Design and Evaluation of Information Bottleneck LDPC Decoders for Software Defined Radios

Lewandowsky, Jan; Bauch, Gerhard; Tschauner, Matthias; Oppermann, Peter

doi:10.1109/icspcs.2018.8631719

Cited by 5 publications

(2 citation statements)

References 13 publications

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“…6 It is worth mentioning that h(T ) in Fig. 6(b) was used in [19] and [20] to implement check node update for decoding regular LDPC codes with variable node degree 3 and check node degree 6.…”

Section: B Computation Treesmentioning

confidence: 99%

A Class of Optimal Structures for Node Computations in Message Passing Algorithms

He¹,

Cai²,

Zhou³

2020

Preprint

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Consider the computations at a node in the message passing algorithms. Assume that the node has incoming and outgoing messages x = (x1, x2, . . . , xn) and y = (y1, y2, . . . , yn), respectively. In this paper, we investigate a class of structures that can be adopted by the node for computing y from x, where each yj, j = 1, 2, . . . , n is computed via a binary tree with leaves x excluding xj. We have three main contributions regarding this class of structures. First, we prove that the minimum complexity of such a structure is 3n − 6, and if a structure has such complexity, its minimum latency is δ + log(n − 2 δ ) with δ = log(n/2) . Second, we prove that the minimum latency of such a structure is log(n − 1) , and if a structure has such latency, its minimum complexity is n log(n − 1) when n − 1 is a power of two. Third, given (n, τ ) with τ ≥ log(n − 1) , we propose a construction for a structure which likely has the minimum complexity among structures with latencies at most τ . Our construction method runs in O(n 3 log 2 (n)) time, and the obtained structure has complexity at most (generally much smaller than) n log(n) − 2.

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Section: B Computation Treesmentioning

confidence: 99%

A Class of Optimal Structures for Node Computations in Message Passing Algorithms

He¹,

Cai²,

Zhou³

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Moreover, all expensive operations were replaced by simple lookup operations in the designed mutual-informationmaximizing lookup tables. In [13] and [14] it was shown that this approach is, in fact, beneficial in comparison to state-ofthe-art LDPC decoders in practical decoder implementations. The applied mutual-information-maximizing lookup tables can be constructed using the information bottleneck method [15].…”

Section: Introductionmentioning

confidence: 99%

Decoding of Non-Binary LDPC Codes using the Information Bottleneck Method

Stark¹,

Bauch²,

Lewandowsky³

et al. 2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

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Recently, a novel lookup table based decoding method for binary low-density parity-check codes has attracted considerable attention. In this approach, mutual-informationmaximizing lookup tables replace the conventional operations of the variable nodes and the check nodes in message passing decoding. Moreover, the exchanged messages are represented by integers with very small bit width. A machine learning framework termed the information bottleneck method is used to design the corresponding lookup tables. In this paper, we extend this decoding principle from binary to non-binary codes. This is not a straightforward extension but requires a more sophisticated lookup table design to cope with the arithmetic in higher order Galois fields. Provided bit error rate simulations show that our proposed scheme outperforms the log-max decoding algorithm and operates close to sum-product decoding.

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A Discrete Detection and Decoding of MLC NAND Flash Memory With Retention Noise

Sun

Zheng

2020

IEEE Access

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The retention noise in MLC NAND flash memory has a great impact on reliability and lifetime of devices. How to recover information from the data corrupted by retention noise is a challenging problem. The joint processing of channel estimation, detection and low-density parity-check (LDPC) decoding is an effective method to handle this problem, while which is hindered by the limited computational resource of NAND flash memory devices. This paper proposes a discrete retention-failure recovery method, where the reading system only processes integers. The proposed method consists of two major components referred to binary tree searching (BTS) based channel updating and information bottleneck (IB) based LDPC decoding. In channel updating, the proposed learning based BTS algorithm can acquire reference voltages directly; thus it bypasses the intermediate stage of retention noise parameter estimation. The LDPC decoder is realized by IB based message passing, where node operation is achieved by lookup tables, and the messages passed between nodes are integers. Besides, a dynamic quantization level reduction strategy for IB based decoding is proposed to reduce the memory consumption of lookup tables. Finally, using PEG-constructed regular LDPC code (8000, 7200), the numerical results show that the proposed discrete method has much lower computational complexity and similar performance compared with the conventional method.

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Design and Evaluation of Information Bottleneck LDPC Decoders for Software Defined Radios

Cited by 5 publications

References 13 publications

A Class of Optimal Structures for Node Computations in Message Passing Algorithms

A Class of Optimal Structures for Node Computations in Message Passing Algorithms

Decoding of Non-Binary LDPC Codes using the Information Bottleneck Method

A Discrete Detection and Decoding of MLC NAND Flash Memory With Retention Noise

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