New results on the real-time transmission problem
IEEE Transactions on Information Theory
Stochastic systems: estimation, identification and adaptive control
Stochastic systems: estimation, identification and adaptive control
Simultaneous design of measurement and control strategies for stochastic systems with feedback
Automatica (Journal of IFAC)
A Survey of solution techniques for the partially observed Markov decision process
Annals of Operations Research
A survey of algorithmic methods for partially observed Markov decision processes
Annals of Operations Research
Discrete-time controlled Markov processes with average cost criterion: a survey
SIAM Journal on Control and Optimization
Adaptive Markov Control Processes
Adaptive Markov Control Processes
Optimization over Time
Optimal Sequential Vector Quantization of Markov Sources
SIAM Journal on Control and Optimization
The Complexity of Decentralized Control of Markov Decision Processes
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Algorithms for partially observable markov decision processes
Algorithms for partially observable markov decision processes
Point-Based Value Iteration for Continuous POMDPs
The Journal of Machine Learning Research
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 3
Efficient adaptive algorithms and minimax bounds for zero-delay lossy source coding
IEEE Transactions on Signal Processing
A zero-delay sequential scheme for lossy coding of individual sequences
IEEE Transactions on Information Theory
On limited-delay lossy coding and filtering of individual sequences
IEEE Transactions on Information Theory
Source coding exponents for zero-delay coding with finite memory
IEEE Transactions on Information Theory
Causal coding of stationary sources and individual sequences with high resolution
IEEE Transactions on Information Theory
On the Structure of Optimal Real-Time Encoders and Decoders in Noisy Communication
IEEE Transactions on Information Theory
Universal Zero-Delay Joint Source–Channel Coding
IEEE Transactions on Information Theory
Redundant data transmission in control/estimation over lossy networks
Automatica (Journal of IFAC)
| Hi-index | 754.84 |
Optimal design of sequential real-time communication of a Markov source over a noisy channel is investigated. In such a system, the delay between the source output and its reconstruction at the receiver should equal a fixed prespecified amount. An optimal communication strategy must minimize the total expected symbol-by-symbol distortion between the source output and its reconstruction. Design techniques or performance bounds for such real-time communication systems are unknown. In this paper a systematic methodology, based on the concepts of information structures and information states, to search for an optimal real-time communication strategy is presented. This methodology trades off complexity in communication length (linear in contrast to doubly exponential) with complexity in alphabet sizes (doubly exponential in contrast to exponential). As the communication length is usually order of magnitudes bigger than the alphabet sizes, the proposed methodology simplifies the search for an optimal communication strategy. In spite of this simplification, the resultant optimality equations cannot be solved efficiently using existing algorithmic techniques. The main idea is to formulate a zero-delay communication problem as a dynamic team with nonclassical information structure. Then, an appropriate choice of information states converts the dynamic team problem into a centralized stochastic control problem in function space. Thereafter, Markov decision theory is used to derive nested optimality equations for choosing an optimal design. For infinite horizon problems, these optimality equations give rise to a fixed point functional equation. Communication systems with fixed finite delay constraint, a higher-order Markov source, and channels with memory are treated in the same manner after an appropriate expansion of the state space. Thus, this paper presents a comprehensive methodology to study different variations of real-time communication.