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Early-Decision Decoding of LDPC Codes

Anton Blad

Published Jan 1, 2009• 1 citation
OpenAlex

Abstract

Since their rediscovery in 1995, low-density parity-check (LDPC) codes have received wide-spread attention as practical capacity-approaching code candidates. It has been shown that the class of codes can perform arbitrarily close to the channel capacity, and LDPC codes are also used or suggested for a number of important current and future communication standards. However, the problem of implementing an energy-efficient decoder has not yet been solved. Whereas the decoding algorithm is computationally simple, withuncomplicated arithmetic operations and low accuracy requirements, the random structure and irregularity of a theoretically well-defined code does not easily allow efficient VLSI implementations. Thus the LDPC decoding algorithm can be said to be communication-bound rather than computation-bound. In this thesis, a modification to the sum-product decoding algorithm called early-decision decoding is suggested. The modification is based on the idea that the values of the bits in a block can be decided individually during decoding. As the sum-product decoding algorithm is a soft-decision decoder, a reliability can be defined for each bit. When the reliability of a bit is above a certain threshold, the bit can be removed from the rest of the decoding process, and thus the internal communication associated with the bit can be removed in subsequent iterations. However, with the early decision modification, an increased error probability is associated. Thus, bounds on the achievable performance as well as methods to detect graph inconsistencies resulting from erroneous decisions are presented. Also, a hybrid decoder achieving a negligible performance penalty compared to the sum-product decoder is presented. With the hybrid decoder, the internal communication is reduced with up to 40% for a rate-1/2 code with a length of 1152 bits, whereas increasing the rate allows significantly higher gains. The algorithms have been implemented in a Xilinx Virtex 5 FPGA, and the resulting slice utilization andenergy dissipation have been estimated. However, due to increased logic overhead of the early decision decoder, the slice utilization increases from 14.5% to 21.0%, whereas the logic energy dissipation reduction from 499 pJ to 291 pJ per iteration and bit is offset by the clock distribution power, increased from 141 pJ to 191 pJ per iteration and bit. Still, the early decision decoder shows a net 16% estimated decrease of energy dissipation.

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This thesis is focused on the design and implementation of binary low-density parity-check (LDPC) code decoders for high-speed modern communication systems. The basic of LDPC codes and the performance and bottlenecks, in terms of complexity and hardware efficiency, of the main soft-decision and hard-decision decoding algorithms (such as Min-Sum, Optimized 2-bit Min-Sum and Reliability-based iterative Majority-Logic) are analyzed. The complexity and performance of those algorithms are improved to allow efficient hardware architectures.\n\nA new decoding algorithm called One-Minimum Min-Sum is proposed. It reduces considerably the complexity of the check node update equations of the Min-Sum algorithm. The second minimum is estimated from the first minimum value by a means of a linear approximation that allows a dynamic adjustment. The Optimized 2-bit Min-Sum algorithm is modified to initialize it with the complete LLR values and to introduce the extrinsic information in the messages sent from the variable nodes. Its variable node equation is reformulated to reduce its complexity. Both algorithms were tested for the (2048,1723) RS-based LDPC code and (16129,15372) LDPC code using an FPGA-based hardware emulator. They exhibit BER performance very close to Min-Sum algorithm and do not introduce early error-floor. \n\nIn order to show the hardware advantages of the proposed algorithms, hardware decoders were implemented in a 90 nm CMOS process and FPGA devices based on two types of architectures: full-parallel and partial-parallel one with horizontal layered schedule. The results show that the decoders are more area-time efficient than other published decoders and that the low-complexity of the Modified Optimized 2-bit Min-Sum allows the implementation of 10 Gbps decoders in current FPGA devices. \n\nFinally, a new hard-decision decoding algorithm, the Historical-Extrinsic Reliability-Based Iterative Decoder, is presented. This algorithm introduces the new idea of considering hard-decision votes as soft-decision to compute the extrinsic information of previous iterations. It is suitable for high-rate codes and improves the BER performance of the previous RBI-MLGD algorithms, with similar complexity.

