Skip to main content

Delta Modulation & Demodulation



Delta Modulation & Demodulation Technique



Another name for delta modulation is a 1-bit quantizer. As a result, compared to PCM or DPCM, less bandwidth is needed here.


We know that bandwidth (BW),


BW = nfs/2 .........(1)




Where n = number of bits per sample


          fs = Frequency of Sampling





To avoid the cause of under-sampling, fs cannot be decreased in the above equation 1 to decrease bandwidth (BW). To retrieve the intended signal at the receiver side, we must keep our sample frequency at least two times the frequency of the message signal.



Alternatively, fs > 2fm



In this case, fm stands for message signal frequency, which is often the highest frequency available in message transmission.




However, in delta modulation, the bandwidth will be reduced to the smallest amount feasible by picking the lowest possible value of n, i.e. 1 bit/sample.


Assume that Rb = nfs is the data rate.


As a result, Rb = fs (if n=1 bit/sample)


So, in the delta modulation scheme, we can say,



Bit rate = Pulse rate = Sampling rate



Because we're only allocating 1 bit/sample, the number of levels is L = 2^(1) = 2. In general, the highest level is represented by '+∆', while the lowest level is represented by '-∆'. From the quantizer value we decide whether the sampling bit is '1' or '0'.










In delta modulation, we actually accomplish the following:



We compare the current sample value to the prior sample value in this modulation. When the difference (also known as "error") value exceeds the threshold value, the value is detected as "1." In the same way, if it goes below the threshold value, it will be '0'.







Diagram:











                                                                       Fig: Delta Modulation



Here, the input of the quantizer,


e(nTs) = m(nTs) – m^(nTs)


Where, m(nTs) = current sample

m^(nTs) = previous sample

The difference between the current sample value and the previous sample value (or, e(nTs)) is the quantizer's input. The modulated signal is represented as bit '1' if the difference value is greater than the threshold value (say, 0 Volt); otherwise, it is represented as bit '0'.


With the use of diagrams, we'll now discuss delta modulation (DM) and demodulation at the receiver side.



Delta Demodulation


Assume there are two levels (due to the one-bit quantizer) or that the quantizer step value is '+∆' and '–∆' on the negative side. '+∆' indicates a higher level, whereas '-∆' indicates a lower level.


Take a look at the quantizer diagram below. If the difference (or error value) between the current sample value and the prior sample value exceeds the threshold value, the sample will be converted to bit '1' (For your convenience, let's say, the threshold is 0 Volt). If the above-mentioned difference value is between 0 and + ∆ Volt, we convert it to bit '1'. Similarly, we translate to bit '0'  for values between 0 and - ∆ Volt.




Diagram of DM Quantizer:








DM Encoder:









DM Decoder at receiver side:








In decoding process, at t=0, sample value = 0

At, t = Ts, sample value = 0+∆ = +∆

      t = 2Ts, sample value = +∆ +∆ = +2∆

      t = 3Ts, sample value = +2∆ +∆ = +3∆

      t = 4Ts, sample value = +3∆ -∆ = +2∆

      t = 5Ts, sample value = +2∆ -∆ = +∆


Whenever the signal reaches the receiver it was 0, at t=0 & t< Ts; At t=Ts, we receive +∆. Now, the summation of the present sample value and previous sample value (which is '0' at the start) equals 0 +∆= +∆; At t=2Ts,  the sum of the current sample value and previous sample value = +∆ +∆ = +2∆ and so on (as shown in the above chart).

MATLAB Code for Delta Modulation and Demodulation

 
 
 

 
                                                                 (Get MATLAB Code)




People are good at skipping over material they already know!

View Related Topics to







Contact Us

Name

Email *

Message *

Popular Posts

BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, ...(MATLAB Code + Simulator)

📘 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...

BER performance of QPSK with BPSK, 4-QAM, 16-QAM, 64-QAM, 256-QAM, etc (MATLAB + Simulator)

📘 Overview 📚 QPSK vs BPSK and QAM: A Comparison of Modulation Schemes in Wireless Communication 📚 Real-World Example 🧮 MATLAB Code 📚 Further Reading   QPSK provides twice the data rate compared to BPSK. However, the bit error rate (BER) is approximately the same as BPSK at low SNR values when gray coding is used. On the other hand, QPSK exhibits similar spectral efficiency to 4-QAM and 16-QAM under low SNR conditions. In very noisy channels, QPSK can sometimes achieve better spectral efficiency than 4-QAM or 16-QAM. In practical wireless communication scenarios, QPSK is commonly used along with QAM techniques, especially where adaptive modulation is applied. Modulation Bits/Symbol Points in Constellation Usage Notes BPSK 1 2 Very robust, used in weak signals QPSK 2 4 Balanced speed & reliability 4-QAM ...

