Skip to main content

Wireless Communication Based Projects for M.Tech


Our colleges either assign us projects individually during M.Tech or Ph.D coursework. When working on a project, you should be able to apply theoretical concepts to real-world situations. By applying your theoretical knowledge to a project, you will gain a better understanding of a subject and face new challenges at work. And the primary goal of a researcher, engineer, or scientist is to solve problems or difficulties. On the other hand, project excellence can attract companies or investors.

We'll discuss various project/thesis ideas based on contemporary wireless communication. It will benefit both professors and students.


M.Tech Project/Dissertation ideas:

1. Investigating of different beamforming strategies in millimeter wave band

[1.1 Beamforming, Analog, Digital, and Hybrid Beamforming, ]
[1.2 Millimeter Wave ]

2. Signal processing in Massive MIMO
[2.1 SVD based MIMO transmission, ]
[2.2 Optimal power allocation in MIMO ]

3. Channel modelling for extremely high frequency bands such as UWB or millimeter wave bands
[3.1 Channel model for UWB and mm wave ]

4. Saleh Valenzuala Channel Model
[4.1 Time-delayed saleh valenzuala cluster model for UWB & mm-Wave ]

6. Millimeter wave (mm wave) imaging

7. Modulation Techniques for 5G communication (OFDM & NOMA)
[7.1 OFDM for 4G & 5G ]

8. Device to Device Communication (D2D)

9. Industrial M2M Communication using UWB or millimeter wave band

10. Precoding at downlink OFDM

11. FBMC

12. Detection of AOA & AOD in UWB

13. Possible solutions to overcome limitations of under-water wireless communication

14. UAV (unmanned aerial vehicle)

15. Fog Computing for IoTs

16. Wi-Max (60 GHz)

17. Ad hoc networks

18. Li Fi

19. Traffic management using IoTs

20. Fleet management using IoTs

21. Communication at the network layer (in OSI)

22. LED and modem-based E-Notice board

23. Classification of images using deep learning

(For that project artificial neural network Alex-net may be helpful. Similarly, image-net may also be helpful as well for your work ... The basic difference between machine learning and deep learning is - machine learning only can identify an image from a pre-loaded image database while deep learning can learn from dataset and can make its own decision.)
24. Ionospheric scintillation prediction using sophisticated machine learning algorithm
Click here for more details.


(Python / MATLAB for development of machine learning algorithm , gps signal, etc.)


Also read about
[1] Analog and Digital Communication Mini Projects

<<Previous Page
Next Page>>
#beamforming
📊 MATLAB & ONLINE SIMULATIONS (Web-Based)
🎓 GATE & UGC - NET SOLUTIONS
📡 WIRELESS & SIGNAL PROCESSING


Contact Us

Name

Email *

Message *

Popular Posts

Hybrid Beamforming | Page 1

Beamforming Techniques Hybrid Beamforming... Page 1 | Page 2 | Hybrid Beamforming: Hybrid beam formation was developed to address some of the limitations of digital pre-coding approaches. Every antenna element is connected to an RF chain in digital pre-coding (beam forming) method. We also know that each RF chain is in charge of providing a separate data stream between the transmitter and the receiver. We know that a larger number of independent data streams leads to higher data rates. It has a spatial multiplexing feature for MIMO. As a result, we may assume that switching from MIMO to massive MIMO will benefit us more in terms of spatial multiplexing in massive MIMO, where each antenna is coupled to a single RF chain. We'll proceed with a definition of hybrid beam forming. Overview of hybrid beam forming with example: Unlike digital beam forming, more than one antenna element is connected to a single RF chain in hybr...
Read more

UGC NET Electronic Science Previous Year Question Papers with Solutions

Home / Engineering & Other Exams / UGC NET 2026 PYQ ⬇️ Download Papers and Solutions 📋 Exam Pattern 💡 Preparation Tips ❓ FAQs 📊 Exam Highlights: Electronic Science (88) Feature Details Junior Research Fellowship (JRF) ₹37,000 + HRA per month Eligibility M.Sc/M.Tech in Electronics (55%) Validity of Certificate JRF (3 Years) | Lectureship (Lifetime) 📥 Download UGC NET Electronics PDFs Complete collection of previous year question papers, answer keys and explanations for Subject Code 88. Start Downloading 📂 View All Question Papers June 2025 - Question Paper Download PDF June 2025 - Solved Paper + Explanation ...
Read more

