Gradient Bit-Flipping LDPC Decoder for ATSC 3.0

Jerji, Fadi; Akamine, Cristiano

doi:10.1109/bmsb47279.2019.8971839

Cited by 6 publications

(1 citation statement)

References 14 publications

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“…For the AWGN case, the performance was compared using the bit error rate (BER) as the figure of merit for a range of SNR values, and low‐density parity‐check (LDPC) channel coding using the gradient bit‐flapping (GBF) algorithm with a code rate of 2/16 [12]. As can be observed from Figure 3, the FC‐DNN surpasses the ZF estimator performance for all simulated SNR values.…”

Section: Simulations Resultsmentioning

confidence: 99%

Neural network channel estimator for time‐variant frequency‐selective fading channels

Barragam,

Jerji,

Akamine

2023

Electronics Letters

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The next generations of wireless communications systems are pushing the limits of the channel estimation methods utilized in the orthogonal frequency division multiplexing receptors. This letter proposes a novel channel estimation method using a densely connected neural network considering the time‐variant frequency‐selective fading channel model. A fully connected deep neural network for the AWGN channel case is also proposed. The comparative complexity of the estimation for different channel models is also discussed. The simulation results demonstrate that the densely connected neural network method surpasses the minimum mean‐square error method performance for a signal‐to‐noise ratio ranging from 0 to 25 dB in the frequency‐selective channel.

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Section: Simulations Resultsmentioning

confidence: 99%