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aamirmahmood's Projects

aloha-course icon aloha-course

This is the code related to the lab exercise in Python about MAC competitive protocols (ALOHA, CSMA).

channel-prediction-meta-learning icon channel-prediction-meta-learning

Code for the paper "Predicting Multi-Antenna Frequency-Selective Channels via Meta-Learned Linear Filters based on Long-Short Term Channel Decomposition"

codd icon codd

Cooperative Driving Dataset: a dataset for multi-agent driving scenarios

crnoma_ddpg icon crnoma_ddpg

A DDPG based reinforcement learning algorithm for cognitive radio inspired non-orthogonal multiple access (CR-NOMA) systems

dl_ofdm icon dl_ofdm

Deep-Waveform: A Learned OFDM Receiver Based on Deep Complex-valued Convolutional Networks

fb_quadriga icon fb_quadriga

Code repository for working on Quadriga simulations

goodbye-aloha icon goodbye-aloha

Implementing a Distributed Queuing protocol as an alterenative to the ALOHA MAC Protocol.

irsa_python icon irsa_python

Implementation of Irregular Repetition Slotted ALOHA protocol.

kalman-and-bayesian-filters-in-python icon kalman-and-bayesian-filters-in-python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

loraphy icon loraphy

Complete LoRa physical layer (LoRa PHY) implementation in MATLAB.

markov icon markov

Materials for book: "Markov Chains for programmers"

mimobook icon mimobook

Simulation code and accompanying material for the textbook "Introduction to Multiple Antenna Communications and Reconfigurable Surfaces" by Emil Björnson and Özlem Tuğfe Demir, Boston-Delft: now publishers, 2024

modsim2021 icon modsim2021

Simulation of the ALOHA protocol. Project made for Simulations and Models 2021

opennfm icon opennfm

Automatically exported from code.google.com/p/opennfm

radar-aided-beam-prediction icon radar-aided-beam-prediction

The evaluation code for the paper "Radar Aided 6G Beam Prediction: Deep Learning Algorithms and Real-World Demonstration".

reference-pe-and-measurements-db-for-wifi-time-based-scalable-location icon reference-pe-and-measurements-db-for-wifi-time-based-scalable-location

The repository includes a reference Matlab code for a mobile WiFi client receiver, Kalman-Filter-based positioning engine (PE) and a database of time-delay measurements of an indoor environment. The database includes both real-measured data, and simulated time-delay data, as well as ground-truth client position information, which can be used for validation and performance analysis. The PE code is designed to process the database data format and produce estimates of the mobile WiFi receiver position within the indoor venue. The database may be used for the development, validation and performance analysis of additional positioning engines. This kind of WiFi client PE enables an unlimited number of clients to estimate the position and navigate within the Wi-Fi network coverage area. Hence, it enables so-called "Wi-Fi Scalable Location". A *.pdf whitepaper is included in the repository and explains the functionality and usage of the code and database.

speccy icon speccy

Visualization tool for ath spectral scan

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