| Paper ID | D3-S2-T2.2 |
| Paper Title |
Sparse Multi-Decoder Recursive Projection Aggregation for Reed-Muller Codes |
| Authors |
Dorsa Fathollahi, Institute of Science and Technology Austria, Austria; Nariman Farsad, Ryerson University, Canada; Seyyed Ali Hashemi, Stanford University, United States; Marco Mondelli, Institute of Science and Technology Austria, Austria |
| Session |
D3-S2-T2: Reed-Muller Codes |
| Chaired Session: |
Wednesday, 14 July, 22:20 - 22:40 |
| Engagement Session: |
Wednesday, 14 July, 22:40 - 23:00 |
| Abstract |
Reed-Muller (RM) codes are one of the oldest families of codes. Recently, a recursive projection aggregation (RPA) decoder has been proposed, which achieves a performance that is close to the maximum likelihood decoder for short-length RM codes. One of its main drawbacks, however, is the large amount of computations needed. In this paper, we devise a new algorithm to lower the computational budget while keeping a performance close to that of the RPA decoder. The proposed approach consists of multiple sparse RPAs that are generated by performing only a selection of projections in each sparsified decoder. In the end, a cyclic redundancy check (CRC) is used to decide between output codewords. Simulation results show that our proposed approach reduces the RPA decoder's computations by up to 80% with negligible performance loss.
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