Designing Power-Efficient Modulation Formats for Noncoherent Optical Systems
Paper in proceedings, 2011

We optimize modulation formats for the additive white Gaussian noise channel with a nonnegative input constraint, also known as the intensity-modulated direct detection channel, with and without confining them to a lattice structure. Our optimization criteria are the average electrical and optical power. The nonnegativity input signal constraint is translated into a conical constraint in signal space, and modulation formats are designed by sphere packing inside this cone. Some remarkably dense packings are found, which yield more power-efficient modulation formats than previously known. For example, at a spectral efficiency of 1 bit/s/Hz, the obtained modulation format offers a 0.86 dB average electrical power gain and 0.43 dB average optical power gain over the previously best known modulation formats to achieve a symbol error rate of 10^-6. This modulation turns out to have a lattice-based structure. At a spectral efficiency of 3/2 bits/s/Hz and to achieve a symbol error rate of 10^-6, the modulation format obtained for optimizing the average electrical power offers a 0.58 dB average electrical power gain over the best lattice-based modulation and 2.55 dB gain over the best previously known format. However, the modulation format optimized for average optical power offers a 0.46 dB average optical power gain over the best lattice-based modulation and 1.35 dB gain over the best previously known format.

Author

Johnny Karout

Chalmers, Signals and Systems, Kommunikationssystem, informationsteori och antenner, Communication Systems

Erik Agrell

Chalmers, Signals and Systems, Kommunikationssystem, informationsteori och antenner, Communication Systems

Krzysztof Szczerba

Chalmers, Microtechnology and Nanoscience (MC2), Photonics

Magnus Karlsson

Chalmers, Microtechnology and Nanoscience (MC2), Photonics

GLOBECOM - IEEE Global Telecommunications Conference

6133546

Areas of Advance

Information and Communication Technology

Subject Categories

Computational Mathematics

Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1109/GLOCOM.2011.6133546

ISBN

978-1-4244-9268-8

More information

Latest update

3/29/2018