Skip to main content

Best Wireless Communication Based Projects for Final Year Students



Our colleges either give us projects individually or require us to work in groups to complete them. You want to be able to apply theoretical concepts to real-world situations when working on a project. You will gain a greater understanding of a subject by applying your theoretical knowledge to a project, and you will face new challenges at work. And a researcher, engineer, or scientist's primary goal is to solve issues or difficulties in order to provide us with a better tomorrow. Excellence in a project, on the other side, can attract companies or investors. This will help you advance in your career.

We'll talk about various project/thesis ideas based on modern wireless communication. Both professors and students will benefit from it. Wireless communication is now being used in our everyday lives. Without a doubt, no other application in our lives is as dominant as electronics/wireless appliances.

Without further ado, we'll go through several project ideas that can be beneficial to B.E, B.Tech, or M.Tech students.


1. Comparison of ASK, FSK & PSK

(We know all modulation schemes are derived from these three primary modulation schemes i.e., ASK, FSK, & PSK) because in modulation we vary the amplitude, frequency or phase of carrier signal in accordance with amplitude of message signal. For example, QAM modulation scheme a combination of ASK & PSK)

Resources:

[1.1] ASK FSK PSK with simulation in MATLAB

[1.2] M-ary Modulation | QPSK & QAM | Constellation



2. M-ary Modulation (QPSK & QAM)

(M-ary modulation scheme is very important to increase the data rate of a system. Because here we send multiple bits as a symbol at a time unlike ASK, FSK & PSK. If we use 4 QPSK then we are able to send 4 bits at a time or data rate increases by four times rather than transferring one bit at a time)

[2.1] M-ary Modulation Techniques



3. Comparison of m-ary QPSK & QAM (especially when we increasing the number of bits in a symbol)

[3.1] BER vs SNR for QAM, QPSK ...

[3.2] MATLAB code for BER vs SNR for M-QAM & M-PSK



4. Terrestrial microwave communication

[4.1] Microwave Link Communication for Long-distance



5. Multi carrier modulation - OFDM
6. OFDM SC at uplink
7. UWB
8. Device ranging in UWB
9. UWB in WiFi 4 and above
10. Millimeter wave communication
11. 60 GHz Communication (57 - 64 GHz)
12. Short range high speed wireless communication
13. FHSS
15. Blutooth communication
16. Zigbee communication
17. Under-water wireless communication
18. SDM in MIMO
19. Spatial Multiplexing (SM) in MIMO
20. IPv6
21. Internet of things (IoTs)
22. Night Vision
23. Cybersecurity (using cryptography)
24. Technology: 4G vs. 5G
25. Fading in wireless communication channel
26. RFID
27. V2V communication
28. Smart city
29. IEEE 802.11
30. Software defined radio (SDR)
31. Laser based wireless communication




Also Read
[1] More Wireless Communication Based Projects for M.Tech


<<Previous Page
Next Page>>

# digital communication project using ask  #wireless communication based projects  #wireless communication projects for final year  #wireless communication projects using python  #wireless communication mini projects  #project on wireless communication

People are good at skipping over material they already know!

View Related Topics to







Contact Us

Name

Email *

Message *

Popular Posts

Online Simulator for ASK, FSK, and PSK

Try our new Digital Signal Processing Simulator!   Start Simulator for binary ASK Modulation Message Bits (e.g. 1,0,1,0) Carrier Frequency (Hz) Sampling Frequency (Hz) Run Simulation Simulator for binary FSK Modulation Input Bits (e.g. 1,0,1,0) Freq for '1' (Hz) Freq for '0' (Hz) Sampling Rate (Hz) Visualize FSK Signal Simulator for BPSK Modulation ...
Read more

Constellation Diagrams of ASK, PSK, and FSK

📘 Overview of Energy per Bit (Eb / N0) 🧮 Online Simulator for constellation diagrams of ASK, FSK, and PSK 🧮 Theory behind Constellation Diagrams of ASK, FSK, and PSK 🧮 MATLAB Codes for Constellation Diagrams of ASK, FSK, and PSK 📚 Further Reading 📂 Other Topics on Constellation Diagrams of ASK, PSK, and FSK ... 🧮 Simulator for constellation diagrams of m-ary PSK 🧮 Simulator for constellation diagrams of m-ary QAM BASK (Binary ASK) Modulation: Transmits one of two signals: 0 or -√Eb, where Eb​ is the energy per bit. These signals represent binary 0 and 1.    BFSK (Binary FSK) Modulation: Transmits one of two signals: +√Eb​ ( On the y-axis, the phase shift of 90 degrees with respect to the x-axis, which is also termed phase offset ) or √Eb (on x-axis), where Eb​ is the energy per bit. These signals represent binary 0 and 1.  BPSK (Binary PSK) Modulation: Transmits one of two signals...
Read more

BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, ...

