2020 IEEE International Symposium
on Information Theory
21-26 June 2020 • Los Angeles, California, USA
| Paper ID | C.2.3 | ||
| Paper Title | Low-Complexity Chase Decoding of Reed-Solomon Codes through Basis Reduction | ||
| Authors | Jiongyue Xing, Li Chen, Sun Yat-sen University, China; Martin Bossert, Ulm University, Germany | ||
| Session | C.2: Coding for Communications II | ||
| Presentation | Lecture | ||
| Track | Coding for Communications | ||
| Manuscript | Click here to download the manuscript | ||
| Virtual Presentation | Click here to watch in the Virtual Symposium | ||
| Abstract | This paper proposes the low-complexity Chase (LCC) decoding using basis reduction (BR) interpolation for Reed-Solomon (RS) codes, namely the LCC-BR algorithm. With received soft information, a number of decoding test-vectors are formulated. The LCC-BR algorithm first constructs a common basis which will be utilized by the following individual basis constructions of all test-vectors. This eliminates the redundant computation in BR interpolation, resulting in a low decoding complexity. Moreover, the LCC-BR algorithm can decode each test-vector in parallel, lowering the decoding latency. This paper further proposes the progressive LCC-BR (PLCC-BR) algorithm that decodes the test-vectors sequentially and terminates once the intended message is found. This progressive decoding is realized without additional memory cost. Simulation results show the complexity and latency advantages of the proposed algorithms over the other benchmark algorithms. | ||
Plan Ahead
2021 IEEE International Symposium on Information Theory
11-16 July 2021 | Melbourne, Victoria, Australia
