The software BAA-Action, is a matlab package which computes the maximum of
normalized directed information for finite state channels with states
known to the decoder, when the encoder
takes cost constrained actions to determine whether or not the state is
fed back to the encoder. Specifically the following quantity is evaluated for the
figure shown above,
where maximum is over causal conditioning distribution such that the cost constraints on actions are satisfied. Please
refer to the Section XI-A in the reference for more details. The software
is specifically coded for the example in Section XI-B of the paper, where
the channel is Markovian, all channel input symbols, output symbols and states
The Blahut-Arimoto Algorithm for Action-Dependent Feedback (BAA-Action) is as follows.
BAA-Action.m : This function file computes the normalized directed information with action dependent feedback. The input parameters are :
= Maximum Number of Iterations for a fixed block length and lambda.
= Block Length to compute BAA-Action.
= The vector of Lagrangian Multiplier valus that will sweep the cost-capacity trade-off curve.
= Channel Transition Matrix.
BAA_Markov_Channel.m : This file computes the capacity upper and lower bounds for the Markovian Channel (cf. Fig. 7 in the reference). Typical bounds, computed for N=2, N=3 are shown below,
1. To Feed or Not to Feed Back
Himanshu Asnani, Haim Permuter, Tsachy Weissman, submitted to IEEE Transactions on Information Theory, Nov 2010.
A shorter version to appear in Proceedings of 2011 IEEE Interational Symposium on Information Theory, St. Petersburg, Russia, August 2011. (slides) (ISIT STUDENT PAPER AWARD FINALIST)
The work has been supported by the NSF Award-1049413.
Email : asnani AT stanford.edu