On the duality of globally constrained separable problems and its application to distributed signal processing

On the duality of globally constrained separable problems and its application to distributed signal processing

Sherson, T.W. (TU Delft Signal Processing Systems)
Heusdens, R. (TU Delft Signal Processing Systems)
Kleijn, W.B. (TU Delft Signal Processing Systems; Victoria University of Wellington)

2016-12-01

In this paper, we focus on the challenge of processing data generated within decentralised wireless sensor networks in a distributed manner. When the desired operations can be expressed as globally constrained separable convex optimisation problems, we show how we can convert these to extended monotropic programs and exploit Lagrangian duality to form equivalent distributed consensus problems. Such problems can be embedded in sensor network applications via existing solvers such as the alternating direction method of multipliers or the primal dual method of multipliers. We then demonstrate how this approach can be used to solve specific problems including linearly constrained quadratic problems and the classic Gaussian channel capacity maximisation problem in a distributed manner.

extended monotropic programs
Wireless sensor networks
distributed signal processing
Lagrangian duality

http://resolver.tudelft.nl/uuid:86a7f178-fe77-4607-9cfe-77f1bc3b90d8

https://doi.org/10.1109/eusipco.2016.7760415

IEEE, Piscataway, NJ

978-0-9928-6265-7

2016 24th European Signal Processing Conference, EUSIPCO 2016

EUSIPCO 2016, 2016-08-29 → 2016-09-02, Budapest, Hungary

Institutional Repository

conference paper

© 2016 T.W. Sherson, R. Heusdens, W.B. Kleijn