Distributed Detection with Unreliable Reporting Channels: Quantize or Not Quantize?
Lei Cao, R. Viswanathan · 2023
It is known that reporting the raw data observed at sensors to the fusion center completely and without any channel distortion always performs better than reporting the quantized data. However, when channel noise exists as it is always in practice, we show whether it is optimal to send the unquantized raw data or quantized data is a very interesting question that requires more research efforts. We compare these two schemes under the constraints of using the same transmission power and the bandwidth where analog modulation is assumed per channel use. The detection performance with one sensor and two sensors is presented in terms of the Bayes error. The performance of using asymptotically many sensors is compared with the Chernoff information. What presented in the paper could open up a new perspective in the design of the optimal distributed detection systems.