Abstract
AbstractThis paper describes a field-programmable gate array (FPGA) implementation of a fixed-point low-density lattice code (LDLC) decoder where the Gaussian mixture messages that are exchanged during the iterative decoding process are approximated to a single Gaussian. A detailed quantization study is first performed to find the minimum number of bits required for the fixed-point decoder to attain a frame error rate (FER) performance similar to floating-point. Then efficient numerical methods are devised to approximate the required non-linear functions. Finally, the paper presents a comparison of the performance of the different decoder architectures as well as a detailed analysis of the resource requirements and throughput trade-offs of the primary design blocks for the different architectures. A novel pipelined LDLC decoder architecture is proposed where resource re-utilization along with pipelining allows for a parallelism equivalent to 50 variable nodes on the target FPGA device. The pipelined architecture attains a throughput of 10.5 Msymbols/sec at a distance of 5 dB from capacity which is a 1.8$$\times$$
×
improvement in throughput compared to an implementation with 20 parallel variable nodes without pipelining. This implementation also achieves 24$$\times$$
×
improvement in throughput over a baseline serial decoder.
Funder
Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
Intel Corporation
CMC Microsystems
Publisher
Springer Science and Business Media LLC
Subject
Hardware and Architecture,Modeling and Simulation,Information Systems,Signal Processing,Theoretical Computer Science,Control and Systems Engineering