Research learning workspace
Picture-first notes on wireless, RIS, sensing and machine learning. Every note opens with a summary, many come with interactive labs that calculate as you drag, and each track ends in a quick self-check.
From frequency and bandwidth to arrays, beams and MIMO: the vocabulary every later note builds on.
1 · Wireless basics
Build the foundation of wireless communication: spectrum, carrier frequency, wavelength, bandwidth, channel capacity, and the difference between bandwidth and data rate.
2 · Wireless basics
Understand how a signal travels from transmitter to receiver, why power is lost, how a link budget is built, and where different tower and small-cell structures are used.
3 · Wireless basics
Interpret received power, signal quality, and CQI feedback in one physical scenario, and see why strong signal bars do not always mean high throughput.
4 · Wireless basics
Learn how antennas shape coverage, what gain and half-power beamwidth mean, why polarization alignment matters, and how cellular antenna systems have evolved.
5 · Wireless basics
Compare uniform linear and rectangular arrays, derive their steering behaviour, and connect array geometry to 2D/3D beam control and RIS design.
6 · Wireless basics
See how controlled phase differences make signals add or cancel, derive the steering phase for an array, and connect phase quantization to practical beamforming.
7 · Wireless basics
Identify electromagnetic field regions, calculate commonly used boundaries, and understand how distance changes coupling, wavefront shape, beam response, and channel modelling.
8 · Wireless basics
Build phased-array intuition from two- and three-element examples, derive distance and phase compensation, compare architectures, and connect active arrays with RIS beam control.
9 · Wireless basics
Connect array phase profiles to electronic steering, beam-search codebooks, sidelobes, calibration, and practical scanning strategies in 5G, 6G, radar, and RIS systems.
10 · Wireless basics
Learn how multiple antennas create diversity, spatial multiplexing, and beamforming gains—and how massive MIMO serves many users on the same time-frequency resource.
11 · Wireless basics
Learn how wideband complex measurements are transformed into delay, how a time gate isolates selected propagation paths, and how the method is used in RIS-assisted channel measurements.
How antennas turn current into coverage, what the channel does to the wave, and how to measure both.
1 · Antennas & propagation
Start with wavelength, matching, radiation pattern, gain, efficiency, and polarization; learn what each quantity tells you before evaluating an antenna.
2 · Antennas & propagation
Read path loss, shadowing, reflection, delay spread, and Doppler as physical effects rather than disconnected channel-model parameters.
3 · Antennas & propagation
A practical measurement checklist: which antenna and channel parameters to record, what they mean, and when to use each one.
Sampling, OFDM, receiver metrics, duplexing, traffic and scheduling: what happens once the wave is captured.
1 · Signal processing
Learn what a receiver actually samples, why I/Q is useful, and how time- and frequency-domain views guide wireless signal processing.
2 · Signal processing
Compare narrowband and wideband links, then see how subcarriers, pilots, and receiver processing recover data.
3 · Signal processing
Read PSK and QAM constellations, compare uncoded R=1 BER curves, and choose receiver, rate, spectrum, energy, fairness and latency metrics.
4 · Signal processing
Understand how FDD and TDD separate uplink from downlink, where each is useful, and how modern networks combine both modes across carriers and coverage layers.
5 · Signal processing
Follow traffic from an application through QoS classification and radio scheduling, then compare current traffic patterns with the six IMT-2030 usage scenarios expected to shape 6G.
6 · Signal processing
See how a base-station scheduler uses queues, QoS, channel quality and duplex constraints to allocate slots, frequency resources, beams and retransmissions across competing users.
Learn through calculated experiments: classification, regression, optimization, neural networks, reinforcement and transfer learning.
1 · Machine learning
A clearer introduction to machine learning, the basic vocabulary, and how classification problems are framed.
2 · Machine learning
A practical guide to the main ways machines learn from labeled, unlabeled, and partly labeled data.
3 · Machine learning
A beginner-friendly guide to common machine learning, deep learning, DNN, and DRL parameters such as seed, batch size, epoch, bias, overfitting, underfitting, learning rate, and exploration.
