Error correction for low power sensors in asynchronous communication

We propose a forward error correction scheme for asynchronous sampling via level crossing (LC) sampling and time encoding, where the dominant errors consist of pulse deletions and insertions, and where encoding is required to take place in an instantaneous fashion. For LC sampling the presented scheme consists of a combination of an outer systematic convolutional code, an embedded inner marker code, and power-efficient frequency-shift keying modulation at the sensor node. Decoding is first obtained via a maximum a-posteriori (MAP) decoder for the inner marker code, which achieves synchronization for the insertion and deletion channel, followed by MAP decoding for the outer convolutional code. Besides investigating the rate trade-off between marker and convolutional codes, we also show that residual redundancy in the asynchronously sampled source signal can be successfully exploited in combination with redundancy only from a marker code. This provides a low complexity alternative for deletion and insertion error correction compared to using explicit redundancy. For time encoding, only the pulse timing is of relevance at the receiver, and the outer channel code is replaced by a quantizer to represent the relative position of the pulse timing. Numerical simulations show that LC sampling outperforms time encoding in the low to moderate signal-to-noise ratio regime by a large margin.