1. Direct Sequence Spread Spectrum Modulation and Demodulation using Compressive Sensing Under the guidance of M.Venugopala Rao Submitted by K.Y.K.Kumari (11004192) G.Vamsidhar (11004201) A.Kartheek (11004322) A.Vinay Kumar (11004094)

2. Contents Introduction Objective Spread spectrum DSSS Block Diagram Tasks Results

3. Motivation  DSSS is a spread spectrum modulation technique for digital signal transmission.  Since DSSS is used for any specific signal we are trying to transmit different types of signals through DSSS  In addition to this we are using compressive sensing at receiver to reduce the complexity.

4. Objective  To transmit and receive various types of data signals initially and check for the presence of errors. 1.Binary 2.Text 3.Speech 4.Image  Using compressive sensing technique at receiver for better reception for all data signals.

5. Spread Spectrum  Important encoding method for wireless communications  Spread data over wide bandwidth  Makes jamming and interception harder  Signal modulated using sequence of digits i.e Spreading code/sequence  Increases bandwidth significantly  Spreads spectrum Receiver uses same sequence to demodulate signal  Types 1.DSSS (Direct Sequence Spread Spectrum) 2.FHSS ( Frequency Hopping Spread Spectrum)

6. DSSS Block Diagram

7. Tasks 1.Binary data transmission and reception 2.Text data transmission and reception 3.speech signal transmission and reception 4.Image transmission and reception 5.Speech transmission and reception using compression technique 6.Image transmission and reception using compression technique 7.speech transmission and reception using compressive sensing technique 8.Image transmission and reception using compressive sensing technique

8. Binary input DSSS Modulation DSSS Demodulation Binary output Binary through DSSS Random Input Binary sequenceOutput Binary Sequence

9. BER vs SNR for binary signal SNR BERBER

10. Text through DSSS Text to binary DSSS Modulation DSSS Demodulation Binary to text Text input Text output

11. Text signal was transmitted and received using DSSS modulation Input text signal Output text signal

12. BER vs SNR for text signal SNR BERBER

13. Speech through DSSS ADC DSSS Modulation DSSS Demodulation DAC speech input speech output Input speech signalOutput speech signal SNR = 26DB

14. Image through DSSS ADC DSSS Modulation DSSS Demodulation DAC Image input Image output Input imageOutput image fig1 Input image fig2 Output image Fig 3 Error generated SNR= 24DB

15. Colour image through DSSS Input colour image Output colour image Error generated SNR=23DB

16. Colour image-2 Input colour imageOutput colour image Error generated SNR=22DB

17. Compression technique Huffman coding: Variable length coding to use a lower number of bits to encode the data in to binary codes that occurs more frequently. The Compression Ratio depends on the probability as well as number of the compressed bits of the samples

18. Speech compression through DSSS ADC DSSS Modulation Speech input ENCODER DSSS Demodulation DAC Speech output DECODER

19. Result -1 Input speech signal before compression Recovered signal after decompression Error generated AMPLITUDEAMPLITUDE SAMPLES Speech signal of 2000 samples

20. Result -2 (speech signal of 4000 samples) Input speech signal before compression Recovered speech signal after compression Error generated SAMPLES AMPLITUDEAMPLITUDE Added noise SNR=9 signal SNR=23DB

21. Result -3 Input speech signal before compression Recovered speech signal after compression Error generated SAMPLES Added noise SNR=10 signal SNR=24DB AMPLITUDEAMPLITUDE ( speech signal of 4000 samples)

22. Result -4 Input speech signal before compression Recovered speech signal after compression Error generated SAMPLES Added noise SNR=11 signal SNR=25DB AMPLITUDEAMPLITUDE ( speech signal of 4000 samples)

23. Result-5 ( audio signal of 4000 samples) Input audio signal before compression output audio signal after decompression Error generated SAMPLES Added noise SNR=10 signal SNR=23DB AMPLITUDEAMPLITUDE

24. Compressive Sensing  simple and efficient signal acquisition technique that collects a few measurements about the signal of interest, and later uses optimization techniques for reconstruction of the original signal.  Sensing a signal in compressed form.

25. Future tasks Image transmission and reception using compression technique through DSSS speech transmission and reception using compression sensing through DSSS Image transmission and reception using compression sensing through DSSS

26. THANK YOU

27. ADC DSSS Modulation Image input ENCODER DSSS Demodulation DAC Image output DECODER