communication system, concurrent kernel execution, CUDA, Decoding, distribute decoding load, error statistics, general-purpose graphics processing units, GPU, graphics processing units, joint channel-security coding system, memory access improvement, multiple cores, parallel processing, parallel secure turbo code, parallelism, Physical layer, pubcrawl170102, secure decoding algorithm, security, security enhancement, Throughput, Turbo code, turbo codes
Abstract

Turbo code has been one of the important subjects in coding theory since 1993. This code has low Bit Error Rate (BER) but decoding complexity and delay are big challenges. On the other hand, considering the complexity and delay of separate blocks for coding and encryption, if these processes are combined, the security and reliability of communication system are guaranteed. In this paper a secure decoding algorithm in parallel on General-Purpose Graphics Processing Units (GPGPU) is proposed. This is the first prototype of a fast and parallel Joint Channel-Security Coding (JCSC) system. Despite of encryption process, this algorithm maintains desired BER and increases decoding speed. We considered several techniques for parallelism: (1) distribute decoding load of a code word between multiple cores, (2) simultaneous decoding of several code words, (3) using protection techniques to prevent performance degradation. We also propose two kinds of optimizations to increase the decoding speed: (1) memory access improvement, (2) the use of new GPU properties such as concurrent kernel execution and advanced atomics to compensate buffering latency.

URLhttps://ieeexplore.ieee.org/document/7422336
DOI10.1109/SPIS.2015.7422336
Citation Key7422336