Implicit vs. Explicit Approximate Matrix Inversion for Wideband Massive MU-MIMO Data Detection
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Signal Processing Systems"
DOI: 10.1007/s11265-017-1313-z
Abstract: Massive multi-user (MU) MIMO wireless technology promises improved spectral efficiency compared to that of traditional cellular systems. While data-detection algorithms that rely on linear equalization achieve near-optimal error-rate performance for massive MU-MIMO systems, they require… read more here.
Keywords: detection; data detection; implicit explicit; matrix inversion ... See more keywords
Abnormal data detection for industrial processes using adversarial autoencoders support vector data description
Sign Up to like & getrecommendations! Published in 2022 at "Measurement Science and Technology"
DOI: 10.1088/1361-6501/ac4f02
Abstract: Abnormal data detection for industrial processes is essential in industrial process monitoring and is an important technology to ensure production safety. However, for most industrial processes, it is a challenge to establish an effective abnormal… read more here.
Keywords: data detection; detection; industrial processes; model ... See more keywords
A novel abnormal data detection method based on dynamic adaptive local outlier factor for the vibration signals of rotating parts
Sign Up to like & getrecommendations! Published in 2023 at "Measurement Science and Technology"
DOI: 10.1088/1361-6501/accbda
Abstract: Abnormal signals are inevitable in big data acquired from harsh industrial environments. Abnormal data detection is a crucial component of condition monitoring for rotating parts and is also the premise of data cleaning, compensation, and… read more here.
Keywords: abnormal data; rotating parts; method based; data detection ... See more keywords
A Low Complexity Data Detection Algorithm for Uplink Multiuser Massive MIMO Systems
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Journal on Selected Areas in Communications"
DOI: 10.1109/jsac.2017.2710878
Abstract: A major challenge for uplink multiuser massive multiple-input and multiple-output (MIMO) systems is the data detection problem at the receiver due to the substantial increase in the dimensions of MIMO systems. The optimal maximum likelihood… read more here.
Keywords: data detection; complexity; uplink multiuser; multiuser massive ... See more keywords
Data Detection With CFO Uncertainty and Nonlinearity for mmWave MIMO-OFDM Systems
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Systems Journal"
DOI: 10.1109/jsyst.2021.3093333
Abstract: The nonlinear distortions attributed by radio frequency power amplifiers (PAs) are inevitable in millimeter-wave (mmWave) systems due to the high frequency and large bandwidth. This nonlinearity induces multiplicative distortion and intercarrier interference in mmWave multiple-input-multiple-output… read more here.
Keywords: detection cfo; nonlinearity; frequency; data detection ... See more keywords
Multiuser Activity and Data Detection via Sparsity-Blind Greedy Recovery for Uplink Grant-Free NOMA
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2019.2937117
Abstract: Exploiting the sparse activity of users, compressed sensing (CS) has been of interest in multiuser detection (MUD) for non-orthogonal multiple access (NOMA), to enable a massive connection of users in machine-type communications (MTC). In this… read more here.
Keywords: activity data; activity; multiuser activity; sparsity ... See more keywords
Learning From Noisy Labels for MIMO Detection With One-Bit ADCs
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Wireless Communications Letters"
DOI: 10.1109/lwc.2022.3230403
Abstract: This letter presents a data detection method for multiple-input multiple-output systems with one-bit analog-to-digital converters. The basic idea is to learn the likelihood function of the system from training samples. To this end, a training… read more here.
Keywords: noisy labels; one bit; data detection; learning noisy ... See more keywords
Bad Data Detection in the Context of Leverage Point Attacks in Modern Power Networks
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Smart Grid"
DOI: 10.1109/pesgm.2017.8274244
Abstract: This paper demonstrates a concept to detect bad data in state estimation when the leverage measurements are tampered with gross error. The concept is based on separating leverage measurements from non-leverage measurements by a technique… read more here.
Keywords: data detection; bad data; leverage measurements; power ... See more keywords
Joint Bayesian Channel Estimation and Data Detection for OTFS Systems in LEO Satellite Communications
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Communications"
DOI: 10.1109/tcomm.2022.3179389
Abstract: Lower earth orbit (LEO) satellites play an important role in the integration of space and terrestrial communication networks, which typically encounter high-mobility scenarios. It has been shown that orthogonal time frequency space (OTFS) modulation performs… read more here.
Keywords: satellite communications; leo satellite; estimation data; channel estimation ... See more keywords
Abnormal Data Detection Based on Adaptive Sliding Window and Weighted Multiscale Local Outlier Factor for Machinery Health Monitoring
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Industrial Electronics"
DOI: 10.1109/tie.2022.3231279
Abstract: Identifying abnormal data to improve data quality is of great importance for machinery health monitoring (MHM). Existing abnormal data detection methods generally depend on appropriate parameter settings and prior knowledge of data distribution, which result… read more here.
Keywords: abnormal data; data detection; outlier factor; detection ... See more keywords
Distributed Kalman-Like Filtering and Bad Data Detection in the Large-Scale Power System
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2021.3119136
Abstract: This article investigates the distributed state estimation problem for large-scale power systems with the appearance of bad data. The power system is decomposed into several nonoverlapping agents and these agents interact with each other through… read more here.
Keywords: power system; power; data detection; measurement ... See more keywords