Deep Learning for Wireless Communications

The 4-step AI workflow designed to solve complex parameter challenges in modern networks like 5G and Wi-Fi, bypassing the need for manual algorithms. 1 2 3 4 Data Preparation & Synthesis AI models require massive amounts of data. To overcome real-world data shortages, engineers synthesize millions of compliant waveforms using MATLAB apps, or capture live ... Read More

Data Packet

What is a Data Packet? In wireless communications, large files (like an image or a video stream) are never sent as one continuous block. Instead, they are chopped up into thousands of tiny, manageable chunks called Data Packets. Think of a packet as a digital envelope moving through the postal system. Anatomy of a Packet ... Read More

Different types of modulation

In wireless communication, modulation is the process of encoding information into a carrier wave by varying one or more of its properties. The various types of modulation can be categorized into analog, digital, and spread spectrum modulation. Analog Digital Spread Spectrum Types of Modulations 1. Analog Modulation While mostly replaced by digital systems in modern ... Read More

What are electromagnetic waves?

Further, electromagnetic waves are different from mechanical wave which need medium to travel. What is an Electromagnetic Wave? Most waves we encounter like sound or water ripples are mechanical. They need matter (a “medium”) to travel, bumping molecules together like falling dominoes. But Electromagnetic (EM) waves are different. They don’t need a medium at all, ... Read More

How Data or Information travel wirelessly?

Wireless communication relies on invisible electromagnetic waves that carry information through the air by altering their size or speed. By precisely manipulating these wave properties, using techniques like Amplitude Modulation (AM), Frequency Modulation (FM), and digital Frequency Shift Keying (FSK), devices can seamlessly transmit everything from analog radio broadcasts to high-speed Wi-Fi data. How Wireless ... Read More

Quantum Perceptron

To understand Variational Quantum Circuits, we can have analogy with Classical Neural Networks. NN vs. QNN Classical Perceptrons (Left) vs. Quantum Gates (Right) Mapping to Hilbert Space R U Classical NN Quantum QNN Classical: Data flows through fixed layers of neurons. Quantum: Data is encoded into qubits and transformed via Rotational Gates. Non-Linearity: In QNNs, ... Read More

Asymptotic Lower Bound – Omega

Resources: What is Asymptotic Lower Bound? In the world of algorithm analysis, Asymptotic Lower Bound, denoted by the Greek letter Omega ($\omega$), is used to describe the “best-case” or the minimum rate of growth for a function as the input size n approaches infinity. Think of it as a guarantee. If an algorithm has a ... Read More

Big Oh Expressions Reference

Big-O Time Complexity O(1) Constant time — stays the same regardless of input size. O(log n) Logarithmic — grows very slowly (e.g., binary search). O((log n)2) Log-squared — slightly faster growth than log n. O(√n) Square root — moderate growth, better than linear. O(n) Linear — grows directly with input size. O(n log n) Efficient ... Read More

2025 ACM A.M. Turing Award Honors Quantum Pioneers

2025 ACM A.M. Turing Award Honors Quantum Pioneers Recipients: Charles H. Bennett & Gilles Brassard ACM has named Charles H. Bennett (IBM Research) and Gilles Brassard (Université de Montréal) as the recipients of the 2025 A.M. Turing Award. Often called the “Nobel Prize of Computing,” the award includes a $1 million prize for their foundational ... Read More
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