Selected papers by E. Agrell and his colleagues are here supplemented by software, data files, and errata. The resources may be freely copied, used, and modified, provided that the source is acknowledged.
The software is carefully tested and we believe it to be accurate, but in the unlikely case that something goes wrong when you use it, we take no responsibility.
| Paper | Format | Supplementary material | Description |
|---|---|---|---|
| E. Agrell and T. Eriksson,
“Optimization of lattices for quantization,”
IEEE Trans. Inform. Theory,
vol. 44, no. 5, pp. 1814–1828, Sept. 1998.
DOI, Chalmers repository |
Text | Data | Generator matrices of 90 lattices in dimensions 2–10, which were numerically optimized in 1996. The lattice labeled 5l was used in Example 1. The parameters of the following lattices are listed in Table II, from top to bottom: 2r, 3q, 4l, 4j, 5l, 5m, 6p, 6m, 7r, 7i, 8q, 9r, 9j, 9n, and 10q. |
| A. Ghasemmehdi and E. Agrell,
“Faster recursions in sphere decoding,”
IEEE Trans. Inform. Theory,
vol. 57, no. 6, pp. 3530–3536, June 2011.
arXiv, DOI, Chalmers repository |
Mathematica | Implementation and examples | In the paper, 8 algorithms are compactly presented in one figure, Fig. 2. Here they are implemented and exemplified separately. |
| A. Alvarado and E. Agrell,
“Four-dimensional coded modulation with bit-wise decoders for future optical communications,”
J. Lightw. Technol.,
vol. 33, no. 10, pp. 1993–2003, May 2015.
arXiv, DOI, Chalmers repository |
Text | Data, snapshot April 2021 | Coordinates of some four-dimensional constellations studied in the paper are provided, along with their binary labelings. |
| E. Agrell and M. Secondini,
“Information-theoretic tools for optical communications engineers,”
invited tutorial in Proc. IEEE Phot. Conf. (IPC),
Reston, VA, Sept.–Oct. 2018, pp. 99–103.
DOI, Chalmers repository |
Table I with corrections | Two errors were found in Table I. They were corrected in the Chalmers repository but not in IEEExplore. | |
|
E. Agrell, M. Secondini, A. Alvarado, and T. Yoshida,
“Performance prediction recipes for optical links,”
invited tutorial in IEEE Phot. Techn. Lett.,
vol. 33, no. 18, pp. 1034–1037, Sept. 2021.
arXiv, DOI, Chalmers repository |
Matlab | Implementation and examples: current version, snapshot April 2021 | The “recipes” presented in the paper are here implemented as modular Matlab code, which can be used to calculate performance metrics for arbitrary channel models or experimental data. The examples in the paper were produced using this code. |