In this presentation, I will survey some recent efforts within my research 
group in the OSU Department of Electrical and Computer Engineering. 
Broadly speaking, these efforts fall in the intersection of signal 
processing, communications, and networking.
In the first part of the talk, I will discuss communication 
over channels with significant delay and Doppler spreading.
The discussion will include channel capacity analysis, 
optimized multicarrier modulation, 
and reception strategies that iterate soft-input soft-output 
decoding and joint channel-estimation/equalization.
In the second part of the talk, I will discuss the compressive sensing
problem, where one attempts to reconstruct a signal that has been sampled
far below the Nyquist rate by exploiting the fact that the signal is 
sparse in some known basis.
(Such signals include images---natural, radar, or medical---and 
communication-channel responses.)
Here, I will focus on Bayesian strategies and signals with structured 
sparsity patterns.
In the last part of the talk, I will discuss adaptive communication schemes
where the transmitter attempts to optimize resource allocation based on 
channel estimates obtained through limited ARQ feedbacks (i.e., ACK/NAK).
In particular, I will discuss optimal and practical solutions for rate 
adaptation and for joint rate/power/user adaptation.
Funding for these efforts has come primarily from 
the National Science Foundation and the Office of Naval Research.