Feedback & Feed-forward.

Feedback is an important resource that is often available in both wireless and wired communication, but the question of how to optimally use feedback in a multi-terminal setting is not well understood. Broadly speaking, feedback induces correlation between the distributed transmitters and receivers in the network. We have developed coding schemes that effectively harness this correlation for multiple-access and broadcast channels with feedback. These schemes significantly improve on the best-known rates for these channels. In my Ph.D thesis, I also investigated the role of feed-forward in lossy data compression, for both point-to-point and multi-terminal models.

  • Slides from talk at HP Labs, Palo Alto, March 2010.
  • Slides from talk at ISIT, Austin, July 2010.
  • Slides from thesis defense. (Source coding with feed-forward)
  • "An Achievable Rate Region for the Broadcast Channel with Feedback", IEEE Transactions on Information Theory, vol. 59, no.10, pp. 6175-6191, October 2013. [PDF]
  • "A New Achievable Rate Region for the Discrete Memoryless Multiple-Access Channel with Feedback", IEEE Transactions on Information Theory, vol. 57, pp. 8038-8054, December 2011. [PDF]
  • "Source coding with feedforward: Rate-distortion theorems and error exponents for a general source", IEEE Transactions on Information Theory, vol. 53, pp. 2154-2179, June 2007. [PDF]
  • "Achievable rates for multiple descriptions with feed-forward", IEEE Transactions on Information Theory, vol. 57, pp. 2270-2277, April 2011. [PDF]

Codes for Data Storage.

Many non-volatile memory technologies such as Phase Change Media and Flash use `rewrites', i.e., it is possible to write multiple times on a memory cell until a desirable output is obtained. Since rewrites consume extra power and shorten the lifetime of the memory, there is a basic trade-off: what is the storage capacity of the memory subject to a fixed rewrite budget? Further, how do we design codes that optimally exploit the rewrite option? In collaboration with researchers from the Memory Technologies group at IBM, we have developed effiicient coding schemes for some basic rewritable channel models.

  • "Rewritable storage channels with hidden state", IEEE JSAC, vol. 32, no. 5, pp. 815-824, May 2014. [PDF]
  • "Coding Strategies for the uniform noise rewritable channel with hidden state", ISIT 2012. [PDF] [Slides]