Skip to main content

Function of a Decision Feedback Equalizer (DFE) Equalizer (with MATLAB)

 

Decision Feedback Equalizer is the abbreviation for this. We know that in a typical wireless communication scenario, different multipath cause the signal to arrive at the receiver at different times after transmitting it from the transmitter. Our signal may show a slight spatial frequency shift as a result. By using several taps to receive signals with varying time delays or signals with a slight frequency shift, equalizers solve this problem by changing their tap weights.

Decision feedback equalizers continuously update their tap coefficient vectors by reducing the error between the desired signal and adaptive filter output.

Inter-symbol interference (ISI) happens in a typical wireless communication system when the modulation bandwidth exceeds the radio channel's coherence bandwidth. Equalization reduces the ISI produced by multipath within a time-dispersive channel.

** Coherence bandwidth is the bandwidth (range of frequencies) over which the channel is constant is called coherence bandwidth

Both feed-forward taps and feed-backward taps are used in a DFE equalizer. 

'Input' - Input signal, specified as a column vector
'Desired' - Training symbols (column vector). The vector length of the desired must be less than or equal to the length of the input.
'Train' - Train equalizer flag. It starts training when the value changes from 0 to 1.
'Error' - Error signal (column vector)
'Weight' - Tap weights

The error between the feedforward and feedback signal is used to adjust the tap weights. To recover the original signal, it also converges the tap weights. DFE uses an adaptive algorithm at the receiver side to track the changing channel and modifies the weight of its filter to recover the known pilot signal most of the time. The data bits are then appropriately corrected. Pilot signals are provided at short intervals and are known to the receiver to track the communication channel or medium's frequently changing characteristics.

 


QPSK + Multipath + Decision Feedback Equalizer (DFE)

20 BER Before: 0 | BER After: 0

Simulator Workflow & Mathematics

1 The Signal Path

  1. QPSK Modulation Random bits are grouped into pairs and mapped to complex symbols: s = exp(j * (π/4 + kπ/2)).
  2. Multipath Channel The signal is convolved with a multi-tap impulse response, simulating reflections that cause Inter-Symbol Interference (ISI).
  3. DFE Equalization A Feedforward Filter (FFF) suppresses precursor ISI, while a Feedback Filter (FBF) subtracts post-cursor ISI using previous symbol decisions.

2 The DFE Equations

// 1. Equalizer Output

y[n] = Σ(w_f[k] * x[n-k]) - Σ(w_b[k] * d[n-k])

(Feedforward Output - Feedback Correction)

// 2. Error Calculation

e[n] = d_known[n] - y[n]

// 3. LMS Weight Update

w_f[k] = w_f[k] + μ * e[n] * x*[n-k]

w_b[k] = w_b[k] - μ * e[n] * d*[n-k-1]

Where μ is the step size, x* is the conjugate of the received signal, and d are previous decisions.

Also read about

[2] Adaptive Equalizer to mitigate Channel Distortion (in MATLAB)

[3] Roll of an Equalizer in Channel Estimation




Contact Us

Name

Email *

Message *

Popular Posts

Hybrid Beamforming | Page 1

Beamforming Techniques Hybrid Beamforming... Page 1 | Page 2 | Hybrid Beamforming: Hybrid beam formation was developed to address some of the limitations of digital pre-coding approaches. Every antenna element is connected to an RF chain in digital pre-coding (beam forming) method. We also know that each RF chain is in charge of providing a separate data stream between the transmitter and the receiver. We know that a larger number of independent data streams leads to higher data rates. It has a spatial multiplexing feature for MIMO. As a result, we may assume that switching from MIMO to massive MIMO will benefit us more in terms of spatial multiplexing in massive MIMO, where each antenna is coupled to a single RF chain. We'll proceed with a definition of hybrid beam forming. Overview of hybrid beam forming with example: Unlike digital beam forming, more than one antenna element is connected to a single RF chain in hybr...

MATLAB Code for 8-PSK, 16-PSK, ...

