Iterative Decoding and Sparse Channel Estimation for an Underwater Acoustic Telemetry Modem

Abstract

An acoustic modem employing direct-sequence spread-spectrum (DSSS) signaling is considered with LDPC coding. The underwater acoustic channel is tracked using a Kalman filter which requires accurate data decisions. To improve KF performance and reduce the overall error rate, joint iterative LDPC decoding and channel estimation is proposed based on a factor graph and sum-product algorithm approximation. In this scheme, the decoder posterior log likelihood ratios (LLRs) provide data decisions for the KF. Decoder extrinsic LLRs are similarly incorporated into the detector LLRs to yield improved priors for decoding. Error rate simulations of the overall modem are provided for a shallow-water channel model with Ricean/Rayleigh fading.