  Sparse superposition codes are a recent class of codes introduced by Barron
and Joseph for efficient communication over the AWGN channel. With an
appropriate power allocation, these codes have been shown to be asymptotically
capacity-achieving with computationally feasible decoding. However, a direct
implementation of the capacity-achieving construction does not give good finite
length error performance. In this paper, we consider sparse superposition codes
with approximate message passing (AMP) decoding, and describe a variety of
techniques to improve their finite length performance. These include an
iterative algorithm for SPARC power allocation, guidelines for choosing
codebook parameters, and estimating a critical decoding parameter online
instead of pre-computation. We also show how partial outer codes can be used in
conjunction with AMP decoding to obtain a steep waterfall in the error
performance curves. We compare the error performance of AMP-decoded sparse
superposition codes with coded modulation using LDPC codes from the WiMAX
standard.
