Name
Abstract | ||
|---|---|---|
Similar to the belief propagation decoder, linear programming decoding based on the alternating direction method of multipliers (ADMM) can also be seen as an iterative message-passing decoding algorithm. How to schedule messages efficiently is an important aspect since it will influence the convergence rate of iterative decoders. In this letter, we investigate the node-wise scheduling for ADMM decoders, named NS-ADMM. In particular, we propose a reduced-complexity method for the NS-ADMM decoder by avoiding Euclidean projections involved in the calculation of message residuals. Simulation results show that the proposed method converges much faster than the flooding and layered scheduling while keeping a lower complexity when compared with the NS-ADMM decoder. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/LCOMM.2016.2643629 | IEEE Communications Letters |
Keywords | Field | DocType |
Decoding,Iterative decoding,Complexity theory,Convergence,Signal to noise ratio,Indexes | Convergence (routing),Sequential decoding,Computer science,Scheduling (computing),Low-density parity-check code,Real-time computing,Rate of convergence,Decoding methods,List decoding,Belief propagation | Journal |
Volume | Issue | ISSN |
21 | 3 | 1089-7798 |
Citations | PageRank | References |
4 | 0.44 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaopeng Jiao | 1 | 38 | 9.90 |
| Jianjun Mu | 2 | 41 | 10.63 |
| Haoyuan Wei | 3 | 9 | 0.92 |