  Spatially-coupled (SC) codes are a family of graph-based codes that have
attracted significant attention thanks to their capacity approaching
performance and low decoding latency. An SC code is constructed by partitioning
an underlying block code into a number of components and coupling their copies
together. In this paper, we first introduce a general approach for the
enumeration of detrimental combinatorial objects in the graph of finite-length
SC codes. Our approach is general in the sense that it effectively works for SC
codes with various column weights and memories. Next, we present a two-stage
framework for the construction of high-performance binary SC codes optimized
for additive white Gaussian noise channel; we aim at minimizing the number of
detrimental combinatorial objects in the error floor regime. In the first
stage, we deploy a novel partitioning scheme, called the optimal overlap
partitioning, to produce optimal partitioning corresponding to the smallest
number of detrimental objects. In the second stage, we apply a new circulant
power optimizer to further reduce the number of detrimental objects in the
lifted graph. An SC code constructed by our new framework has nearly 5 orders
of magnitudes error floor performance improvement compared to the uncoupled
setting.
