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uav-communication

5G and UAV Communication

uav-ddpg

Code for paper "Computation Offloading Optimization for UAV-assisted Mobile Edge Computing: A Deep Deterministic Policy Gradient Approach"

uav-in-cognitive-radio-network

uav-navigation-learning

uav-noise-suppression

An UAV Wireless Communication Noise Suppression Method Based on OFDM Modulation and Demodulation

uav-noma-adm

uav-pos-2d

Optimal position in 2D for UAV as a communication relay

uav-ris-drl

3D-Trajectory Design and Phase-Shift for RIS-Assisted UAV Communication using Deep Reinforcement Learning

uav-ris_eh_ddpg

uav-ris_energyharvesting

uav-trajectory-planning

The first unofficial implementation of a paper with the title of "UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices" (IEEE Transactions on Wireless Communications 2019)

uav3dbeamforming

secure transmission for UAV communication systems based on deep learning

uav_clustering_minpower

uav_communication

UAV Aerial Drone Communication Simulation

uav_data_harvesting

Python implementation of DDQN multi-UAV data harvesting

uav_gbs_joint_optimization

Trajectory design and bandwidth assignment for UAV_GBS intergated network

uav_integrated_navigation

多旋翼无人机组合导航系统-多源信息融合算法

uav_relay_dqn

论文UAV relay in VANETs against smart jamming with reinforcement learning DQN版本

uav_relay_simulation

UAV relay in VANETs against smart jamming with reinforcement learning论文仿真

uav_rl_maximize_throughput

UAV-based MEC to maximize user throughput via reinforcement learning

uav_swarm_reinforcement_learning

ud501

The Python scripts for Udacity Machine Learning for Trading. By Georgia Tech as CS 7646

udke

Official implementation of Unfolded Deep Kernel Estimation for Blind Image Super-resolution.

udl

PyTorch code for NeurIPS2021 paper "Uncertainty-Driven Loss for Single Image Super-Resolution"

ul2dl

uma_random_user_activity

Matlab codes for Unsourced Multiple Access With Random User Activity by K.-H. Ngo, A. Lancho, G. Durisi, and A. Graell i Amat

umdpsn

Implementation for DPSN in Applied Soft Computing

un-based-risbf

underwater-acoustic-target-classification-based-on-dense-convolutional-neural-network

In oceanic remote sensing operations, underwater acoustic target recognition is always a difficult and extremely important task of sonar systems, especially in the condition of complex sound wave propagation characteristics. Expensively learning recognition model for big data analysis is typically an obstacle for most traditional machine learning (ML) algorithms, whereas convolutional neural network (CNN), a type of deep neural network, can automatically extract features for accurate classification. In this study, we propose an approach using a dense CNN model for underwater target recognition. The network architecture is designed to cleverly re-use all former feature maps to optimize classification rate under various impaired conditions while satisfying low computational cost. In addition, instead of using time-frequency spectrogram images, the proposed scheme allows directly utilizing original audio signal in time domain as the network input data. Based on the experimental results evaluated on the real-world dataset of passive sonar, our classification model achieves the overall accuracy of 98.85$\%$ at 0 dB signal-to-noise ratio (SNR) and outperforms traditional ML techniques, as well as other state-of-the-art CNN models.

unequally-sub-connected-architecture-for-hybrid-beamforming-in-massive-mimo-systems