Forward error correction enables reliable one-way communication over noisy channels, by transmitting redundant data along with the message in order to detect and resolve errors at the receiver. Low-density parity-check (LDPC) codes achieve superior error-correction performance on Gaussian channels under belief propagation decoding, however, their complex parity-check matrix structure introduces hardware implementation challenges. This thesis explores how the quasi-cyclic structure of LDPC parity-check matrices can be exploited in the design of low-power hardware architectures for multi-Gigabit/second decoders realized in CMOS technology, as well as in the design and construction of multi-edge LDPC codes for long-distance (beyond 100km) quantum cryptography over optical fiber. A frame-interleaved architecture is presented with a path-unrolled message-passing schedule to reduce the complexity of routing interconnect in an integrated circuit decoder implementation. A proof-of-concept silicon test chip was fabricated in the 28nm CMOS technology node. The LDPC decoder chip supports the four codes presented in the IEEE 802.11ad standard, occupies an area of 3.41mm^2, and achieves an energy efficiency of 15pJ/bit while delivering a maximum throughput of 6.78Gb/s, and operating with a 202MHz clock at 0.9V supply. The test chip achieves the highest normalized energy efficiency among published CMOS-based decoders for the IEEE 802.11ad standard. A quasi-cyclic code construction technique is applied to a multi-edge LDPC code with block length of 10^6 bits in order to reduce the latency of LDPC decoding in the key reconciliation step of long-distance quantum key distribution. The GPU-based decoder achieves a maximum information throughput of 7.16Kb/s, and extends the current maximum transmission distance from 100km to 160km with a secret key rate of 4.10 x 10^(-7) bits/pulse under 8-dimensional reconciliation. The GPU-based decoder delivers up to 8.03x higher decoded information throughput over the upper bound on secret key rate for a lossy optical channel, thus demonstrating that key reconciliation with LDPC codes is no longer a post-processing bottleneck in quantum key distribution. The contributions presented in this thesis can be applied to future research in the implementation of silicon-based linear-program decoders for high-reliability channels, and single-chip solutions for quantum key distribution containing integrated photonics and post-processing algorithms.
Forward error correction enables reliable one-way communication over noisy channels, by transmitting redundant data along with the message in order to detect and resolve errors at the receiver. Low-density parity-check (LDPC) codes achieve superior error-correction performance on Gaussian channels under belief propagation decoding, however, their complex parity-check matrix structure introduces hardware implementation challenges. This thesis explores how the quasi-cyclic structure of LDPC parity-check matrices can be exploited in the design of low-power hardware architectures for multi-Gigabit/second decoders realized in CMOS technology, as well as in the design and construction of multi-edge LDPC codes for long-distance (beyond 100km) quantum cryptography over optical fiber. A frame-interleaved architecture is presented with a path-unrolled message-passing schedule to reduce the complexity of routing interconnect in an integrated circuit decoder implementation. A proof-of-concept silicon test chip was fabricated in the 28nm CMOS technology node. The LDPC decoder chip supports the four codes presented in the IEEE 802.11ad standard, occupies an area of 3.41mm^2, and achieves an energy efficiency of 15pJ/bit while delivering a maximum throughput of 6.78Gb/s, and operating with a 202MHz clock at 0.9V supply. The test chip achieves the highest normalized energy efficiency among published CMOS-based decoders for the IEEE 802.11ad standard. A quasi-cyclic code construction technique is applied to a multi-edge LDPC code with block length of 10^6 bits in order to reduce the latency of LDPC decoding in the key reconciliation step of long-distance quantum key distribution. The GPU-based decoder achieves a maximum information throughput of 7.16Kb/s, and extends the current maximum transmission distance from 100km to 160km with a secret key rate of 4.10 x 10^(-7) bits/pulse under 8-dimensional reconciliation. The GPU-based decoder delivers up to 8.03x higher decoded information throughput over the upper bound on secret key rate for a lossy optical channel, thus demonstrating that key reconciliation with LDPC codes is no longer a post-processing bottleneck in quantum key distribution. The contributions presented in this thesis can be applied to future research in the implementation of silicon-based linear-program decoders for high-reliability channels, and single-chip solutions for quantum key distribution containing integrated photonics and post-processing algorithms.
