Multi-rate control over AWGN channels via analog joint source-channel coding
Online Publication Date2017-01-05
Print Publication Date2016-12
Permanent link to this recordhttp://hdl.handle.net/10754/623567
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AbstractWe consider the problem of controlling an unstable plant over an additive white Gaussian noise (AWGN) channel with a transmit power constraint, where the signaling rate of communication is larger than the sampling rate (for generating observations and applying control inputs) of the underlying plant. Such a situation is quite common since sampling is done at a rate that captures the dynamics of the plant and which is often much lower than the rate that can be communicated. This setting offers the opportunity of improving the system performance by employing multiple channel uses to convey a single message (output plant observation or control input). Common ways of doing so are through either repeating the message, or by quantizing it to a number of bits and then transmitting a channel coded version of the bits whose length is commensurate with the number of channel uses per sampled message. We argue that such “separated source and channel coding” can be suboptimal and propose to perform joint source-channel coding. Since the block length is short we obviate the need to go to the digital domain altogether and instead consider analog joint source-channel coding. For the case where the communication signaling rate is twice the sampling rate, we employ the Archimedean bi-spiral-based Shannon-Kotel'nikov analog maps to show significant improvement in stability margins and linear-quadratic Gaussian (LQG) costs over simple schemes that employ repetition.
CitationKhina A, Pettersson GM, Kostina V, Hassibi B (2016) Multi-rate control over AWGN channels via analog joint source-channel coding. 2016 IEEE 55th Conference on Decision and Control (CDC). Available: http://dx.doi.org/10.1109/cdc.2016.7799185.
SponsorsThe work of A. Khina was supported in part by a Fulbright fellowship, Rothschild fellowship and has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłlodowska-Curie grant agreement No 708932. The work of G. M. Pettersson at Caltech was supported by The Boeing Company under the SURF program. The work of B. Hassibi was supported in part by the National Science Foundation under grants CNS-0932428, CCF-1018927, CCF-1423663 and CCF-1409204, by a grant from Qualcomm Inc., by NASA’s Jet Propulsion Laboratory through the President and Directors Fund, and by King Abdullah University of Science and Technology.
Conference/Event name55th IEEE Conference on Decision and Control, CDC 2016