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Abstract — Low-density parity-check codes have recently received extensive attention as a forward error correction scheme in a wide area of applications. The decoding algorithm is inherently parallelizable, allowing communication at high speeds. One of the main disadvantages, however, is large memory requirements for interim storing of decoding data. In this paper, we investigate a modification to the decoding algorithm, using early decisions for bits with high reliabilities. Currently, there are two early decision schemes proposed. We compare their theoretical performances and their suitability for hardware implementation. We also propose a new decision method, which we call weak decisions, that offers an increase in performance by a factor of two. 1

System-on-Chip Conference•Jan 1, 2005•1 citation
Since their rediscovery in 1995, low-density parity-check (LDPC) codes have received wide-spread attention as practical capacity-approaching code candidates. It has been shown that the class of codes can perform arbitrarily close to the channel capacity, and LDPC codes are also used or suggested for a number of important current and future communication standards. However, the problem of implementing an energy-efficient decoder has not yet been solved. Whereas the decoding algorithm is computationally simple, withuncomplicated arithmetic operations and low accuracy requirements, the random structure and irregularity of a theoretically well-defined code does not easily allow efficient VLSI implementations. Thus the LDPC decoding algorithm can be said to be communication-bound rather than computation-bound. In this thesis, a modification to the sum-product decoding algorithm called early-decision decoding is suggested. The modification is based on the idea that the values of the bits in a block can be decided individually during decoding. As the sum-product decoding algorithm is a soft-decision decoder, a reliability can be defined for each bit. When the reliability of a bit is above a certain threshold, the bit can be removed from the rest of the decoding process, and thus the internal communication associated with the bit can be removed in subsequent iterations. However, with the early decision modification, an increased error probability is associated. Thus, bounds on the achievable performance as well as methods to detect graph inconsistencies resulting from erroneous decisions are presented. Also, a hybrid decoder achieving a negligible performance penalty compared to the sum-product decoder is presented. With the hybrid decoder, the internal communication is reduced with up to 40% for a rate-1/2 code with a length of 1152 bits, whereas increasing the rate allows significantly higher gains. The algorithms have been implemented in a Xilinx Virtex 5 FPGA, and the resulting slice utilization andenergy dissipation have been estimated. However, due to increased logic overhead of the early decision decoder, the slice utilization increases from 14.5% to 21.0%, whereas the logic energy dissipation reduction from 499 pJ to 291 pJ per iteration and bit is offset by the clock distribution power, increased from 141 pJ to 191 pJ per iteration and bit. Still, the early decision decoder shows a net 16% estimated decrease of energy dissipation.
This thesis is focused on the design and implementation of binary low-density parity-check (LDPC) code decoders for high-speed modern communication systems. The basic of LDPC codes and the performance and bottlenecks, in terms of complexity and hardware efficiency, of the main soft-decision and hard-decision decoding algorithms (such as Min-Sum, Optimized 2-bit Min-Sum and Reliability-based iterative Majority-Logic) are analyzed. The complexity and performance of those algorithms are improved to allow efficient hardware architectures.\n\nA new decoding algorithm called One-Minimum Min-Sum is proposed. It reduces considerably the complexity of the check node update equations of the Min-Sum algorithm. The second minimum is estimated from the first minimum value by a means of a linear approximation that allows a dynamic adjustment. The Optimized 2-bit Min-Sum algorithm is modified to initialize it with the complete LLR values and to introduce the extrinsic information in the messages sent from the variable nodes. Its variable node equation is reformulated to reduce its complexity. Both algorithms were tested for the (2048,1723) RS-based LDPC code and (16129,15372) LDPC code using an FPGA-based hardware emulator. They exhibit BER performance very close to Min-Sum algorithm and do not introduce early error-floor. \n\nIn order to show the hardware advantages of the proposed algorithms, hardware decoders were implemented in a 90 nm CMOS process and FPGA devices based on two types of architectures: full-parallel and partial-parallel one with horizontal layered schedule. The results show that the decoders are more area-time efficient than other published decoders and that the low-complexity of the Modified Optimized 2-bit Min-Sum allows the implementation of 10 Gbps decoders in current FPGA devices. \n\nFinally, a new hard-decision decoding algorithm, the Historical-Extrinsic Reliability-Based Iterative Decoder, is presented. This algorithm introduces the new idea of considering hard-decision votes as soft-decision to compute the extrinsic information of previous iterations. It is suitable for high-rate codes and improves the BER performance of the previous RBI-MLGD algorithms, with similar complexity.