4 · Machine learning
A deeper but beginner-friendly explanation of gradient descent, learning rate, optimization variants, and common training problems.
5 · Machine learning
A deeper guide to common classification algorithms, their intuition, strengths, weaknesses, and practical use cases.
6 · Machine learning
A deeper explanation of regression models for predicting continuous values, with intuition, assumptions, and practical guidance.
7 · Machine learning
A beginner-friendly explanation of Ridge Regression and Kernel Ridge Regression from first principles, with intuition, equations, kernels, and Python examples.
8 · Machine learning
A practical comparison of classifiers and regressors, including output type, metrics, computational efficiency, and model-selection guidance.
9 · Machine learning
A clearer and deeper guide to neural networks, CNNs, RNNs, transformers, training, and practical limitations.
10 · Machine learning
A clearer and deeper guide to reinforcement learning, value functions, policies, exploration, Q-learning, and deep RL.
11 · Machine learning
A practical guide to transfer learning, frozen layers, fine-tuning, applications, benefits, and limitations.
Programmable surfaces that reshape the radio channel: physics, hardware, coverage, localisation and 6G deployment.
1 · RIS
A detailed beginner-friendly explanation of RIS, smart radio environments, and why RIS is important for 6G wireless networks.
2 · RIS
A deeper explanation of RIS physics, architectures, design variables, advantages, and practical limitations.
3 · RIS
A structured view of RIS applications in coverage, interference control, security, IoT, sensing, and smart indoor environments.
4 · RIS
How RIS helps localization through virtual anchors, controllable paths, near-field wavefronts, and channel-parameter estimation.
5 · RIS
Why mmWave and RIS are naturally connected for high-resolution positioning, beam training, and near-field localization.
6 · RIS
A 6G-oriented view of RIS in mmWave/sub-THz networks, including deployment, AI control, digital twins, and open research directions.
One waveform that both carries data and senses the world: principles, trade-offs, tracking and 6G use cases.
1 · ISAC
A detailed introduction to ISAC, why it matters for 6G, and how a radio signal can both communicate and sense.
2 · ISAC
How a radio measures range, speed and direction from an echo, why echoes are so much weaker than communication signals, and how a receiver decides that a target is really there.
3 · ISAC
Step by step: how a base station removes its own data from the echo and reads range and speed from an ordinary OFDM signal with two FFTs.
4 · ISAC
The signal-processing principles behind ISAC, including waveform design, sensing metrics, communication metrics, and unavoidable trade-offs.
5 · ISAC
Major ISAC use cases in autonomous mobility, smart factories, healthcare, drones, localization, and network intelligence.
6 · ISAC
How ISAC supports device-based and device-free localization, tracking, Doppler estimation, and predictive beamforming.
7 · ISAC
Why mmWave and THz frequencies are central to high-resolution ISAC, and what challenges they introduce.
8 · ISAC
How ISAC fits into 6G networks with AI, RIS, digital twins, edge computing, and sensing-as-a-service.
Where the two meet: how a surface helps one system communicate and sense at the same time.
1 · RIS-assisted ISAC
Follow a waveform from data transmission to a controlled reflection and a target echo, then recover the correct path distance.
2 · RIS-assisted ISAC
Derive a reciprocal aperture budget, separate one-way signal gain from echo gain, and test distance and panel-size penalties.
3 · RIS-assisted ISAC
Connect user rate, reciprocal echo strength and a fixed-aperture partition baseline before attempting joint optimization.
4 · RIS-assisted ISAC
Explore when a virtual anchor improves position information and how quantized spherical-wave phases focus energy on a chosen point.
5 · RIS-assisted ISAC
Compare active, STAR and hybrid surfaces using noise and energy budgets, then ask what measurements support a research claim.
6 · RIS-assisted ISAC
Calculate how scanning consumes a frame and lets a target move, then build a fair evaluation plan for a practical RIS-assisted ISAC system.