Mikael Johansson
Information Systems Laboratory
Stanford University
Stanford, California, USA
E-mail:
mikaelj@stanford.edu
In the first part of the talk, we assume that the linear system is fixed and address the problem of allocating communication resources to optimize system performance. We show that for many channel models, this problem is convex, hence readily solved. We describe a dual decomposition method that exploits the problem structure, and show how the method reduces to standard waterfilling techniques in problems with only one coupling constraint. We briefly describe how integer constraints on communication rates can be handled and give a bound on how suboptimal these heuristics can be.
In the second part of the talk, we consider the problem of jointly allocating communication resources and designing the linear system in order to optimize the overall system performance. This problem is in general not convex, but can be solved heuristically in a way that exploits the problem structure and appears to work well in practice.
This talk is based on joint work with Lin Xiao, Haitham Hindi, Stephen Boyd, and Andrea Goldsmith.