Abstract The speed at which two remote parties can exchange secret keys in continuous-variable quantum key distribution (CV-QKD) is currently limited by the computational complexity of key reconciliation. Multi-dimensional reconciliation using multi-edge low-density parity-check (LDPC) codes with low code rates and long block lengths has been shown to improve error-correction performance and extend the maximum reconciliation distance. We introduce a quasi-cyclic code construction for multi-edge codes that is highly suitable for hardware-accelerated decoding on a graphics processing unit (GPU). When combined with an 8-dimensional reconciliation scheme, our LDPC decoder achieves an information throughput of 7.16 Kbit/s on a single NVIDIA GeForce GTX 1080 GPU, at a maximum distance of 142 km with a secret key rate of 6.64 × 10−8 bits/pulse for a rate 0.02 code with block length of 106 bits. The LDPC codes presented in this work can be used to extend the previous maximum CV-QKD distance of 100 km to 142 km, while delivering up to 3.50× higher information throughput over the tight upper bound on secret key rate for a lossy channel.
Quantum key distribution (QKD) can provide an unconditionally secure communication encryption method. Continuous-variable QKD (CVQKD) requires extracting the key from the noisy channel, leading to higher requirements for the error-correcting codes used in multidimensional reconciliation. We extend the quasi-cyclic low-density parity-check of the radio design for the global 5G mobile communication technology standard to achieve error correction under lower signal-to-noise ratio on integrated hardware. A field programmable gate array (FPGA) chip is used to realize the approximate lower triangular matrix encoding algorithm, and the core module only has the circular shift register, which reduces the encoding complexity, improves the encoding efficiency, and reduces the hardware resource consumption. For extended super-long code words, the decoding algorithm requires additional hardware resources to implement, which the previous algorithm cannot meet. Therefore, we present a hardware implementation of offset minimum sum algorithm (OMSA), which can avoid operations of complex mathematical formula. The offset factor of OMSA reduce the error caused by the low accuracy of calculation on the hardware. The update of the decoding information is layered in a partially parallel way in the matrix to achieve the cross processing of node information. It speeds up the transmission of information between different nodes and the convergence of decoding algorithm of low-complexity parallel structure. Simulation results show that the maximum theoretical coordination efficiency is 85% when the code with block length is 69632 at a bit rate of 22/68 and the signal-to-noise ratio asymptotic threshold is 0.7. Using an FPGA, ∼0.1 frame error rate was achieved, but with a zero-bit error rate, the optimal achievable secret key rate is about 200 Kbps at 30-km distance theoretically. For a 200-MHz system clock on the successfully decoded block, 125 Gbps encoding throughput and 472 Kbps decoding throughput was achieved, better than the theoretical key rate of prototype of CVQKD.
Low-density parity-check (LDPC) codes had a renaissance when they were rediscovered in the 1990’s. Since then LDPC codes have been an important part of the field of error-correcting codes, and have been shown to be able to approach the Shannon capacity, the limit at which we can reliably transmit information over noisy channels. Following this, many modern communications standards have adopted LDPC codes. Error-correction is equally important in protecting data from corruption on a hard-drive as it is in deep-space communications. It is most commonly used for example for reliable wireless transmission of data to mobile devices. For practical purposes, both encoding and decoding need to be of low complexity to achieve high throughput and low power consumption. This thesis provides a literature review of the current state-of-the-art in encoding and decoding of LDPC codes. Message- passing decoders are still capable of achieving the best error-correcting performance, while more recently considered bit-flipping decoders are providing a low-complexity alternative, albeit with some loss in error-correcting performance. An implementation of a low-complexity stochastic bit-flipping decoder is also presented. It is implemented for Graphics Processing Units (GPUs) in a parallel fashion, providing a peak throughput of 1.2 Gb/s, which is significantly higher than previous decoder implementations on GPUs. The error-correcting performance of a range of decoders has also been tested, showing that the stochastic bit-flipping decoder provides relatively good error-correcting performance with low complexity. Finally, a brief comparison of encoding complexities for two code ensembles is also presented.