📘 Overview of BER and SNR 🧮 Online Simulator for BER calculation of m-ary QAM and m-ary PSK 🧮 MATLAB Code for BER calculation of M-ary QAM, M-ary PSK, QPSK, BPSK, ... 📚 Further Reading 📂 View Other Topics on M-ary QAM, M-ary PSK, QPSK ... 🧮 Online Simulator for Constellation Diagram of m-ary QAM 🧮 Online Simulator for Constellation Diagram of m-ary PSK 🧮 MATLAB Code for BER calculation of ASK, FSK, and PSK 🧮 MATLAB Code for BER calculation of Alamouti Scheme 🧮 Different approaches to calculate BER vs SNR What is Bit Error Rate (BER)? The abbreviation BER stands for Bit Error Rate, which indicates how many corrupted bits are received (after the demodulation process) compared to the total number of bits sent in a communication process. BER = (number of bits received in error) / (total number of tran...
Read more

Q-function in BER vs SNR Calculation

Q-function in BER vs. SNR Calculation In the context of Bit Error Rate (BER) and Signal-to-Noise Ratio (SNR) calculations, the Q-function plays a significant role, especially in digital communications and signal processing . What is the Q-function? The Q-function is a mathematical function that represents the tail probability of the standard normal distribution. Specifically, it is defined as: Q(x) = (1 / sqrt(2Ï€)) ∫â‚“∞ e^(-t² / 2) dt In simpler terms, the Q-function gives the probability that a standard normal random variable exceeds a value x . This is closely related to the complementary cumulative distribution function of the normal distribution. The Role of the Q-function in BER vs. SNR The Q-function is widely used in the calculation of the Bit Error Rate (BER) in communication systems, particularly in systems like Binary Phase Shift Ke...
Read more

Theoretical BER vs SNR for m-ary PSK and QAM

Relationship Between Bit Error Rate (BER) and Signal-to-Noise Ratio (SNR) The relationship between Bit Error Rate (BER) and Signal-to-Noise Ratio (SNR) is a fundamental concept in digital communication systems. Here’s a detailed explanation: BER (Bit Error Rate): The ratio of the number of bits incorrectly received to the total number of bits transmitted. It measures the quality of the communication link. SNR (Signal-to-Noise Ratio): The ratio of the signal power to the noise power, indicating how much the signal is corrupted by noise. Relationship The BER typically decreases as the SNR increases. This relationship helps evaluate the performance of various modulation schemes. BPSK (Binary Phase Shift Keying) Simple and robust. BER in AWGN channel: BER = 0.5 × erfc(√SNR) Performs well at low SNR. QPSK (Quadrature...
Read more

Wiener Filter Theory: Equations, Error Signal, and MSE

  Assuming known stationary signal and noise spectra and additive noise, the Wiener filter is a filter used in signal processing to provide an estimate of a desired or target random process through linear time-invariant (LTI) filtering of an observed noisy process. The mean square error between the intended process and the estimated random process is reduced by the Wiener filter. Fig: Block diagram view of the FIR Wiener filter for discrete series. An input signal x[n] is convolved with the Wiener filter g[n] and the result is compared to a reference signal s[n] to obtain the filtering error e[n]. In the big picture, the signal is attenuated and added with noise, then the signal is passed through a Wiener filter. And the function of the Wiener filter is to minimize the mean square error between the filter output of the received signal and the reference signal by adjusting the Wiener filter tap coefficient.   Description...
Read more

MATLAB code for Pulse Code Modulation (PCM) and Demodulation

📘 Overview & Theory 🧮 Quantization in Pulse Code Modulation (PCM) 🧮 MATLAB Code for Pulse Code Modulation (PCM) 🧮 MATLAB Code for Pulse Amplitude Modulation and Demodulation of Digital data 🧮 Other Pulse Modulation Techniques (e.g., PWM, PPM, DM, and PCM) 📚 Further Reading MATLAB Code for Pulse Code Modulation clc; close all; clear all; fm=input('Enter the message frequency (in Hz): '); fs=input('Enter the sampling frequency (in Hz): '); L=input('Enter the number of the quantization levels: '); n = log2(L); t=0:1/fs:1; % fs nuber of samples have tobe selected s=8*sin(2*pi*fm*t); subplot(3,1,1); t=0:1/(length(s)-1):1; plot(t,s); title('Analog Signal'); ylabel('Amplitude--->'); xlabel('Time--->'); subplot(3,1,2); stem(t,s);grid on; title('Sampled Sinal'); ylabel('Amplitude--->'); xlabel('Time--->'); % Quantization Process vmax=8; vmin=-vmax; %to quanti...
Read more

Wide Sense Stationary Signal (WSS)

Q & A and Summary Stationary and Wide Sense Stationary Process A stochastic process {…, X t-1 , X t , X t+1 , X t+2 , …} consisting of random variables indexed by time index t is a time series. The stochastic behavior of {X t } is determined by specifying the probability density or mass functions (pdf’s): p(x t1 , x t2 , x t3 , …, x tm ) for all finite collections of time indexes {(t 1 , t 2 , …, t m ), m < ∞} i.e., all finite-dimensional distributions of {X t }. A time series {X t } is strictly stationary if p(t 1 + Ï„, t 2 + Ï„, …, t m + Ï„) = p(t 1 , t 2 , …, t m ) , ∀Ï„, ∀m, ∀(t 1 , t 2 , …, t m ) . Where p(t 1 + Ï„, t 2 + Ï„, …, t m + Ï„) represents the cumulative distribution function of the unconditional (i.e., with no reference to any particular starting value) joint distribution. A process {X t } is said to be strictly stationary or strict-sense stationary if Ï„ doesn’t affect the function p. Thus, p is not a function of time. A time series {X t } ...
Read more