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Spatially-coupled (SC) codes are a family of graph-based codes that haveattracted significant attention thanks to their capacity approachingperformance and low decoding latency. An SC code is constructed by partitioningan underlying block code into a number of components and coupling their copiestogether. In this paper, we first introduce a general approach for theenumeration of detrimental combinatorial objects in the graph of finite-lengthSC codes. Our approach is general in the sense that it effectively works for SCcodes with various column weights and memories. Next, we present a two-stageframework for the construction of high-performance binary SC codes optimizedfor additive white Gaussian noise channel; we aim at minimizing the number ofdetrimental combinatorial objects in the error floor regime. In the firststage, we deploy a novel partitioning scheme, called the optimal overlappartitioning, to produce optimal partitioning corresponding to the smallestnumber of detrimental objects. In the second stage, we apply a new circulantpower optimizer to further reduce the number of detrimental objects in thelifted graph. An SC code constructed by our new framework has nearly 5 ordersof magnitudes error floor performance improvement compared to the uncoupledsetting.

Finite-Length Construction of High Performance Spatially-Coupled Codes via Optimized Partitioning and Lifting