Iterative timing recovery via soft decision metrics of low-density parity-check decoding

Bao, Jianrong; Zhan, Yafeng; Lu, Jianhua

doi:10.1049/iet-com.2009.0747

Cited by 9 publications

(8 citation statements)

References 11 publications

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“…The received baseband signals are raised-cosine pulses from the combination of SRRC pulse-shaped filters located at the transmitters and receivers along with the AWGNs. In [6], the sampling positions approached the sampled points from LDPC decoding and corresponding analyses, which led to the increased absolute value of all LDPC decoding metrics, i.e., log-likelihood ratios (LLRs). A similar effect of the sum of all LLR squares under these timing errors also manifested.…”

Section: Influence Of Timing Errors On Ldpc Decodingmentioning

confidence: 99%

“…Moreover, m (k−1) u is assigned to a zero mean value, because initial messages from all check nodes are zero. The updated messages coming from check nodes to variable nodes are presented similar to [6] as…”

Section: ) Update the Variable Nodes And Perform The Final Decoding Judgmentmentioning

confidence: 99%

“…However, it suffered from insufficient hard metrics, or unreliable satisfaction percentages of decoded codewords for the parity check equation for just few iterations [4,5]. Studies also suggested the use of timing recovery based on soft LDPC metrics with complex optimization calculations [6]. Other expectation maximization (EM)-based timing recovery methods for turbo or LDPC coding have also been suggested [7,8].…”

Section: Introductionmentioning

confidence: 99%

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Efficient Iterative Timing Recovery of Low-Density Parity-Check Decoding Metrics Using the Steepest Descent Algorithm for Satellite Communications at Low SNRs

et al. 2021

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An efficient iterative timing recovery via steepest descent of low-density parity-check (LDPC) decoding metrics is presented. In the proposed algorithm, a more accurate symbol timing synchronization is achieved at a low signal-to-noise (SNR) without any pilot symbol by maximizing the sum of the square of all soft metrics in LDPC decoding. The principle of the above-proposed algorithm is analyzed theoretically with the evolution trend of the probability mean of the soft LDPC decoding metrics by the Gaussian approximation. In addition, an efficiently approximate gradient descent algorithm is adopted to obtain excellent timing recovery with rather low complexity and global convergence. Finally, a complete timing recovery is accomplished where the proposed scheme performs fine timing capture, followed by a traditional Mueller–Müller (M&M) timing recovery, which acquires timing track. Using the proposed iterative timing recovery method, the simulation results indicate that the performance of the LDPC coded binary phase shift keying (BPSK) scheme with rather large timing errors is just within 0.1 dB of the ideal code performance at the cost of some rational computation and storage. Therefore, the proposed iterative timing recovery can be efficiently applied on occasions of the weak signal timing synchronization in satellite communications and so on.

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Section: Influence Of Timing Errors On Ldpc Decodingmentioning

confidence: 99%

Section: ) Update the Variable Nodes And Perform The Final Decoding Judgmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Efficient Iterative Timing Recovery of Low-Density Parity-Check Decoding Metrics Using the Steepest Descent Algorithm for Satellite Communications at Low SNRs

et al. 2021

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“…According to Fig. 8, we propose a detection algorithm, namely multi-carrier joint detection [20][21][22][23][24][25]. The received signal in AWGN can be expressed as…”

Section: Multi-carrier Joint Detection (Mjd)mentioning

confidence: 99%

Efficient modulation and demodulation methods for multi‐carrier communication

Chen

2016

IET Communications

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“…Code-aided synchronisation just utilises this relationship to assist signal demodulation under low SNR. The author designed a joint demodulation and decoding algorithm [23] using the sum of the absolute values of LLR of LDPC decoding as the target function of the synchronisation loop. To maximise the target function by iteration, all the synchronisation parameters could be estimated.…”

Section: Code-aided Synchronisationmentioning

confidence: 99%

Robust algorithm for high‐dynamic and low‐signal‐to‐noise ratio signal reception in deep space communications

et al. 2013

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In deep space communications, the received signals are always highly dynamic and very weak, which makes it quite challenging to achieve reliable data reception. To tackle these problems, a robust algorithm which joins tracking and code-aided synchronisation is proposed in this study. The frequency lock loop-assisted phase lock loop is used as the tracking loop, which integrates the characteristics of both outstanding dynamic performance and precise measurement. The code-aided synchronisation is adopted as the demodulation and decoding loop, which utilises the relationship among the coded symbols to assist signal demodulation under the low signal-to-noise ratio condition. It is worth pointing out that the power tradeoff between the main carrier and subcarrier signals which operate in the two loops mentioned above is also optimised to minimise the total transmitting power. Simulation results showed that the proposed scheme with code rate 1/5 low-density parity-check codes could almost eliminate the effect of these factors, with the excellent performance, which closely approximates the ideal decoder in additive white Gaussian noise channel.

show abstract

Iterative timing recovery via soft decision metrics of low-density parity-check decoding

Cited by 9 publications

References 11 publications

Efficient Iterative Timing Recovery of Low-Density Parity-Check Decoding Metrics Using the Steepest Descent Algorithm for Satellite Communications at Low SNRs

Efficient Iterative Timing Recovery of Low-Density Parity-Check Decoding Metrics Using the Steepest Descent Algorithm for Satellite Communications at Low SNRs

Efficient modulation and demodulation methods for multi‐carrier communication

Robust algorithm for high‐dynamic and low‐signal‐to‐noise ratio signal reception in deep space communications

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