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 believed 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, are provided. 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 Apr. 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 Apr. 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. |
| V. Oliari, E. Agrell, G. Liga, and A. Alvarado,
“Frequency logarithmic perturbation on the group-velocity dispersion parameter with applications to passive optical networks,”
J. Lightw. Technol.,
vol. 39, no. 16, pp. 5287–5299, Aug. 2021.
arXiv, DOI, Chalmers repository |
Matlab | Implementation and examples: current version, snapshot Jan. 2024 | Five perturbative channel modes are implemented in Matlab. The results in the paper were produced using this code. |
| D. Pook-Kolb, E. Agrell, and B. Allen,
“The Voronoi region of the Barnes–Wall lattice Λ16,”
IEEE J. Select. Areas Inform. Theory,
vol. 4, pp. 16–23, 2023.
arXiv, DOI, Chalmers repository |
Equations and comments | An error, which first appeared in a classic 1984 paper, reappeared in equation (12) and also influences (13)–(15). It was corrected in the Chalmers repository but not in arXiv or IEEExplore. The matter is discussed in Sec. III-A of arXiv 2401.01799, from which the attached PDF was extracted. |