SongKunL's starred repositories
DL-channel-estimation-MaMIMO
This repository contains the code needed to reproduce results in the paper by M. Belgiovine, et al. “Deep Learning at the Edge for Channel Estimation in Beyond-5G Massive MIMO,” accepted at IEEE Wireless Communications Magazine (WCM), April 2021.
5Gdataset
In this work, we present a 5G trace dataset collected from a major Irish mobile operator. The dataset is generated from two mobility patterns (static and car), and across two application patterns(video streaming and file download). The dataset is composed of client-side cellular key performance indicators (KPIs) comprised of channel-related metrics, context-related metrics, cell-related metrics and throughput information. These metrics are generated from a well-known non-rooted Android network monitoring application, G-NetTrack Pro. To the best of our knowledge, this is the first publicly available dataset that contains throughput, channel and context information for 5G networks. To supplement our real-time 5G production network dataset, we also provide a 5G large scale multi-cell ns-3 simulation framework. The availability of the 5G/mmwave module for the ns-3 mmwave network simulator provides an opportunity to improve our understanding of the dynamic reasoning for adaptive clients in 5G multi-cell wireless scenarios. The purpose of our framework is to provide additional information (such as competing metrics for users connected to the same cell), thus providing otherwise unavailable information about the basestation (eNodeB or eNB) environment and scheduling principle, to end user. Our framework permits other researchers to investigate this interaction through the generation of their own synthetic datasets.
Radio_Localization
Channel modeling, performance analysis, localization and optimization algorithm for 5G/6G (mmWave/THz) localization and sensing
Capacity-Estimation-on-the-Mathworks-5G-NR-CDL-Model
Single-link channel capacity estimation on the microwave and millimetre wave frequencies by using the Mathworks 5G NR CDL model for NLOS.
Zotero-engines
Zotero的内置检索引擎配置json文件，扩展可选检索源，定期更新
New-Methodology-for-Multipath-Parameter-Estimation
Multipath Profiles Extraction, Signal Parameter Estimation Strategies
dsatools
Digital signal analysis library for python. The library includes such methods of the signal analysis, signal processing and signal parameter estimation as ARMA-based techniques; subspace-based techniques; matrix-pencil-based methods; singular-spectrum analysis (SSA); dynamic-mode decomposition (DMD); empirical mode decomposition; variational mode decomposition (EMD); empirical wavelet transform (EWT); Hilbert vibration decomposition (HVD) and many others.
StatisticalSignalProcessing
Matlab code implementing different methods used in statistical signal processing; mainly Extended Kalman Filters, LMS/RLS, Wiener, robust regression, MMSE estimators, ML estimators, Hi-Frequency estimators (Pisarenko, MUSIC, ESPRIT)
Sound_Localization_Algorithms
Classical algorithms of sound source localization with beamforming, TDOA and high-resolution spectral estimation.
MedComNet2024_5G_pos_meas
This repository contains datasets of 5G positioning measurements simulated in a realistic environment using a Matlab raytracer tool.
5GPositioning
This is a demonstration of 5G mmWave positioning
NLOSPosSynInit
A simple routine for intializing 5G positioning and synchronization from only NLOS paths
The-JUAD-resource-allocation-for-D2D-in-a-FDD-cellular-network
WCSP：（1）Joint Uplink and Downlink Resource Allocation for D2D Communications Underlying Cellular Networks
Supervised-Deep-Learning-for-Radio-Resource-Allocation
A supervised deep learning based resource allocation scheme for multi-cell wireless system.
NOMA_with_reinformcement
Optimizing resource allocation with deep reinforcement learning
resource-allocation-opt
Solving Resource Allocation problems with Mixed-Integer Linear Programming in Python
M.S.-Thesis
CNN-Based Resource Allocation for Energy-Efficient D2D Communications
Globecom2020-ResourceAllocationGNN
Code for Globecom2020 paper: Resource Allocation based on Graph Neural Networks in Vehicular Communications
ml-for-resource-allocation
Machine Learning for Dynamic Resource Allocation in Network Function Virtualization
Resource-Allocation-using-deeprl
Deep Reinforcement Learning Based Dynamic Resource Allocation in 5G Ultra-Dense Networks
power_bandwidth_allocation_optimization
A Genetic Algorithm for Joint Power and Bandwidth Allocation in Multibeam Satellite Systems
Power-allocation-for-multi-user-OFDM-DCSK-system-in-frequency-selective-fading-channel
This project is related to the paper: "Power allocation for multi-user OFDM-DCSK system in frequency selective fading channel", Majid Mobini, M.Reza Zahabi, Physical Communication, 24, (2017), pp. 146–153. In this paper, we introduce a grouping approach for power allocation in the multi-user OFDM-DCSK (MU-OFDM-DCSK) system under the frequency selective fading channels. The suggested procedure is convenient also for the other comb-type non-coherent schemes with similar structure. Furthermore, we derive analytical bit error rate (BER) expression for the grouped scheme and offer an optimal power distribution policy for both the single- and multi-user scenarios. This power assignment strategy is formulated by a min–max problem with the target of the worst group BER minimization incorporating total power and interference constraints. Simulation results confirm the advantages of the proposed power allocation scheme.
wireless-simulator-ua-pc
Wireless Cellular Simulator for Radio Resource Management
ResourceAllocationReinforcementLearning
intial version
Resources-Allocation-in-The-Edge-Computing-Environment-Using-Reinforcement-Learning
Simulated the scenario between edge servers and users with a clear graphic interface. Also, implemented the continuous control with Deep Deterministic Policy Gradient (DDPG) to determine the resources allocation (offload targets, computational resources, migration bandwidth) in the edge servers