… and not enough solutions:

• Matching source and channel models for large sensor networks : I want to characterize when a fully-distributed set of gains can “match” a linear/matrix observation model with a linear/matrix communication channel model. I think it’s a broad class, especially as the number of gains (which is the number of sensors) increases.
• Dense sensor network scaling laws: under some better constraints, it should be possible to show that the total capacity does not scale with the network size for dense networks.
• Causal jamming relays: a new take on relays as potential jammers. You can’t trust anyone.
• Fast distributed consensus: not quite sure where this is going, but it has to do with creating a speedy algorithm for calculating the average of a function on a graph.

There are, of course, other problems, but unless I write these down I’ll be liable to forget them when the next shiny object comes along.