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Found 27 papers, 3 papers with code
A Massive MIMO Sampling Detection Strategy Based on Denoising Diffusion Model
The Langevin sampling method relies on an accurate score matching while the existing massive multiple-input multiple output (MIMO) Langevin detection involves an inevitable singular value decomposition (SVD) to calculate the posterior score.
Learning Wireless Data Knowledge Graph for Green Intelligent Communications: Methodology and Experiments
In this paper, we propose a solution, termed the pervasive multi-level (PML) native AI architecture, which integrates the concept of knowledge graph (KG) into the intelligent operational manipulations of mobile networks, resulting in the establishment of a wireless data KG.
Joint Active and Passive Beamforming for IRS-Aided Wireless Energy Transfer Network Exploiting One-Bit Feedback
To reap the active and passive beamforming gain in an intelligent reflecting surface (IRS)-aided wireless network, a typical way is to first acquire the channel state information (CSI) relying on the pilot signal, and then perform the joint beamforming design.
Random Aggregate Beamforming for Over-the-Air Federated Learning in Large-Scale Networks
Extensive simulation results are presented to demonstrate the effectiveness of the proposed random aggregate beamforming-based scheme as well as the refined method.
Wireless Network Digital Twin for 6G: Generative AI as A Key Enabler
Digital twin, which enables emulation, evaluation, and optimization of physical entities through synchronized digital replicas, has gained increasingly attention as a promising technology for intricate wireless networks.
Digital Twin-Enhanced Deep Reinforcement Learning for Resource Management in Networks Slicing
In this paper, a framework consisting of a digital twin and reinforcement learning agents is present to handle the issue.
AIR-DA: Adversarial Image Reconstruction for Unsupervised Domain Adaptive Object Detection
This results in an imbalance of the adversarial training between the domain discriminator and the feature extractor.
In-Situ Calibration of Antenna Arrays for Positioning With 5G Networks
Owing to the ubiquity of cellular communication signals, positioning with the fifth generation (5G) signal has emerged as a promising solution in global navigation satellite system-denied areas.
On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds
A series of white papers and survey papers have been published, which aim to define 6G in terms of requirements, application scenarios, key technologies, etc.
Deep Learning-Based Modeling of 5G Core Control Plane for 5G Network Digital Twin
However, the intricate structure and diverse functionalities of the existing 5G core network, especially the control plane, present challenges in constructing core network digital twins.
Fast Direct Localization for Millimeter Wave MIMO Systems via Deep ADMM Unfolding
Next, we develop a deep ADMM unfolding network (DAUN) to learn the ADMM parameter settings from the training data and a position refinement algorithm is proposed for DAUN.
Link-level simulator for 5G localization
Channel-state-information-based localization in 5G networks has been a promising way to obtain highly accurate positions compared to previous communication networks.
Representation Learning of Knowledge Graph for Wireless Communication Networks
Finally, the results show that the classification accuracy of the proposed model is better than the existing unsupervised graph neural network models, such as VGAE and ARVGE.
Unsupervised Recurrent Federated Learning for Edge Popularity Prediction in Privacy-Preserving Mobile Edge Computing Networks
In this article, we propose an unsupervised and privacy-preserving popularity prediction framework for MEC-enabled IIoT.
Real-time Dual-channel 2 * 2 MIMO Fiber-THz-Fiber Seamless Integration System at 385 GHz and 435 GHz
We demonstrate the first practical real-time dual-channel fiber-THz-fiber 2 * 2 MIMO seamless integration system with a record net data rate of 2 * 103. 125 Gb/s at 385 GHz and 435 GHz over two spans of 20 km SSMF and 3 m wireless link.
Efficient Joint DOA and TOA Estimation for Indoor Positioning with 5G Picocell Base Stations
Secondly, based on the deployment reality that 5G picocell gNBs only have a small-scale antenna array but have a large signal bandwidth, the proposed scheme decouples the estimation of time-of-arrival (TOA) and direction-of-arrival (DOA) to reduce the huge complexity induced by two-dimensional joint processing.
Joint DoA-Range Estimation Using Space-Frequency Virtual Difference Coarray
In this paper, we address the problem of joint direction-of-arrival (DoA) and range estimation using frequency diverse coprime array (FDCA).
Amplitude-Constrained Constellation and Reflection Pattern Designs for Directional Backscatter Communications Using Programmable Metasurface
For the constellation design, we adopt the amplitude and phase-shift keying (APSK) constellation and optimize the parameters of APSK such as ring number, ring radius, and inter-ring phase difference.
Distributed Reinforcement Learning for Privacy-Preserving Dynamic Edge Caching
In this paper, a privacy-preserving distributed deep deterministic policy gradient (P2D3PG) algorithm is proposed to maximize the cache hit rates of devices in the MEC networks.
Hybrid Policy Learning for Energy-Latency Tradeoff in MEC-Assisted VR Video Service
Virtual reality (VR) is promising to fundamentally transform a broad spectrum of industry sectors and the way humans interact with virtual content.
Rank Minimization-based Toeplitz Reconstruction for DoA Estimation Using Coprime Array
The atomic-norm representation of the measurements from the interpolated virtual array is considered, and the equivalent dual-variable rank minimization problem is formulated and solved using a cyclic optimization approach.
ECS-Net: Improving Weakly Supervised Semantic Segmentation by Using Connections Between Class Activation Maps
Image-level weakly supervised semantic segmentation is a challenging task.
True-data Testbed for 5G/B5G Intelligent Network
Future beyond fifth-generation (B5G) and sixth-generation (6G) mobile communications will shift from facilitating interpersonal communications to supporting Internet of Everything (IoE), where intelligent communications with full integration of big data and artificial intelligence (AI) will play an important role in improving network efficiency and providing high-quality service.
Achievable Rate Region of MISO Interference Channel Aided by Intelligent Reflecting Surface
This paper investigates the achievable rate region of the multiple-input single-output (MISO) interference channel aided by intelligent reflecting surfaces (IRSs).
BlendMask: Top-Down Meets Bottom-Up for Instance Segmentation
The proposed BlendMask can effectively predict dense per-pixel position-sensitive instance features with very few channels, and learn attention maps for each instance with merely one convolution layer, thus being fast in inference.
Ranked #13 on
Real-time Instance Segmentation
on MSCOCO
Attention Mechanism Enhanced Kernel Prediction Networks for Denoising of Burst Images
Deep learning based image denoising methods have been extensively investigated.
An Attention-Based Approach for Single Image Super Resolution
We propose an attention-based approach to give a discrimination between texture areas and smooth areas.
