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ECG-biometrics-bench: A Unified Framework for Reproducible Benchmarking of ECG Biometrics Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning Towards Improving Speaker Distance Estimation through Generative Impulse Response Augmentation Federated Learning with Hypergradient-based Online Update of Aggregation Weights Soft Graph Diffusion Transformer for MIMO Detection SPLICE: Latent Diffusion over JEPA Embeddings for Conformal Time-Series Inpainting Sequential Inference for Gaussian Processes: A Signal Processing Perspective Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework Recent Advances in mm-Wave and Sub-THz/THz Oscillators for FutureG Technologies Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods Super-resolution Multi-signal Direction-of-Arrival Estimation by Hankel-structured Sensing and Decomposition Hankel and Toeplitz Rank-1 Decomposition of Arbitrary Matrices with Applications to Signal Direction-of-Arrival Estimation Adaptive Transform Coding for Semantic Compression EdgeSpike: Spiking Neural Networks for Low-Power Autonomous Sensing in Edge IoT Architectures Sparse Graph Learning from Sparse Data via Fiedler Number Maximization A Deep Learning Model for Battery State Prediction towards Intelligent Energy Management Transfer Learning for Tonal Noise Prediction in VRF Units Using Thermodynamic and Vibration Signals EVT-Based Generative AI for Tail-Aware Channel Estimation Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing BandRouteNet: An Adaptive Band Routing Neural Network for EEG Artifact Removal Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface Selective Correlation Based Knowledge Distillation for Ground Reaction Force Estimation Deep Learning-Enabled Dissolved Oxygen Sensing in Biofouling Environments for Ocean Monitoring Speech Enhancement Based on Drifting Models Robust and Clinically Reliable EEG Biomarkers: A Cross Population Framework for Generalizable Parkinson's Disease Detection An AI-Based Supervisory Measurement Integrity Validation Layer for Cyber-Resilient AC/DC Protection in Inverter-Based Microgrids Explainable AI in Speaker Recognition -- Making Latent Representations Understandable Time-Localized Parametric Decomposition of Respiratory Airflow for Sub-Breath Analysis NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals An Algorithm for On-Sensor Agnostic Detection of Changes in Human Activity for Ultra-Low-Power Applications
Analysis and Comparison of the LDPC and Reed Solomon Enco...
Nima Taherkhani, Merve Apalak, Kamran Kiasaleh · 2019-09-23 · via eess.SP updates on arXiv.org

The linear error-correcting codes are known to be well suited for battling and correcting the burst errors caused by noise in the wireless data transmission system. However, different types of codes offer different decoding and burst-error-correcting capabilities. This paper compares the Low-Density-Parity Check (LDPC) and Reed Solomon (RS) encoding schemes in battling and correcting the burst error caused by the clipping distortion occurred due to the dynamic range constraints in an Orthogonal Frequency Division Multiplexing (OFDM) based Visible Light Communication (VLC). The unipolar conversion applied to the output of the multiplexer in this system results in a clipping noise which distorts the data symbols on the subcarriers in OFDM block. Considering that such distortion impacts the data symbol on each subcarrier differently, RS and LDP are used to encode the data block before being modulated for mapping the OFDM block. In order to control the extreme value of the output of the multiplexer, the transmitter applies puncturing to the generated codeword before mapping OFDM subcarriers, leaving the corresponding subcarriers of the punctured symbols empty. This will lead to the reduction of clipping events in the optical front-end and will mitigate the impact of nonlinear distortion on the modulated symbols for the occupied subcarriers. The redundancy in the codeword generated by the encoder is used not only to control the clipping probability by shortening the number of active subcarriers but also for the reconstruction of the original codeword and correction of the errors caused by channel noise. This work investigates the ability of LDCP and RS encoders in battling the effects of clipping noise in the frequency domain and compares their performances in improving the bit error ratio (BER) performance of an OFDM-based VLC.