Channel Estimation with Low-Precision Analog-to-Digital Conversion

We consider the problem of estimating the impulse response of a dispersive channel when the channel output is sampled using a low-precision analog-to-digital converter (ADC). While traditional channel estimation techniques require about 6 bits of ADC precision to approach full-precision performance, we are motivated by applications to multiGigabit communication, where we may be forced to use much lower precision (e.g., 1-3 bits) due to considerations of cost, power, and technological feasibility. We show that, even with such low ADC precision, it is possible to attain near full-precision performance using closed-loop estimation, where the ADC input is dithered and scaled. The dither signal is obtained using linear feedback based on the Minimum Mean Squared Error (MMSE) criterion. The dither feedback coefficients and the scaling gains are computed offline using Monte Carlo simulations based on a statistical model for the channel taps, and are found to work well over wide range of channel variations.