Approaching the capacity of AWGN channels using multi-layer raptor codes and superposition modulation

Abstract

We propose a capacity approaching coding strategy for additive white Gaussian noise (AWGN) channels by using multi-layer Raptor codes and superposition modulation. Each AWGN channel is divided into several binary-input AWGN (BI-AWGN) channels at a very low signal to noise ratio (SNR), where a capacity approaching Raptor code can be used to encode the message over each layer. A single capacity approaching degree distribution is then used for the Raptor codes over all the layers. A well-known multi-stage decoder is used for successive interference cancellation and decoding the multi-layer Raptor code, where each decoding stage is modeled by a BI-AWGN channel of a fixed SNR. This allows the development of a capacity approaching code for an AWGN channel at every SNR by using a single Raptor code with a fixed degree distribution as the component code.