MATLAB code for BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ...(with Online Simulator)

🧮 MATLAB Code for BPSK, M-ary PSK, and M-ary QAM Together 🧮 MATLAB Code for M-ary QAM 🧮 MATLAB Code for M-ary PSK 📚 Further Reading MATLAB Script for BER vs. SNR for M-QAM, M-PSK, QPSK, BPSK % Written by Salim Wireless clc; clear; close all; num_symbols = 1e5; snr_db = -20:2:20; psk_orders = [2, 4, 8, 16, 32]; qam_orders = [4, 16, 64, 256]; ber_psk_results = zeros(length(psk_orders), length(snr_db)); ber_qam_results = zeros(length(qam_orders), length(snr_db)); for i = 1:length(psk_orders) psk_order = psk_orders(i); for j = 1:length(snr_db) data_symbols = randi([0, psk_order-1], 1, num_symbols); modulated_signal = pskmod(data_symbols, psk_order, pi/psk_order); received_signal = awgn(modulated_signal, snr_db(j), 'measured'); demodulated_symbols = pskdemod(received_signal, psk_order, pi/psk_order); ber_psk_results(i, j) = sum(data_symbols ~= demodulated_symbols) / num_symbols; end end for i...

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 ...

Theoretical BER vs SNR for binary ASK, FSK, and PSK with MATLAB Code + Simulator

📘 Overview & Theory 🧮 MATLAB Codes 📚 Further Reading Theoretical BER vs SNR for Amplitude Shift Keying (ASK) The theoretical Bit Error Rate (BER) for binary ASK depends on how binary bits are mapped to signal amplitudes. For typical cases: If bits are mapped to 1 and -1, the BER is: BER = Q(√(2 × SNR)) If bits are mapped to 0 and 1, the BER becomes: BER = Q(√(SNR / 2)) Where: Q(x) is the Q-function: Q(x) = 0.5 × erfc(x / √2) SNR : Signal-to-Noise Ratio N₀ : Noise Power Spectral Density Understanding the Q-Function and BER for ASK Bit '0' transmits noise only Bit '1' transmits signal (1 + noise) Receiver decision threshold is 0.5 BER is given by: P b = Q(0.5 / σ) , where σ = √(N₀ / 2) Using SNR = (0.5)² / N₀, we get: BER = Q(√(SNR / 2)) Theoretical BER vs ...

Doppler Delay

  Doppler Shift Formula When either the transmitter or the receiver is in motion, or when both are in motion, Doppler Shift is an essential parameter in wireless Communication. We notice variations in reception frequencies in vehicles, trains, or other similar environments. In plain language, the received signal frequency increases as the receiver moves toward the transmitter and drops as the receiver moves in the opposite direction of the transmitter. This phenomenon is called the Doppler shift or Doppler spread. Doppler Shift Formula: By equation,                fR = fT (+/-) fD                                      fR= receiving  frequency                                      fT= transmitted frequency              ...

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 ...

MATLAB Code for QPSK Modulation and Demodulation

📘 Overview 🧮 MATLAB Codes 🧮 Theory 🧮 BER performance of QPSK with BPSK, 4-QAM, 16-QAM, 64-QAM, 256-QAM, etc 📚 Further Reading   Quadrature Phase Shift Keying (QPSK) is a digital modulation scheme that conveys two bits per symbol by changing the phase of the carrier signal. Each pair of bits is mapped to one of four possible phase shifts: 0°, 90°, 180°, or 270° 00  ===> 0 degree phase shift of carrier signal 01  ===> 90 degree 11  ===> 180 degree 10  ===> 270 degree   MATLAB Script clc; clear all; close all; clc; M = 4; data = randi([0 (M-1)], 1000, 1); Phase = 0; modData=pskmod(data,M,Phase); figure(1); scatterplot(modData); channelAWGN = 15; rxData2 = awgn(modData, channelAWGN); figure(2); scatterplot(rxData2); demodData = pskdemod(rxData2,M,Phase);   Result data 1 0 2 2 0 2 1 . . . modData -1.00000000000000 + 1.22464679914735e-16i -1.83697019872103e-16 - 1.000000000000...