After the introduction of iterative coding, Low Density Parity Check (LDPC) codes have received a lot of attention due to their remarkable near Shannon-limit performance and practical decoder implementation. However, when employing an LDPC code for various applications, multiple issues do arise at the simulation, algorithm and implementation levels. The first issue is the performance evaluation of the iterative LDPC decoder in the very low Bit Error Rate (BER) regions. So far, no analytical tool has been developed to evaluate the performance of LDPC codes. Unfortunately standard Monte Carlo (MC) simulations cannot be used for performance estimation in these low BER regions due to prohibitive execution times. The second issue is the efficiency of the decoding algorithm. Due to the presence of short cycles in the bipartite graph, sum-product decoding algorithms lead to considerable performance loss for short block-length LDPC codes and produce error floors for longer codes. In addition, the iterative processing and estimation of soft probabilistic values with these algorithms result in very high computational complexity, which in turn impedes the adoption of LDPC codes for power constrained systems. Another prime objective is to design a high throughput decoder architecture which is capable of supporting multiple rates and variable code lengths within minimal area. This work aims to address and provide solutions to the above problems. As a solution to the performance estimation problem of LDPC codes, a highly efficient and novel fast BER simulation technique is developed. At the algorithm level, a performance improvement and error floor avoidance method is introduced, and a computationally efficient algorithm is developed for the sum-product decoding of LDPC codes. And finally, at the architecture level, a high throughput multi-rate variable code length implementation is presented which, when implemented, efficiently minimizes device resources while alleviating the routing complexity of the decoder.
Recent advances in coding theory have uncovered the previously forgotten power of Low-Density Parity-Check (LDPC) codes. Their popularity can be related to their relatively simple iterative decoders and their potential to achieve high performance close to shannon limit. These make them an attractive candidate for error correcting application in communication systems. In this thesis, we focus our research on the iterative decoding algorithms for Low-Density Parity-Check codes and present an improved decoding algorithm. First, the graph structure of LDPC codes is studied and a graph-based search algorithm to find the shortest closed walk and shortest cycle for each node of the graph is proposed. Then, the Deterministic schedule is applied on nodes of the graph with the objective of preserving the optimality of the algorithms. Finally, Hybrid Switch-Type technique is applied on the improved algorithms to provide a desirable complexity/performance trade-off. Hybrid Technique and Deterministic schedule are combined for decoding regular and irregular LDPC codes. The performance and complexity of the decoder is studied for Sum-Product and Gallager A algorithms. The result is a flexible decoder for any available LDPC code and any combination of decoding algorithms based on the communication systems need. In this technique, we benefit the high performance of soft-decision algorithms and low complexity of hard-decision algorithms by changing the decoding rule after a few iterations. Hence, a desirable performance can be obtained with less average number of soft iterations. Moreover, all the nodes do not update messages in each iteration. As a result, the total number of computations is reduced considerably
Low-density parity-check codes have recently received extensive attention as a forward error correction scheme in a wide area of applications. The decoding algorithm is inherently parallelizable, allowing communication at high speeds. One of the main disadvantages, however, is large memory requirements for interim storing of decoding data. In this paper, we investigate a modification to the decoding algorithm, using early decisions for bits with high reliabilities. This reduces the amount of messages passed by the algorithm, which can be expected to reduce the switching activity of a hardware implementation. While direct application of the modification results in severe performance penalties, we show how to adapt the algorithm to reduce the impact, resulting in a negligible decrease in error correction performance.
Low-density parity-check codes have recently received much attention because of their excellent performance and the availability of a simple iterative decoder. The decoder, however, requires large amounts of memory, which causes problems with memory consumption. We investigate a new decoding scheme for low density parity check codes to address this problem. The basic idea is to define a reliability measure and a threshold, and stop updating the messages for a bit whenever its reliability is higher than the threshold. We also consider some modifications to this scheme, including a dynamic threshold more suitable for codes with cycles, and a scheme with soft thresholds which allow the possibility of removing a decision which have proved wrong. By exploiting the bits different rates of convergence we are able to achieve an efficiency of up to 50% at a bit error rate of less than 10^-5. The efficiency should roughly correspond to the power consumption of a hardware implementation of the algorithm.
Abstract — Low-density parity-check codes have recently received extensive attention as a forward error correction scheme in a wide area of applications. The decoding algorithm is inherently parallelizable, allowing communication at high speeds. One of the main disadvantages, however, is large memory requirements for interim storing of decoding data. In this paper, we investigate a modification to the decoding algorithm, using early decisions for bits with high reliabilities. Currently, there are two early decision schemes proposed. We compare their theoretical performances and their suitability for hardware implementation. We also propose a new decision method, which we call weak decisions, that offers an increase in performance by a factor of two. 1