article · IEEE Transactions on Information Theory · 2011
Signal Codes: Convolutional Lattice Codes
Ofir Shalvi, Naftali Sommer, Meir Feder
Cited by 45Abstract and details only
Abstract
The coded modulation scheme proposed in this paper has a simple construction: an integer sequence, representing the information, is convolved with a fixed, continuous-valued, finite impulse response (FIR) filter to generate the codeword - a lattice point. Due to power constraints, the code construction includes a shaping mechanism inspired by precoding techniques such as the Tomlinson-Harashima filter. We naturally term these codes “convolutional lattice codes” or alternatively “signal codes” due to the signal processing interpretation of the code construction. Surprisingly, properly chosen short FIR filters can generate good codes with large minimal distance. Decoding can be done efficiently by sequential decoding or for better performance by bidirectional sequential decoding. Error analysis and simulation results indicate that for the additive white Gaussian noise (AWGN) channel, convolutional lattice codes with computationally reasonable decoders can achieve low error rate close to the channel capacity.
Cite this paper
Shalvi, O., Sommer, N., & Feder, M. (2011). Signal Codes: Convolutional Lattice Codes. IEEE Transactions on Information Theory, 57(8), 5203–5226. https://doi.org/10.1109/tit.2011.2158876
Shalvi, Ofir, et al. “Signal Codes: Convolutional Lattice Codes.” IEEE Transactions on Information Theory, vol. 57, no. 8, 2011, pp. 5203–26, https://doi.org/10.1109/tit.2011.2158876.
Shalvi, Ofir, Naftali Sommer, and Meir Feder. 2011. “Signal Codes: Convolutional Lattice Codes.” IEEE Transactions on Information Theory 57 (8): 5203–26. https://doi.org/10.1109/tit.2011.2158876.
Shalvi, O., Sommer, N. and Feder, M. (2011) ‘Signal Codes: Convolutional Lattice Codes’, IEEE Transactions on Information Theory, 57(8), pp. 5203–5226. Available at: https://doi.org/10.1109/tit.2011.2158876.
@article{shalvi2011signal,
title = {{Signal Codes: Convolutional Lattice Codes}},
author = {Shalvi, Ofir and Sommer, Naftali and Feder, Meir},
journal = {IEEE Transactions on Information Theory},
volume = {57},
number = {8},
pages = {5203--5226},
year = {2011},
doi = {10.1109/tit.2011.2158876}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.
Related papers
Decoding of woven convolutional codes and simulation results
Ralph Jordan, Walter Schnug, Martin Bossert et al. · IEEE International Symposium on Information Theory (ISIT) · 2002
Cited by 0Open access
Hyperimposed convolutional codes
J.-F. Cheng · International Conference on Communications · 2002
Cited by 10
A repeat request strategy based on sliding window decoding of convolutional codes
Jürgen Freudenberger, Martin Bossert, Sergo Shavgulidze · IEEE International Symposium on Information Theory (ISIT) · 2004
Cited by 1
An expurgation upper bound on the probability of correct path loss for list decoding of time-invariant convolutional codes
Rolf Johannesson, Kamil Sh. Zigangirov · IEEE International Conference on Communication Technology (ICCT) · 2002
Cited by 0Open access
A repeat request strategy based on sliding window decoding of unit-memory convolutional codes
Jürgen Freudenberger, Sergo Shavgulidze · IEEE Transactions on Information Theory · 2006
Cited by 1
On Convolutional Coupled Codes
Slim Chaoui · AEU - International Journal of Electronics and Communications · 2004
Cited by 3Open access
Deficient decoding for convolutional codes
Takeshi Hashimoto, Suguru Arimotos · Electronics and Communications in Japan (Part I Communications) · 1980
Cited by 1
Convolutional Codes and Turbo‐Codes
Sergei Semenov, Andrey D. Trofimov · Wiley eBooks · 2010
Cited by 0