šŸ“˜ Overview & Theory 🧮 MATLAB Code for BPSK, QPSK, 8-PSK, 16-PSK, 32-PSK 🧮 Simulator for m-ary PSK šŸ“š Further Reading   MATLAB Code for BPSK, QPSK, 8-PSK, 16-PSK, 32-PSK clc; clear all; close all; rng(10) M = 8; % M = 2, 4, 8, 16, 32, etc. N_Bits = 2520; Phase = 0; data_info_bit = randi([0,1],N_Bits,1); data_temp = bi2de(reshape(data_info_bit,N_Bits/log2(M),log2(M))); modData = pskmod(data_temp,M,Phase); figure(1); scatterplot(modData); channelAWGN = 15; rxData2 = awgn(modData, channelAWGN); figure(2); scatterplot(rxData2); demodData = pskdemod(rxData2,M,Phase);   for BPSK, Constellation Size, M = 2 for QPSK, M = 4 for 8-PSK, M = 8, and so on    Output Figure: 8-PSK Modulation Figure: 8-PSK Demodulation after adding AWGN Noise Using the above MATLAB code you'll able be to modulate and demodulate 2-PSK, 4-PSK, 8-PSK, 16-PSK, 32-PSK and so on.  16-PSK   Fig: 16-PSK In this above code ' M ' is the number of the conste...

UGC NET Electronic Science Previous Year Question Papers with Solutions

Home / Engineering & Other Exams / UGC NET 2026 PYQ ⬇️ Download Papers and Solutions šŸ“‹ Exam Pattern šŸ’” Preparation Tips ❓ FAQs šŸ“Š Exam Highlights: Electronic Science (88) Feature Details Junior Research Fellowship (JRF) ₹37,000 + HRA per month Eligibility M.Sc/M.Tech in Electronics (55%) Validity of Certificate JRF (3 Years) | Lectureship (Lifetime) šŸ“„ Download UGC NET Electronics PDFs Complete collection of previous year question papers, answer keys and explanations for Subject Code 88. Start Downloading šŸ“‚ View All Question Papers June 2025 - Question Paper Download PDF June 2025 - Solved Paper + Explanation ...

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 (Ļ„)} Here, R x (Ļ„)}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 ...

Advanced M-ary Modulation Simulator: Constellation, min dist, Efficiency, SER, EVM (RMS)

Advanced M-ary Communication Lab Analytical & Statistical Performance of Digital Modulation Theoretical Probability of Error (\(P_s\)) \[ P_s = Q\left(\sqrt{\frac{2 E_b}{N_0}}\right) \] Modulation (M-ary) BPSK (M=2) QPSK (M=4) 8-PSK (M=8) 16-QAM (M=16) 64-QAM (M=64) 256-QAM (M=256) SNR (\(E_b/N_0\)): 12 dB Efficiency 2 bps/Hz Min Dist (\(d_{min}\)) 1.41 Symbol Error 1.2e-5 EVM (RMS) 0.0% Constellation Diagram Noise PDF & Decision Tail 1. Geometric Mapping ...

Frequency Shift Keying (FSK) Modulation & Demodulation (with Simulation)

Frequency Shift Keying (FSK) Theoretical Foundations: Frequency Shift Keying (FSK) is a discrete frequency modulation scheme wherein the digital information is encoded via instantaneous shifts in the carrier signal's frequency. The fundamental implementation is Binary FSK (BFSK), which maps binary data onto two distinct, discrete spectral states. A binary '1' (the "mark" state) is represented by a carrier frequency \( f_1 \), while a binary '0' (the "space" state) corresponds to frequency \( f_2 \). Each symbol is sustained for a bit interval denoted by \( T_b \). FSK Transmitter Characterization: The mathematical model for the modulated BFSK output \( s(t) \) is defined as: \[ s(t) = \begin{cases} A_c \cos(2\pi f_1 t), & \text{for } m = 1 \\ A_c \cos(2\pi f_2 t), & \text{for } m = 0 \end{cases} \] ...

OFDM Symbols and Subcarriers Explained

This article explains how OFDM (Orthogonal Frequency Division Multiplexing) symbols and subcarriers work. It covers modulation, mapping symbols to subcarriers, subcarrier frequency spacing, IFFT synthesis, cyclic prefix, and transmission. Step 1: Modulation First, modulate the input bitstream. For example, with 16-QAM , each group of 4 bits maps to one QAM symbol. Suppose we generate a sequence of QAM symbols: s0, s1, s2, s3, s4, s5, …, s63 Step 2: Mapping Symbols to Subcarriers Assume N sub = 8 subcarriers. Each OFDM symbol in the frequency domain contains 8 QAM symbols (one per subcarrier): Mapping (example) OFDM symbol 1 → s0, s1, s2, s3, s4, s5, s6, s7 OFDM symbol 2 → s8, s9, s10, s11, s12, s13, s14, s15 … OFDM sym...