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Found 17 papers, 9 papers with code
Modem Optimization of High-Mobility Scenarios: A Deep-Learning-Inspired Approach
The next generation wireless communication networks are required to support high-mobility scenarios, such as reliable data transmission for high-speed railways.
Enhancing Automatic Modulation Recognition through Robust Global Feature Extraction
Modulated signals exhibit long temporal dependencies, and extracting global features is crucial in identifying modulation schemes.
A Low-Overhead Incorporation-Extrapolation based Few-Shot CSI Feedback Framework for Massive MIMO Systems
Accurate channel state information (CSI) is essential for downlink precoding at the base station (BS), especially for frequency FDD wideband massive MIMO systems with OFDM.
Demo: Reconfigurable Distributed Antennas and Reflecting Surface (RDARS)-aided Integrated Sensing and Communication System
Integrated sensing and communication (ISAC) system has been envisioned as a promising technology to be applied in future applications requiring both communication and high-accuracy sensing.
Data Augmentation of Bridging the Delay Gap for DL-based Massive MIMO CSI Feedback
In massive multiple-input multiple-output (MIMO) systems under the frequency division duplexing (FDD) mode, the user equipment (UE) needs to feed channel state information (CSI) back to the base station (BS).
Deep Learning for Hybrid Beamforming with Finite Feedback in GSM Aided mmWave MIMO Systems
Hybrid beamforming is widely recognized as an important technique for millimeter wave (mmWave) multiple input multiple output (MIMO) systems.
Towards Efficient Subarray Hybrid Beamforming: Attention Network-based Practical Feedback in FDD Massive MU-MIMO Systems
Channel state information (CSI) feedback is necessary for the frequency division duplexing (FDD) multiple input multiple output (MIMO) systems due to the channel non-reciprocity.
Quantization Adaptor for Bit-Level Deep Learning-Based Massive MIMO CSI Feedback
In this paper, we propose an adaptor-assisted quantization strategy for bit-level DL-based CSI feedback.
Better Lightweight Network for Free: Codeword Mimic Learning for Massive MIMO CSI feedback
In this paper, a cost free distillation technique named codeword mimic (CM) is proposed to train better feedback networks with the practical lightweight encoder.
On the Generative Utility of Cyclic Conditionals
This is motivated by the observation that deep generative models, in addition to a likelihood model $p(x|z)$, often also use an inference model $q(z|x)$ for extracting representation, but they rely on a usually uninformative prior distribution $p(z)$ to define a joint distribution, which may render problems like posterior collapse and manifold mismatch.
Binarized Aggregated Network with Quantization: Flexible Deep Learning Deployment for CSI Feedback in Massive MIMO System
Massive multiple-input multiple-output (MIMO) is one of the key techniques to achieve better spectrum and energy efficiency in 5G system.
Aggregated Network for Massive MIMO CSI Feedback
In frequency division duplexing (FDD) mode, it is necessary to send the channel state information (CSI) from user equipment to base station.
Binary Neural Network Aided CSI Feedback in Massive MIMO System
In massive multiple-input multiple-output (MIMO) system, channel state information (CSI) is essential for the base station to achieve high performance gain.
Cache Updating Strategy Minimizing the Age of Information with Time-Varying Files' Popularities
Inspired by this solution for the relaxed problem, we propose a practical cache updating strategy that meets all the constraints of the original problem.
Information Theory Information Theory
Multi-resolution CSI Feedback with deep learning in Massive MIMO System
In massive multiple-input multiple-output (MIMO) system, user equipment (UE) needs to send downlink channel state information (CSI) back to base station (BS).
Joint Transceiver Optimization for Wireless Communication PHY with Convolutional Neural Network
The simulation results show that the performance of neural network based system is superior to traditional modulation and equalization methods in terms of time complexity and bit error rate (BER) under fading channels.
Stock assessment for the western winter-spring cohort of neon flying squid (Ommastrephes bartramii) using environmentally dependent surplus production models
Because this squid has a short lifespan and is an ecological opportunist, the dynamics of its stock is greatly influenced by the environmental conditions, which need to be considered in its assessment and management.
