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Coding and modulation for power and bandwidth efficient communication

We investigate methods for power and bandwidth efcient communication. 
The approach we consider is based on powerful binary error correcting codes 
and we construct coded modulation schemes which are able to perform close 
to the capacity of the channel. 
We focus on the additive white Gaussian noise channel. For this channel a 
Gaussian distribution maximizes mutual information and signal shaping has 
to be used to get close to capacity. We investigate a simple method of signal 
shaping based on the superposition of binary random variables. With multistage 
decoding at the receiver, the original coding problem is transformed into 
a coding problem for a set of equivalent binary-input output-symmetric channels. 
It is shown that with the method signal constellations can be designed for 
high spectral efciencies which have their capacity limit within 0.1 dB of the 
capacity of the AWGN channel. Furthermore, low-density parity-check codes 
are designed for the equivalent binary channels resulting from this modulation 
method. We show how to approach the constrained capacity limit of the signal 
constellations we design very closely. 
A downside of multistage decoding is that multiple binary error-correcting 
codes are used. We show how one can limit the number of error-correcting 
codes used by merging bit-interleaved coded modulation and signal shaping. 
This results in a coded modulation scheme which is able to approach the capacity 
of the AWGN channel closely for any spectral efciency. 
These coded modulation methods transform the coding problem for the 
original channel into a coding problem for a set of binary channels. Depending 
on the design of the modulation scheme these channels are symmetric or 
not. We show how to characterize channel symmetry in general and how these 
results can be used to design coded modulation schemes resulting in a set of 
symmetric binary channels.