MATLAB Code for Rms Delay Spread

RMS delay spread is crucial when you need to know how much the signal is dispersed in time due to multipath propagation, the spread (variance) around the average. In high-data-rate systems like LTE, 5G, or Wi-Fi, even small time dispersions can cause ISI. RMS delay spread is directly related to the amount of ISI in such systems. RMS Delay Spread [↗] Delay Spread Calculator Enter delays (ns) separated by commas: Enter powers (dB) separated by commas: Calculate   The above calculator Converts Power to Linear Scale: It correctly converts the power values from decibels (dB) to a linear scale. Calculates Mean Delay: It accurately computes the mean excess delay, which is the first moment of the power delay profile. Calculates RMS Delay Spread: It correctly calculates the RMS delay spread, defined as the square root of the second central moment of the power delay profile.   MATLAB Code  clc...
Read more

Comparisons among ASK, PSK, and FSK (with MATLAB + Simulator)

Modulation ASK, FSK & PSK Constellation MATLAB Simulink MATLAB Code Comparisons among ASK, PSK, and FSK 📘 Comparisons among ASK, FSK, and PSK 🧮 Online Simulator Bandwidth 🧮 MATLAB Code BER Analysis 📚 Further Reading 📂 View Other Topics on Comparisons among ASK, PSK, and FSK ... 🧮 Comparisons of Noise Sensitivity, Bandwidth, Complexity, etc. 🧮 MATLAB Code for Constellation Diagrams of ASK, FSK, and PSK 🧮 Online Simulator for ASK, FSK, and PSK Generation 🧮 Online Simulator for ASK, FSK, and PSK Constellation 🧮 Some Questions and Answers Comparisons among ASK, PSK, and FSK Comparison among ASK, FSK, and PSK Parameters ASK FSK PSK Variable Characteristics Amplitude ...
Read more

How Windowing Affects Your Periodogram

The windowed periodogram is a widely used technique for estimating the Power Spectral Density (PSD) of a signal. It enhances the classical periodogram by mitigating spectral leakage through the application of a windowing function. This technique is essential in signal processing for accurate frequency-domain analysis.   Power Spectral Density (PSD) The PSD characterizes how the power of a signal is distributed across different frequency components. For a discrete-time signal, the PSD is defined as the Fourier Transform of the signal’s autocorrelation function: S x (f) = FT{R x (Ï„)} Here, R x (Ï„)}is the autocorrelation function. FT : Fourier Transform   Classical Periodogram The periodogram is a non-parametric PSD estimation method based on the Discrete Fourier Transform (DFT): P x (f) = \(\frac{1}{N}\) X(f) 2 Here: X(f): DFT of the signal x(n) N: Signal length However, the classical periodogram suffers from spectral leakage due to abrupt truncation of the ...
Read more

What is - 3dB Frequency Response? And applications

📘 Overview & Theory 📘 Application of -3dB Frequency Response 🧮 MATLAB Codes 🧮 Online Digital Filter Simulator 📚 Further Reading Filters What is -3dB Frequency Response?   Remember, for most passband filters, the magnitude response typically remains close to the peak value within the passband, varying by no more than 3 dB. This is a standard characteristic in filter design. The term '-3dB frequency response' indicates that power has decreased to 50% of its maximum or that signal voltage has reduced to 0.707 of its peak value. Specifically, The -3dB comes from either 10 Log (0.5) {in the case of power} or 20 Log (0.707) {in the case of amplitude} . Viewing the signal in the frequency domain is helpful. In electronic amplifiers, the -3 dB limit is commonly used to define the passband. It shows whether the signal remains approximately flat across the passband. For example, in pulse shapi...
Read more

Phase Shift Keying (PSK) Modulation & Demodulation (with Simulation)

Phase Shift Keying (PSK) Theoretical Framework: Phase Shift Keying (PSK) is a digital modulation paradigm where information is encoded by modulating the instantaneous phase of a continuous-wave carrier. In Binary PSK (BPSK), the most fundamental implementation, the bitstream is mapped onto two discrete phases separated by $\pi$ radians—typically representing binary '1' and '0'—resulting in an antipodal signaling scheme where each state change induces a phase reversal in the carrier. BPSK Transmitter Synthesis: The analytic representation of a BPSK signal $s(t)$ is defined as: \[ s(t) = \begin{cases} A_c \cos(2\pi f_c t), & \text{for symbol } m_1 \\ A_c \cos(2\pi f_c t + \pi) = -A_c \cos(2\pi f_c t), & \text{for symbol } m_0 \end{cases} \] NRZ-L m(t) × ...
Read more