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IEEE International Symposium on Circuits and Systems proceedings

Scheduling Algorithm for Partially Parallel Architecture of LDPC Decoder by Matrix Permutation

In‐Cheol Park, Se-Hyeon Kang

Published Jul 27, 2005• 27 citations
Publisher

Abstract

The fully parallel LDPC decoding architecture can achieve high decoding throughput, but it suffers from large hardware complexity caused by a large set of processing units (PUs) and complex interconnections. A practical solution of area-efficient decoders is to use the partially parallel architecture in which a PU is shared for several rows or columns. It is important in the partially parallel architecture to determine the rows or columns to be processed in a PU and their processing order. The dependencies between rows and columns should be considered to minimize the overall processing time by overlapping the decoding operations. This paper proposes an efficient scheduling algorithm that can be applied to general LDPC codes, which is based on the concept of matrix permutation. Experimental results show that the proposed scheduling achieves a higher decoding rate, leading to a reduction of 25% processing time on average. A 1024-bit rate-1/2 LDPC decoder, employing the proposed scheduling algorithm, provides almost 1 Gbps decoding throughput and occupies one-fifth the area compared to the fully parallel decoder.

DOI
10.1109/iscas.2005.1465951

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The fully parallel LDPC decoding architecture can achieve high decoding throughput, but it suffers from large hardware complexity caused by a large set of processing units (PUs) and complex interconnections. A practical solution of area-efficient decoders is to use the partially parallel architecture in which a PU is shared for several rows or columns. It is important in the partially parallel architecture to determine the rows or columns to be processed in a PU and their processing order. The dependencies between rows and columns should be considered to minimize the overall processing time by overlapping the decoding operations. This paper proposes an efficient scheduling algorithm that can be applied to general LDPC codes, which is based on the concept of matrix permutation. Experimental results show that the proposed scheduling achieves a higher decoding rate, leading to a reduction of 25% processing time on average. A 1024-bit rate-1/2 LDPC decoder, employing the proposed scheduling algorithm, provides almost 1 Gbps decoding throughput and occupies one-fifth the area compared to the fully parallel decoder.
In this paper, we propose a partially-parallel LDPC decoder which achieves a high-efficiency message-passing schedule. The proposed LDPC decoder is characterized as follows: (i) The column operations follow the row operations in a pipelined architecture to ensure that the row and column operations are performed concurrently. (ii) The proposed parallel pipelined bit functional unit enables the column operation module to compute every message in each bit node which is updated by the row operations. These column operations can be performed without extending the single iterative decoding delay when the row and column operations are performed concurrently. Therefore, the proposed decoder performs the column operations more frequently in a single iterative decoding, and achieves a high-efficiency message-passing schedule within the limited decoding delay time. Hardware implementation on an FPGA and simulation results show that the proposed partially-parallel LDPC decoder improves the decoding throughput and bit error performance with a small hardware overhead.
In this paper, an area efficient partially parallel decoder architecture suited for (modified) min-sum decoding algorithm for general high rate quasi-cyclic low-density parity-check (QC-LDPC) codes is proposed. To reduce the hardware complexity for parallel processing, an efficient data scheduling unit is presented. The optimized partially parallel decoder architecture can linearly increase the decoding throughput with small hardware overhead. Typically, over 30% of memory can be saved with the architecture presented in this paper. Consequently, the proposed approach facilitates the applications of LDPC codes in area/power sensitive high speed communication systems.
In this work, a high performance LDPC decoder architecture is presented. It is a partially-parallel architecture for low-complexity consideration. In order to eliminate the idling time and hardware complexity in conventional partially-parallel decoders, the decoding process, decoder architecture and memory structure are optimized. Particularly, the parity-check matrix is optimally partitioned into four unequal sub-matrices that lead to high efficiency in hardware sharing. As a result, it can handle two different codewords simultaneously with 100% hardware utilization. Furthermore, for minimizing the performance loss due to round-off errors in fixed-point implementations, the well-known modified min-sum decoding algorithm is enhanced by our recently proposed high-performance CMVP decoding algorithm. Overall, the proposed decoder has high throughput, low complexity, and good BER performances. In the circuit implementation example of the (576, 288) parity check matrix for IEEE 802.16e standard, the decoder achieves a data rate of 5.5Gbps assuming 10 decoding iterations and 7 quantization bits, with a small area of 653K gates, based on UMC 90nm process technology.
This paper proposes a parallel LSI architecture for LDPC decoder which improves a message-passing schedule. The proposed LDPC decoder is characterized as follows: (i) the column operations follow the row operations in a pipelined architecture to ensure that the row and column operations are performed concurrently; and (ii) the proposed parallel pipelined bit functional unit enables the decoder to perform every column operation using the messages which is updated by the row operations. These column operations can be performed without extending the single iterative decoding delay. Hardware implementation and simulation results show that the proposed decoder improves the decoding throughput and bit error performance with a small hardware overhead
This paper proposes a partially-parallel LDPC decoder based on a high-efficiency message-passing algorithm. Our proposed partially-parallel LDPC decoder performs the column operations for bit nodes in conjunction with the row operations for check nodes. Bit functional unit with pipeline architecture in our LDPC decoder allows us to perform column operations for every bit node connected to each of check nodes which are updated by the row operations in parallel. Our proposed LDPC decoder improves the tuning when the column operations are performed, accordingly it improves the message-passing efficiency within the limited number of iterations for decoding. We implemented the proposed partially-parallel LDPC decoder on an FPGA, and simulated its decoding performance. Practical simulation shows that our proposed LDPC decoder reduces the number of iterations for decoding, and it improves the bit error performance with a small hardware overhead.
Layered decoding of Low Density Parity Check (LDPC) codes has been shown to give faster convergence and use less storage than the conventional Two Phase Message Passing (TPMP) algorithm in decoding such codes. To achieve higher throughput, multiple rows of the parity check matrix may be decoded in parallel, as in the Parallel-Turbo Decoding Message Passing (P-TDMP) algorithm. However, contention for globally shared memory permits only a subset of rows to be decoded in parallel thus limiting overall throughput. This paper uses a near optimal scheduling algorithm, based on graph colouring, to overcome memory contention, allowing processing of multiple rows without code modification, resulting in significant throughput gains over the standard P-TDMP algorithm. For the LDPC codes studied, throughput gains compared to the P-TDMP algorithm, of between ten and fifteen are shown to be possible.