Essays about: "channel estimation error"
Showing result 1 - 5 of 45 essays containing the words channel estimation error.
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1. Heart rate estimation from wrist-PPG signals in activity by deep learning methods
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In the context of health improving, the measurement of vital parameters such as heart rate (HR) can provide solutions for health monitoring, prevention and screening for certain chronic diseases. Among the different technologies for HR measuring, photoplethysmography (PPG) technique embedded in smart watches is the most commonly used in the field of consumer electronics since it is comfortable and does not require any user intervention. READ MORE
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2. Network Orientation and Segmentation Refinement Using Machine Learning
University essay from Linköpings universitet/Institutionen för medicinsk teknikAbstract : Network mapping is used to extract the coordinates of a network's components in an image. Furthermore, machine learning algorithms have demonstrated their efficacy in advancing the field of network mapping across various domains, including mapping of road networks and blood vessel networks. READ MORE
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3. Channel Estimation Optimization in 5G New Radio using Convolutional Neural Networks
University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)Abstract : Channel estimation is the process of understanding and analyzing the wireless communication channel's properties. It helps optimize data transmission by providing essential information for adjusting encoding and decoding parameters. READ MORE
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4. Deep Neural Networks for dictionary-based 5G channel estimation with no ground truth in mixed SNR scenarios
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Channel estimation is a fundamental task for exploiting the advantages of massive Multiple-Input Multiple-Output (MIMO) systems in fifth generation (5G) wireless technology. Channel estimates require solving sparse linear inverse problems that is usually performed with the Least Squares method, which brings low complexity but high mean squared error values. READ MORE
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5. Link Adaptation in 5G Networks : Reinforcement Learning Framework based Approach
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Link Adaptation is a core feature introduced in gNodeB (gNB) for Adaptive Modulation and Coding (AMC) scheme in new generation cellular networks. The main purpose of this is to correct the estimated Signal-to-Interference-plus-Noise ratio (SINR) at gNB and select the appropriate Modulation and Coding Scheme (MCS) so the User Equipment (UE) can decode the data successfully. READ MORE