Abstract
Polar codes are featured by their low encoding/decoding complexity for symmetric binary input-discrete memoryless channels. Recently, flexible generic Successive Cancellation List (SCL) decoders for polar codes were proposed to provide different throughput, latency, and decoding performances. In this paper, we propose to use polar codes with flexible fast-adaptive SCL decoders in Digital Video Broadcasting (DVB) systems to meet the growing demand for more bitrates. In addition, they can provide more interactive services with less latency and more throughput. First, we start with the construction of polar codes and propose a new mathematical relation to get the optimized design point for the polar code. We prove that our optimized design point is too close to the one that achieves minimum Bit Error Rate (BER). Then, we compare the performance of polar and Low-Density Parity Check (LDPC) codes in terms of BER, encoder/decoder latencies, and throughput. The results show that both channel coding techniques have comparable BER. However, polar codes are superior to LDPC in terms of decoding latency, and system throughput. Finally, we present the possible performance enhancement of DVB systems in terms of decoding latency and complexity when using optimized polar codes as a Forward Error Correction (FEC) technique instead of Bose Chaudhuri Hocquenghem (BCH) and LDPC codes that are currently adopted in DVB standards.
Highlights
More than a decade ago, polar codes have been introduced by Arikan as a Shannon limit capacity achieving codes for symmetric binary-input discrete memoryless channels.The main idea of polar codes is to create virtual synthetic polarized noise-free or pure-noisy channels from unpolarized likely independent channels
All the error performance, throughput and latency measurements have been obtained on a single core of an Intel i7-4510U Central Processing Unit (CPU), which is based on the Haswell architecture and is manufactured in 22 nm with a base clock frequency of 2 GHz and a maximum turbo frequency of
Results show that optimized polar codes achieve comparable bit error rate performance compared to Low-Density Parity Check (LDPC) code for different code rates, while being free of error floor
Summary
The main idea of polar codes is to create virtual synthetic polarized noise-free or pure-noisy channels from unpolarized likely independent channels. The polarized noise-free channels are used to carry the information bits, while the polarized pure-noisy channels are used to carry the known frozen bits [1]. Polar codes inherently support the adaptation of the code rate by changing only the number of frozen bits while using the same encoder and decoder [3]. It would be a good candidate for other communication systems and is worth investigating
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
