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Found 10 papers, 2 papers with code
Sensor Fusion and Resource Management in MIMO-OFDM Joint Sensing and Communication
This study explores the promising potential of integrating sensing capabilities into multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM)-based networks through innovative multi-sensor fusion techniques, tracking algorithms, and resource management.
Multi-Base Station Cooperative Sensing with AI-Aided Tracking
In this work, we investigate the performance of a joint sensing and communication (JSC) network consisting of multiple base stations (BSs) that cooperate through a fusion center (FC) to exchange information about the sensed environment while concurrently establishing communication links with a set of user equipments (UEs).
Reconstruction-based LSTM-Autoencoder for Anomaly-based DDoS Attack Detection over Multivariate Time-Series Data
In this research, we trained and evaluated our proposed LSTM-AE model on reflection-based DDoS attacks (DNS, LDAP, and SNMP).
CTT-Net: A Multi-view Cross-token Transformer for Cataract Postoperative Visual Acuity Prediction
Clinically, to assess the necessity of cataract surgery, accurately predicting postoperative VA before surgery by analyzing multi-view optical coherence tomography (OCT) images is crucially needed.
Learning Quantization in LDPC Decoders
Finding optimal message quantization is a key requirement for low complexity belief propagation (BP) decoding.
LSTM-Autoencoder based Anomaly Detection for Indoor Air Quality Time Series Data
Anomaly detection for indoor air quality (IAQ) data has become an important area of research as the quality of air is closely related to human health and well-being.
IGRF-RFE: A Hybrid Feature Selection Method for MLP-based Network Intrusion Detection on UNSW-NB15 Dataset
Then, we apply recursive feature elimination(RFE) as a wrapper feature selection method to further eliminate redundant features recursively on the reduced feature subsets.
Training a Bidirectional GAN-based One-Class Classifier for Network Intrusion Detection
The network intrusion detection task is challenging because of the imbalanced and unlabeled nature of the dataset it operates on.
Tensor-based Basis Function Learning for Three-dimensional Sound Speed Fields
In particular, a tensor-based basis function learning framework is proposed, which can include the classical basis functions (using EOFs and/or Fourier basis functions) as its special cases.
Scoring the Terabit/s Goal:Broadband Connectivity in 6G
Several categories of enablers at the infrastructure, spectrum, and protocol/algorithmic levels are required to realize the intended broadband connectivity goals in 6G.
