Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our User Agreement and Privacy Policy.

Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our Privacy Policy and User Agreement for details.

Successfully reported this slideshow.

Like this document? Why not share!

8,450 views

Published on

communication engineering lab report, 5th sem, electrical engineering, IIT Delhi, eep306

No Downloads

Total views

8,450

On SlideShare

0

From Embeds

0

Number of Embeds

2

Shares

0

Downloads

0

Comments

0

Likes

10

No embeds

No notes for slide

- 1. Umang Gupta (2010EE50564) IndraBhushan (2010EE50548) VivekMangal (2010EE50566) Jitendra Kumar Meena (2009EE50483) 19-9-12 Experiment Delta Modulation Aim:To demonstrate modulation and de-modulation of Delta Modulation Scheme. Introduction: Delta modulation is a technique to convert analog-to-digital and digital-to-analog signal. This is used for voice transmission. In this modulation, signal is sent in differential form, the data is encrypted/transmitted in 1 bit. The analog signal is approximated with series of segments and each segment is compared to original analog to determine the change in relative amplitude. Hence only change in information is sent and if no change occurs it remains on the same state. Delta-modulation has to be oversampled to achieve high signal to noise ratio. If not oversampled there are problem of step over-load and granularity. Observations and remarks: Theoritical observations: Matlab code for Delta modulation of a 50Hz wave with 2000Hz sampling frequency % %signal sampling fs=1/2000; tn=0:fs:1/25; m=.5*sin(2*pi*50*tn); % %Delta modulation-demodulation StepSize=1/5; encode=dm_encoder(m, StepSize); decode=dm_decoder(StepSize,fs, encode); m_output=lpf(100, .1, decode); functions used: encoder function: functioncn=dm_encoder(x, StepSize) xlen = length(x); accum(1) = 0; fori=1:xlen if(x(i)>=accum(i)) e_n(i)=1;
- 2. accum(i+1) = accum(i) + e_n(i) * StepSize; else e_n(i)=-1; accum(i+1) = accum(i) + e_n(i) * StepSize; end end cn = e_n< 0; Decoder function: function [Sn]=dm_decoder(StepSize,fs, cn) xlen = length(cn); Ts=1/fs; n=0:Ts:Ts*(xlen-1); xlen = length(cn); accum(1) = 0; fori=1:xlen if(cn(i)==0) accum(i+1) = accum(i)+StepSize; else accum(i+1) = accum(i)-StepSize; end end Sn=accum(2:xlen+1); Low pass filter: function Sa=lpf(tap, cf, Sn) b=fir1(tap,cf); Sa = conv2(Sn,b,'same'); Graphs from Matlab:
- 3. Input signal Decoded signal projected on input signal
- 4. Signal for transmission Demodulated output signal Practical observations:
- 5. Waveforms for sampling freq 100Khz, 50Khz and 25 Khz respectively
- 6. on measuring the sampling frequnecy it comes out to be 100,50 and 25 for above three waveforms. Waveform showing staircase output
- 7. Wavefrom showing the transmitted signal (signal 4) Note that there is some delay and also it is inverted. Below are the two plots showing the demodualation. Note that signal 4 is demodualated signal.
- 8. Here the signal is erraneous because of smaller stepsize. Concluding remarks: Though modulation and demodulation is easy for delta modulation technique, but however it is not used much because it includes noise in the channel, which is undesirable.

No public clipboards found for this slide

Be the first to comment