Structured root-LDPC codes and PEG-based techniques for block-fading channels

Uchôa, André Gustavo Degraf; Healy, Cornelius T.; Lamare, Rodrigo C. de

doi:10.1186/s13638-015-0439-6

Cited by 5 publications

(3 citation statements)

References 24 publications

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“…6 and 7 show the frame-error rate (FER) on a 2 × 2 channel with F = 2 and F = 4, respectively, using 2-PAM modulation. A regular, rate-1/F root-LDPC code [26] of length n = 208, constructed using a PEG-based technique [27], is used in each simulation. As can be seen, the simulations are consistent with the theoretical results, with a performance gap due to the small constellation size and the non-optimality of the channel code.…”

Section: Simulation Resultsmentioning

confidence: 99%

Low-Complexity Integer-Forcing Methods for Block Fading MIMO Multiple-Access Channels

Venturelli

Silva

2017

JCIS

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Abstract-Integer forcing is an alternative approach to conventional linear receivers for multiple-antenna systems. In an integer-forcing receiver, integer linear combinations of messages are extracted from the received matrix before each individual message is recovered. Recently, the integer-forcing approach was generalized to a block fading scenario. Among the existing variations of the scheme, the ones with the highest achievable rates have the drawback that no efficient algorithm is known to find the best choice of integer linear combination coefficients. In this paper, we propose several sub-optimal methods to find these coefficients with low complexity, covering both parallel and successive interference cancellation versions of the receiver. Simulation results show that the proposed methods attain a performance close to optimal in terms of achievable rates for a given outage probability. Moreover, a low-complexity implementation using root LDPC codes is developed, showing that the benefits of the proposed methods also carry on to practice.

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Section: Simulation Resultsmentioning

confidence: 99%

Low-Complexity Integer-Forcing Methods for Block Fading MIMO Multiple-Access Channels

Venturelli

Silva

2017

JCIS

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“…The BP decoder is a message-passing decoder with iterative processing over the factor graph of any polar code P(N,K) that has found numerous applications in wireless communications [14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37]. The factor graph is based on corresponding polarization matrix G ⊗n , composed of n = log 2 N stages, each one with N/2 processing elements (PEs), and (n + 1)N nodes.…”

Section: Belief Propagation Decodingmentioning

confidence: 99%

Decoding of Polar Codes Based on Q-Learning-Driven Belief Propagation

Oliveira

Oliveira²,

Lamare

2021

Preprint

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This paper presents an enhanced belief propagation (BP) decoding algorithm and a reinforcement learning-based BP decoding algorithm for polar codes. The enhanced BP algorithm weighs each Processing Element (PE) input based on their signals and Euclidean distances using a heuristic metric. The proposed reinforcement learning-based BP decoding strategy relies on reweighting the messages and consists of two steps: we first weight each PE input based on their signals and Euclidean distances using a heuristic metric, then a Q-learning algorithm (QLBP) is employed to figure out the best correction factor for successful decoding. Simulations show that the proposed enhanced BP and QLBP decoders outperform the successive cancellation (SC) and belief propagation (BP) decoders, and approach the SCL decoders.

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“…So, the decision g nodes depends on the estimate of f nodes given by (9), that is, of previously decoded bits. Message passing decoding that has found numerous applications in wireless communications [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [32], [31], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48] can also be considered.…”

Section: B Decodingmentioning

confidence: 99%

Study of Polar Codes Based on Piecewise Gaussian Approximation

Oliveira¹,

Lamare

2021

Preprint

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In this paper, we investigate the construction of polar codes by Gaussian approximation (GA) and develop an approach based on piecewise Gaussian approximation (PGA). In particular, with the piecewise approach we obtain a function that replaces the original GA function with a more accurate approximation, which results in significant gain in performance. The proposed PGA construction of polar codes is presented in its integral form as well as an alternative approximation that does not rely on the integral form. Simulations results show that the proposed PGA construction outperforms the standard GA for several examples of polar codes and rates.

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Structured root-LDPC codes and PEG-based techniques for block-fading channels

Cited by 5 publications

References 24 publications

Low-Complexity Integer-Forcing Methods for Block Fading MIMO Multiple-Access Channels

Low-Complexity Integer-Forcing Methods for Block Fading MIMO Multiple-Access Channels

Decoding of Polar Codes Based on Q-Learning-Driven Belief Propagation

Study of Polar Codes Based on Piecewise Gaussian Approximation

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