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In this paper, we introduce two new methods of mitigating decoder error propagation for low-latency sliding window decoding (SWD) of spatially coupled low-density parity-check (SC-LDPC) codes. Building on the recently introduced idea of check node (CN) doping of regular SC-LDPC codes, here we employ variable node (VN) doping to fix (set to a known value) a subset of variable nodes in the coupling chain. Both of these doping methods have the effect of allowing SWD to recover from error propagation, at a cost of a slight rate loss. Experimental results show that, similar to CN doping, VN doping improves performance by up to two orders of magnitude compared to un-doped SC-LDPC codes in the typical signal-to-noise ratio operating range. Further, compared to CN doping, VN doping has the advantage of not requiring any changes to the decoding process. In addition, a log-likelihood-ratio based window extension algorithm is proposed to reduce the effect of error propagation. Using this approach, we show that decoding latency can be reduced by up to a significant fraction without suffering any loss in performance. 

In this paper, we introduce two new methods of mitigating decoder error propagation for low-latency sliding window decoding (SWD) of spatially coupled low density parity check (SC-LDPC) codes. Building on the recently introduced idea of check node (CN) doping of regular SC-LDPC codes, here we employ variable node (VN) doping to fix (set to a known value) a subset of variable nodes in the coupling chain. Both of these doping methods have the effect of allowing SWD to recover from error propagation, at a cost of a slight rate loss. Experimental results show that, similar to CN doping, VN doping improves performance by up to two orders of magnitude compared to undoped SC-LDPC codes in the typical signal-to-noise ratio operating range. Further, compared to CN doping, VN doping has the advantage of not requiring any changes to the decoding process.In addition, a log-likelihood-ratio based window extension algorithm is proposed to reduce the effect of error propagation. Using this approach, we show that decoding latency can be reduced by up to a significant fraction without suffering any loss in performance 

For a large part of earth's history, cyanobacterial mats thrived in low‐oxygen conditions, yet our understanding of their ecological functioning is limited. Extant cyanobacterial mats provide windows into the putative functioning of ancient ecosystems, and they continue to mediate biogeochemical transformations and nutrient transport across the sediment–water interface in modern ecosystems. The structure and function of benthic mats are shaped by biogeochemical processes in underlying sediments. A modern cyanobacterial mat system in a submerged sinkhole of Lake Huron (LH) provides a unique opportunity to explore such sediment–mat interactions. In the Middle Island Sinkhole (MIS), seeping groundwater establishes a low‐oxygen, sulfidic environment in which a microbial mat dominated byPhormidiumandPlanktothrixthat is capable of both anoxygenic and oxygenic photosynthesis, as well as chemosynthesis, thrives. We explored the coupled microbial community composition and biogeochemical functioning of organic‐rich, sulfidic sediments underlying the surface mat. Microbial communities were diverse and vertically stratified to 12 cm sediment depth. In contrast to previous studies, which used low‐throughput or shotgun metagenomic approaches, our high‐throughput 16SrRNAgene sequencing approach revealed extensive diversity. This diversity was present within microbial groups, including putative sulfate‐reducing taxa ofDeltaproteobacteria, some of which exhibited differential abundance patterns in the mats and with depth in the underlying sediments. The biological and geochemical conditions in theMISwere distinctly different from those in typicalLHsediments of comparable depth. We found evidence for active cycling of sulfur, methane, and nutrients leading to high concentrations of sulfide, ammonium, and phosphorus in sediments underlying cyanobacterial mats. Indicators of nutrient availability were significantly related toMISmicrobial community composition, whileLHcommunities were also shaped by indicators of subsurface groundwater influence. These results show that interactions between the mats and sediments are crucial for sustaining this hot spot of biological diversity and biogeochemical cycling.