Matlab code by 2016a version, Slides of Digital Communication Systems

Adaptive delta modulation using matlab code

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2018/2019

Uploaded on 09/30/2019

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Aim:- To study Adaptive Delta Modulation Technique.
Apparatus:- Matlab 2013a, PC.
Theory:- Adaptive delta modulation (ADM) or continuously variable slope delta modulation
(CVSD) is a modification of DM in which the step size is not fixed. Rather, when several
consecutive bits have the same direction value, the encoder and decoder assume that slope
overload is occurring, and the step size becomes progressively larger. Otherwise, the step
size becomes gradually smaller over time. ADM reduces slope error, at the expense of
increasing quantizing error. This error can be reduced by using a low pass filter ADM
provides robust performance in the presence of bit errors meaning error detection and
correction are not typically used in an ADM radio design, this allows for a reduction in host
processor workload.
Diagrams:-
MATLAB Code:-
clc;
clear all;
close all;
%% Input Signals, m(t).
t = 0 : 2*pi/100 : 2*pi;
mt = sin(t); % Sine wave.
mt = sin(t) + 2; % Sine wave with non-zero DC value.
%% Step Size, S.
quantizationLevels = 16;
S = (max(mt) - min(mt)) / quantizationLevels;
%% Modulate.
totalSamples = length(mt) - 1;
mqt = zeros(1, totalSamples); % Quantized Signal, mq(t).
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Aim:- To study Adaptive Delta Modulation Technique.

Apparatus:- Matlab 2013a, PC.

Theory:- Adaptive delta modulation (ADM) or continuously variable slope delta modulation (CVSD) is a modification of DM in which the step size is not fixed. Rather, when several consecutive bits have the same direction value, the encoder and decoder assume that slope overload is occurring, and the step size becomes progressively larger. Otherwise, the step size becomes gradually smaller over time. ADM reduces slope error, at the expense of increasing quantizing error. This error can be reduced by using a low pass filter ADM provides robust performance in the presence of bit errors meaning error detection and correction are not typically used in an ADM radio design, this allows for a reduction in host processor workload.

Diagrams:-

MATLAB Code:- clc; clear all; close all;

%% Input Signals, m(t). t = 0 : 2pi/100 : 2pi; mt = sin(t); % Sine wave. mt = sin(t) + 2; % Sine wave with non-zero DC value.

%% Step Size, S. quantizationLevels = 16; S = (max(mt) - min(mt)) / quantizationLevels;

%% Modulate. totalSamples = length(mt) - 1; mqt = zeros(1, totalSamples); % Quantized Signal, mq(t).

dk = zeros(1, totalSamples); % Output Binary Sequence, d[k]. dt = 0; % Difference, d(t) = m(t) - mq(t). Sk = zeros(1, totalSamples); % Step Size, S[k]. for n = 2 : totalSamples dt = mt(n) - mqt(n); if(dt >= 0) dk(n) = 1; else dk(n) = -1; end Sk(n) = abs(Sk(n-1))dk(n) + Sdk(n-1); mqt(n+1) = mqt(n) + Sk(n); end

%% Display Modulation Result. plot(t, mt,'r','LineWidth',2); hold on; stairs(t, mqt,'k','LineWidth',2); axis([t(1) t(end) (min(min(mqt), min(mt)) - 0.5) (max(max(mqt), max(mt)) + 0.5)]); title('Adaptive Delta Modulation', 'Fontsize', 14); xlabel('Time'); ylabel('Amplitude'); legend('Input Signal, m(t)', 'Modulated Signal, m_q(t)'); grid on;

2) Overcome limitation of Granular Noise:- Quantization levels= 3