1.5 Gbit/s FPGA Implementation of a Fully-Parallel Turbo Decoder Designed for Mission-Critical Machine-Type Communication Applications

Abstract

In wireless communication schemes, turbo codes facilitate near-capacity transmission throughputs by achieving reliable forward error correction. However, owing to the serial data dependencies imposed by the underlying logarithmic Bahl–Cocke-Jelinek–Raviv (Log-BCJR) algorithm, the limited processing throughputs of conventional turbo decoder implementations impose a severe bottleneck upon the overall throughputs of real-time wireless communication schemes. Motivated by this, we recently proposed a fully parallel turbo decoder (FPTD) algorithm, which eliminates these serial data dependencies, allowing parallel processing and hence offering a significantly higher processing throughput. In this paper, we propose a novel resource-efficient version of the FPTD algorithm, which reduces its computational resource requirement by 50%, which enhancing its suitability for field-programmable gate array (FPGA) implementations. We propose a model FPGA implementation. When using a Stratix IV FPGA, the proposed FPTD FPGA implementation achieves an average throughput of 1.53 Gb/s and an average latency of 0.56 $\mu \text{s}$ , when decoding frames comprising ${N}=720$ b. These are, respectively, 13.2 times and 11.1 times superior to those of the state-of-the-art FPGA implementation of the Log-BCJR long-term evolution (LTE) turbo decoder, when decoding frames of the same frame length at the same error correction capability. Furthermore, our proposed FPTD FPGA implementation achieves a normalized resource usage of 0.42 (kALUTs/Mb/s), which is 5.2 times superior to that of the benchmarker decoder. Furthermore, when decoding the shortest $N=40$ -b LTE frames, the proposed FPTD FPGA implementation achieves an average throughput of 442 Mb/s and an average latency of 0.18 $\mu \text{s}$ , which are, respectively, 21.1 times and 10.6 times superior to those of the benchmarker decoder. In this case, the normalized resource usage of 0.08 (kALUTs/Mb/s) is 146.4 times superior to that of the benchmarker decoder.