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

Electronics ◽  
2021 ◽  
Vol 10 (24) ◽  
pp. 3055
Author(s):  
Yu Qiu ◽  
Chao Liu ◽  
Jianrong Bao ◽  
Bin Jiang ◽  
Yanhai Shang

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.

Author(s):  
Mouhcine Razi ◽  
Mhammed Benhayoun ◽  
Anass Mansouri ◽  
Ali Ahaitouf

<span lang="EN-US">For low density parity check (LDPC) decoding, hard-decision algorithms are sometimes more suitable than the soft-decision ones. Particularly in the high throughput and high speed applications. However, there exists a considerable gap in performances between these two classes of algorithms in favor of soft-decision algorithms.  In order to reduce this gap, in this work we introduce two new improved versions of the hard-decision algorithms, the adaptative gradient descent bit-flipping (AGDBF) and adaptative reliability ratio weighted GDBF (ARRWGDBF).  An adaptative weighting and correction factor is introduced in each case to improve the performances of the two algorithms allowing an important gain of bit error rate. As a second contribution of this work a real time implementation of the proposed solutions on a digital signal processors (DSP) is performed in order to optimize and improve the performance of these new approchs. The results of numerical simulations and DSP implementation reveal a faster convergence with a low processing time and a reduction in consumed memory resources when compared to soft-decision algorithms. For the irregular LDPC code, our approachs achieves gains of 0.25 and 0.15 dB respectively for the AGDBF and ARRWGDBF algorithms.</span>


2013 ◽  
Vol 32 (11) ◽  
pp. 3100-3101
Author(s):  
Jiong-cheng LI ◽  
Gui-yu LI ◽  
Heng-hui XIAO ◽  
Hai-yi HUANG

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