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 |
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. |
| E. Agrell, A. Vardy, and K. Zeger,
“A table of upper bounds for binary codes,”
IEEE Trans. Inform. Theory,
vol. 47, no. 7, pp. 3004–3006, Nov. 2001.
DOI, Chalmers |
Correction | The denominator of Theorem 2 was incorrect. | |
| E. Agrell, T. Eriksson, A. Vardy, and K. Zeger,
“Closest point search in lattices,”
IEEE Trans. Inform. Theory,
vol. 48, no. 8, pp. 2201–2214, Aug. 2002.
DOI, Chalmers |
Correction | Two equation references were swapped in the last paragraph. | |
| E. Agrell and M. Karlsson,
“Power-efficient modulation formats in
coherent transmission systems,”
J. Lightw. Technol.,
vol. 27, no. 22, pp. 5115–5126, Nov. 2009.
DOI, Chalmers |
Fig. 6 with correction | The 8-QAM dot in Fig. 6 was incorrectly positioned. | |
| E. Agrell and M. Karlsson,
“On the symbol error probability of regular polytopes,”
IEEE Trans. Inform. Theory,
vol. 57, no. 6, pp. 3411–3415, June 2011.
arXiv, DOI, Chalmers |
Correction | A square root sign was missing in (5). | |
| 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 |
Mathematica | Implementation and examples | In the paper, 8 algorithms are compactly presented in one figure, Fig. 2. Here they are implemented and exemplified separately. |
| M. Karlsson and E. Agrell,
“Generalized pulse-position modulation for optical power-efficient communication,”
European Conference on Optical Communication (ECOC),
Geneva, Switzerland, Sept. 2011.
DOI, Chalmers |
Corrections | An incorrect bandwidth was given in Sec. 3. | |
| 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 |
Text | Data, snapshot Apr. 2021 | Coordinates of some four-dimensional constellations studied in the paper are provided, along with their binary labelings. |
| R. S. Luís, B. J. Puttnam, G. Rademacher, W. Klaus, E. Agrell, Y. Awaji, and N. Wada,
“On the spectral efficiency limits of crosstalk-limited homogeneous single-mode multi-core fiber systems,”
Advanced Photonics Congress (APC),
New Orleans, LA, USA, July 2017.
DOI, Chalmers |
Fig. 1b with correction | The vertical axis in Fig. 1b was incorrectly labeled. | |
| E. Agrell and M. Secondini,
“Information-theoretic tools for optical communications engineers,”
invited tutorial in Proc. IEEE Phot. Conf. (IPC),
Reston, VA, USA, Sept.–Oct. 2018, pp. 99–103.
DOI, Chalmers |
Table I with corrections | Two errors were found in Table I. | |
| 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 |
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. |
| 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 |
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. |
| S. Li, M. Karlsson, and E. Agrell,
“Low-complexity Voronoi shaping for the Gaussian channel,”
IEEE Trans. Commun.,
vol. 70, no. 2, pp. 865–873, Feb. 2022.
arXiv, DOI, Chalmers |
Text | Data | A generator matrix of the lattice L32 is provided. The numerical results are correct but the description of its construction from an RM code is incorrect. If Construction B would be applied to the (32,6,16) RM code, a slightly better lattice with G = 0.0669 and g = 0.957 dB is obtained (unpublished). The same lattice L32 was studied in ECOC 2022 and JLT 2023 with incorrect descriptions (mentioning RM and BW, respectively). |
| 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 |
Corrections | An error, which first appeared in a classic 1984 paper by Conway and Sloane, has propagated to equation (12), which in turn influences (13)–(15). The matter is discussed in Sec. III-A of our 2025 paper. |