Technical Program

Paper Detail

Paper IDO.5.3
Paper Title Tracking an Auto-Regressive Process with Limited Communication
Authors Rooji Jinan, Parimal Parag, Himanshu Tyagi, Indian Institute of Science, Bengaluru, India
Session O.5: Topics in Source Coding
Presentation Lecture
Track Source Coding
Manuscript  Click here to download the manuscript
Virtual Presentation  Click here to watch in the Virtual Symposium
Abstract Samples from a high-dimensional AR[1] process are quantized and sent over a time-slotted communication channel of finite capacity. The receiver seeks to form an estimate of the process in real-time. We consider the slow-sampling regime where multiple communication slots occur between two sampling instants. We propose a successive update scheme which uses communication between sampling instants to update the estimates of the latest sample. We show that there exist quantizers that render the fast but loose version of this scheme, which updates estimates in every slot, universally optimal asymptotically. However, we provide evidence that most practical quantizers will require a judiciously chosen update frequency.

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2021 IEEE International Symposium on Information Theory

11-16 July 2021 | Melbourne, Victoria, Australia

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