Name
Abstract | ||
|---|---|---|
Linear layered probabilistic shaping (LLPS) is proposed, an architecture for linear codes to efficiently encode to shaped code words. In the previously proposed probabilistic amplitude shaping (PAS) architecture, a distribution matcher (DM) maps information bits to shaped bits, which are then systematically encoded by appending uniformly distributed parity bits. LLPS extends PAS by probabilistic parity shaping (PPS), which uses a syndrome DM to calculate shaped parity bits. LLPS enables the transmission with any desired distribution using linear codes, furthermore, by LLPS, a given linear code with rate $R_text{fec}$ can be operated at any rate $Rleq R_text{fec}$ by changing the distribution. LLPS is used with an LDPC code for dirty paper coding against an interfering BPSK signal, improving the energy efficiency by 0.8 dB. |
Year | Venue | DocType |
|---|---|---|
2019 | arXiv: Information Theory | Journal |
Volume | Citations | PageRank |
abs/1902.10648 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Georg Böcherer | 1 | 169 | 25.87 |
| Diego Lentner | 2 | 0 | 0.68 |
| Alessandro Cirino | 3 | 0 | 0.34 |
| Fabian Steiner | 4 | 65 | 11.68 |