The throughput of error correction is one of the main bottlenecks of high-speed continuous variable quantum key distribution (CV-QKD) post-processing, which directly restricts the practical secret key rates (SKR). Implementing the decoder of low-density parity-check (LDPC) codes based on FPGA in limited precision can improve the decoding throughput significantly. In this paper, a high-throughput decoder architecture with limited precision for quasi-cyclic LDPC (QC-LDPC) codes is proposed. In particular, decoding of two typical LDPC codes, with code rates 0.2 and 0.1, for CV-QKD have been implemented on a commercial FPGA. The clock operates at 100 MHZ and the throughput of 1.44 Gbps and 0.78 Gbps is achieved, respectively, which can support 71.89 Mbps and 9.97 Mbps real-time SKR under transmission distance of 25 km and 50 km, respectively. The proposed architecture paves the way for high-rate real-time CV-QKD deployment in secure metropolitan area network.
Binary Low-Density Parity-Check (LDPC) codes are a type of error correction code known to exhibit excellent error-correcting capabilities, and have increasingly been applied as the forward error correction solution in a multitude of systems and standards, such as wireless communications, wireline communications, and data storage systems. In the pursuit of codes with even higher coding gain, non-binary LDPC (NB-LDPC) codes defined over a Galois field of order q have risen as a strong replacement candidate. For codes defined with similar rate and length, NB-LDPC codes exhibit a significant coding gain improvement relative to that of their binary counterparts.Unfortunately, NB-LDPC codes are currently limited from practical application by the immense complexity of their decoding algorithms, because the improved error-rate performance of higher field orders comes at the cost of increasing decoding algorithm complexity. Currently available ASIC implementation solutions for NB-LDPC code decoders are simultaneously low in throughput and power-hungry, leading to a low energy efficiency.We propose several techniques at the algorithm level as well as hardware architecture level in an attempt to bring NB-LDPC codes closer to practical deployment. On the algorithm side, we propose several algorithmic modifications and analyze the corresponding hardware cost alleviation as well as impact on coding gain. We also study the quantization scheme for NB-LDPC decoders, again in the context of both the hardware and coding gain impacts, and we propose a technique that enables a good tradeoff in this space. On the hardware side, we develop a FPGA-based NB-LDPC decoder platform for architecture prototyping as well as hardware acceleration of code evaluation via error rate simulations. We also discuss the architectural techniques and innovations corresponding to our proposed algorithm for optimization of the implementation. Finally, a proof-of-concept ASIC chip is realized that integrates many of the proposed techniques. We are able to achieve a 3.7x improvement in the information throughput and 23.8x improvement in the energy efficiency over prior state-of-the-art, without sacrificing the strong error correcting capabilities of the NB-LDPC code.
In recent years, the amount of digital data which is stored and transmitted for private and public usage has increased considerably. To allow a save transmission and storage of data despite of error-prone transmission media, error correcting codes are used. A large variety of codes has been developed, and in the past decade low-density parity-check (LDPC) codes which have an excellent error correction performance became more and more popular. Today, low-density parity-check codes have been adopted for several standards, and efficient decoder hardware architectures are known for the chosen structured codes. However, the existing decoder designs lack flexibility as only few structured codes can be decoded with one decoder chip. In consequence, different codes require a redesign of the decoder, and few solutions exist for decoding of codes which are not quasi-cyclic or which are unstructured. In this thesis, three different approaches are presented for the implementation of fully programmable LDPC decoders which can decode arbitrary LDPC codes. As a design study, the first programmable decoder which uses a heuristic mapping algorithm is realized on a field-programmable gate array (FPGA), and error correction curves are measured to verify the correct functionality. The main contribution of this thesis lies in the development of the second and the third architecture and an appropriate mapping algorithm. The proposed fully programmable decoder architectures use one-phase message passing and layered decoding and can decode arbitrary LDPC codes using an optimum mapping and scheduling algorithm. The presented programmable architectures are in fact generalized decoder architectures from which the known decoder architectures for structured LDPC codes can be derived.