1 research outputs found
Joint State Estimation and Communication over a State-Dependent Gaussian Multiple Access Channel
A hybrid communication network with a common analog signal and an independent
digital data stream as input to each node in a multiple access network is
considered. The receiver/base-station has to estimate the analog signal with a
given fidelity, and decode the digital streams with a low error probability.
Treating the analog signal as a common state process, we set up a joint state
estimation and communication problem in a Gaussian multiple access channel
(MAC) with additive state. The transmitters have non-causal knowledge of the
state process, and need to communicate independent data streams in addition to
facilitating state estimation at the receiver. We first provide a complete
characterization of the optimal trade-off between mean squared error distortion
performance in estimating the state and the data rates for the message streams
from two transmitting nodes. This is then generalized to an N-sender MAC. To
this end, we show a natural connection between the state-dependent MAC model
and a hybrid multi-sensor network in which a common source phenomenon is
observed at N transmitting nodes. Each node encodes the source observations as
well as an independent message stream over a Gaussian MAC without any state
process. The receiver is interested estimating the source and all the messages.
Again the distortion-rate performance is characterized.Comment: 12 pages, Journal submissio