ComputingNotes

Deep Reinforcement Learning Parameters

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Epsilon (ϵepsilon 𝜖): This is a hyperparameter (a value between 0 and 1) that defines the probability of an agent taking a random action (exploration) instead of the action believed to have the highest reward (exploitation). Epsilon Decay: This is the process of gradually reducing the value of 𝜖 over time or a number of ... Read More

All Machine Learning MOdels

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https://www.ibm.com/think/topics/machine-learning-types Machine learning models are grouped in one of 5 types, supervised, unsupervised, self-supervised, semi-supervised and reinforcement learning. Machine learning libraries, useful.

Pilots and Least Squares work

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BPSK (Binary Phase Shift Keying), a fundamental digital modulation scheme. A receiver uses a simple technique called Least Squares (LS) Channel Estimation to defeat fading and multipath interference. Wireless Channel In this simulation, the channel is designed to be intentionally difficult. It includes two major issues of digital signals: The Transmission Strategy: The Pilot Block ... Read More

pskmod, awgn, rayleigh – matlab

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Notes from – pskmod: Modulate signal using M-PSK method https://au.mathworks.com/help/comm/ref/pskmod.html The pskmod function performs M-ary Phase Shift Keying (M-PSK) modulation, converting input symbols (X) into a complex baseband signal (Y). Key Syntax data = randi([0 M-1], 1000, 1); txSig = pskmod(data, M, pi/M); Adding fading to simulation models a more complex and realistic wireless channel ... Read More

Channel Estimation

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The goal is to solve for H (the Channel) in the equation: Y=H⋅X+N (Received Signal = Channel × Transmitted Signal + Noise) [1]W. Shen, “Deep Learning-Enabled Channel Estimation for Reconfigurable Intelligent Surfaces-Aided Wireless Communications”. 1. Pilot Insertion (The “Known” Data) The receiver cannot estimate the channel using random user data because it doesn’t know what ... Read More

MNIST PCA

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https://medium.com/@azimkhan8018/a-beginners-guide-to-deep-learning-with-mnist-dataset-0894f7183344https://ranasinghiitkgp.medium.com/principal-component-analysis-pca-with-code-on-mnist-dataset-da7de0d07c22https://github.com/mkosaka1/MNIST_PCA_CNN/blob/main/PCA%20%2B%20CNN.ipynbhttps://gist.github.com/tommct/1490cdf856d745ba41c1ac99ada2b579

Channel Estimation

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https://au.mathworks.com/help/lte/ug/channel-estimation.html There are various factors that affect wireless signals. A phone may try to connect to a tower station, but multiple factors such as being in basement, being in moving train etc., the connection might be lost. This is due to the change in the channel of wireless communication system. Now the question is, can ... Read More

Reinforcement Learning

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https://au.mathworks.com/content/dam/mathworks/ebook/gated/reinforcement-learning-ebook-all-chapters.pdf Reinforcement Learning: Type of machine learning, where a computer agent learns to perform a task through a process of repeated trial and error within a dynamic environment. The goal is to learn what to do, how to map situations to take certain actions that minimize a numerical reward signal. Eg. RL trained computer gains ... Read More

Learning Joint Detection, Equalization and Decoding for Short-Packet Communications – Paper Notes

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S. Dörner, J. Clausius, S. Cammerer, and S. ten Brink, “Learning Joint Detection, Equalization and Decoding for Short-Packet Communications,” IEEE Transactions on Communications, vol. 71, no. 2, pp. 837–850, Feb. 2023, doi: 10.1109/TCOMM.2022.3228648. A machine learning-based approach for joint detection, synchronization, equalization, and decoding in short-packet wireless communications, where messages must first be detected before ... Read More
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