Low-Complexity High-Throughput QC-LDPC Decoder for 5G New Radio Wireless Communication

This paper presents a pipelined layered quasi-cyclic low-density parity-check (QC-LDPC) decoder architecture targeting low-complexity, high-throughput, and efficient use of hardware resources compliant with the specifications of 5G new radio (NR) wireless communication standard. First, a combined min-sum (CMS) decoding algorithm, which is a combination of the offset min-sum and the original min-sum algorithm, is proposed. Then, a low-complexity and high-throughput pipelined layered QC-LDPC decoder architecture for enhanced mobile broadband specifications in 5G NR wireless standards based on CMS algorithm with pipeline layered scheduling is presented. Enhanced versions of check node-based processor architectures are proposed to improve the complexity of the LDPC decoders. An efficient minimum-finder for the check node unit architecture that reduces the hardware required for the computation of the first two minima is introduced. Moreover, a low complexity a posteriori information update unit architecture, which only requires one adder array for their operations, is presented. The proposed architecture shows significant improvements in terms of area and throughput compared to other QC-LDPC decoder architectures available in the literature.

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Reduced-complexity offset min-sum check node unit for layered 5G LDPC decoder

Telfor Journal ◽

10.5937/telfor2101007p ◽

2021 ◽

Vol 13 (1) ◽

pp. 7-12

Author(s):

Vladimir Petrović ◽

Mezeni El

Keyword(s):

Parity Check ◽

Ldpc Decoder ◽

Low Density Parity Check ◽

Novel Approach ◽

New Radio ◽

Variable Weight ◽

Decoder Architecture ◽

Check Node ◽

Higher Weights ◽

Reduced Complexity

This paper presents a novel approach for the reduced-complexity Min-Sum (MS) decoding of low density parity check (LDPC) codes in the partially parallel layered decoder architecture, which contains a large number of serial check node processors. Reduced complexity is obtained by using the variant of the single-minimum Offset Min-Sum (smOMS) algorithm that approximates a second minimum with the addition of the variable weight parameter to the minimum value. Although the reduced-complexity MS algorithms primarily reduce hardware resources in fully parallel implementations, the results showed that a considerable reduction can be obtained if serial check node processors are used. The paper also proposes a better subminimum estimation for irregular codes from 5G new radio (5G NR). The method uses smaller subminimum estimation weights in check nodes with a higher degree and higher weights in check nodes with a smaller degree, which leads to the significant improvement in the SNR performance. Additionally, it is shown that SNR performance can be further improved by applying offset before minimum calculation, which differs from conventional Min-Sum approaches.

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A high throughput architecture for a low complexity soft-output demapping algorithm

Advances in Radio Science ◽

10.5194/ars-13-73-2015 ◽

2015 ◽

Vol 13 ◽

pp. 73-80 ◽

Cited By ~ 1

Author(s):

I. Ali ◽

U. Wasenmüller ◽

N. Wehn

Keyword(s):

Wireless Communication ◽

High Throughput ◽

Turbo Code ◽

Low Complexity ◽

Implementation Cost ◽

Qam Modulation ◽

Iterative Systems ◽

Very High ◽

Complexity Algorithm ◽

Hardware Performance

Abstract. Iterative channel decoders such as Turbo-Code and LDPC decoders show exceptional performance and therefore they are a part of many wireless communication receivers nowadays. These decoders require a soft input, i.e., the logarithmic likelihood ratio (LLR) of the received bits with a typical quantization of 4 to 6 bits. For computing the LLR values from a received complex symbol, a soft demapper is employed in the receiver. The implementation cost of traditional soft-output demapping methods is relatively large in high order modulation systems, and therefore low complexity demapping algorithms are indispensable in low power receivers. In the presence of multiple wireless communication standards where each standard defines multiple modulation schemes, there is a need to have an efficient demapper architecture covering all the flexibility requirements of these standards. Another challenge associated with hardware implementation of the demapper is to achieve a very high throughput in double iterative systems, for instance, MIMO and Code-Aided Synchronization. In this paper, we present a comprehensive communication and hardware performance evaluation of low complexity soft-output demapping algorithms to select the best algorithm for implementation. The main goal of this work is to design a high throughput, flexible, and area efficient architecture. We describe architectures to execute the investigated algorithms. We implement these architectures on a FPGA device to evaluate their hardware performance. The work has resulted in a hardware architecture based on the figured out best low complexity algorithm delivering a high throughput of 166 Msymbols/second for Gray mapped 16-QAM modulation on Virtex-5. This efficient architecture occupies only 127 slice registers, 248 slice LUTs and 2 DSP48Es.

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