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Lecture 06: Bit Error Rate (BER) Performance

Published: 2015/06/29

Channel: NOC15 July-Sep EC05

Lecture 07: Bit Error Rate (BER) of AWGN Channels

Published: 2015/07/03

Channel: NOC15 July-Sep EC05

BER vs SNR in BPSK - simulink

Published: 2016/04/04

Channel: wail nofal

Bit error rate (BER) measurement using the R&S®FSV signal and spectrum analyzer

Published: 2012/03/30

Channel: Rohde Schwarz

Lecture 08: Bit Error Rate of Rayleigh Fading Wireless Channel

Published: 2015/07/08

Channel: NOC15 July-Sep EC05

Bit Error Rate Test

Published: 2012/06/19

Channel: niasean

HOW TO MEASURE BER

Published: 2016/01/20

Channel: Tech Box

Experiment wise error rate

Published: 2013/08/14

Channel: Belinda Davey

Matlab program for BPSK BER under AWGN channel by Dr. K. Vinoth Babu

Published: 2016/04/25

Channel: Vinoth Babu

JDSU ValidatorPro BERT Test

Published: 2011/01/06

Channel: TEquipment.NET

Optical Bit Error Rate An Estimation Methodology

Published: 2017/05/27

Channel: Elizabeth Fry

Detector with Minimum Error Probability

Published: 2014/07/07

Channel: Anish Turlapaty

BER Performance of Digitial Modulation Schemes for AWGN, Rayleigh and Rician Channels

Published: 2015/04/29

Channel: Nayanatara Kolhapuri

ClearCurve® Multimode Fiber Cable and Bit Error Rate Performance

Published: 2010/07/28

Channel: Corning Optical Communications

Tasa de Error de BIT

Published: 2011/09/06

Channel: Corning Optical Communications

GNU Radio Tutorials: Part 2 - Hysteresis, Noise, Thresholds & Bit Error Rate

Published: 2012/06/03

Channel: balint256

NIWeek 2010 Digital Bit Error Rate Test on NI FlexRIO

Published: 2010/08/23

Channel: RyanVerret

Packet Error vs Bit Error Rate

Published: 2016/03/21

Channel: Anil Kumar Talari

Testing P25 RX and TX Bit Error Rate (BER)

Published: 2017/01/05

Channel: Freedom Communication Technologies

QEEE Lecture 5- Bit Error Rate

Published: 2014/08/27

Channel: Engineering & Technology

Lecture - 22 Probability of Error Calculation

Published: 2008/08/28

Channel: nptelhrd

Digital communications - Bit error curve (BER)

Published: 2014/09/16

Channel: JDSP Videos

Bit Error Rate experiment

Published: 2008/02/05

Channel: ett101

What Is The BER?

Published: 2017/08/11

Channel: Meissa Meissa

Bit Error Rate Testing and Pattern Generation for 400G

Published: 2014/04/24

Channel: Tektronix EMEA

QPSK Modulation in Matlab AWGN Channel - Part 1 (2016) Matlab Tutorial

Published: 2016/09/01

Channel: Uniformedia

Calculation of Bit Error Rate (BER) of M-ASK Modulation Type in Matlab -Part 38

Published: 2017/07/14

Channel: Tech_Tube

QPSK Modulation in Matlab AWGN Channel (BER) - Part 2 (2016) Matlab Tutorial

Published: 2016/11/20

Channel: Uniformedia

Introducing the FarSync Flex USB Sync/Async with Bit Error Rate Test (BERT) line quality tester

Published: 2010/10/28

Channel: Synchrotech

CDDC 2013 - Bit Error Rate Tester

Published: 2013/08/03

Channel: CoreEL Sandeepani

40 Gb/s BERT Tester | Optical Test | Tektronix

Published: 2014/05/02

Channel: Tektronix

Lecture 50: BER Performance of OFDM Systems

Published: 2015/08/18

Channel: NOC15 July-Sep EC05

Lecture 16: Examples for BER of Wireless Communication

Published: 2015/07/15

Channel: NOC15 July-Sep EC05

Bit Error Rate experiment demonstration on TIMS 301 system

Published: 2009/10/26

Channel: EmonaTIMS

HP AGILENT 70843B 0.1-12 GBIT/ BIT ERROR RATE TESTER / DATA PERFORMANCE ANALYZER

Published: 2014/04/01

Channel: sunrisesurplusinc

MeshConnect Packet Error Rate (PER) Test

Published: 2012/11/02

Channel: CELMarketing

Lec 19 | Principles of Communication-II | Bit Error Rate for QPSK | IIT Kanpur

Published: 2017/07/17

Channel: Principles of Communication Systems: Part - II

JDSU 8000 Test Set BER TEST

Published: 2015/09/07

Channel: Kyle W

Emona TIMS 1st Exp Bit Error Rate

Published: 2015/10/14

Channel: Mohammed Haidar Ahmad

Sigrity SystemSI DDR4 Bit Error Rate Analysis

Published: 2015/10/29

Channel: EMA EDA

FPGA Based Bit Error Rate Performance Measurement of Wireless Systems

Published: 2016/01/11

Channel: jpinfotechprojects

Matlab Code for Performance Analysis (BER vs Eb/N0) of BPSK, QAM, M-PSK, M-QAM, D-PSK, D-QAM etc..

Published: 2017/03/28

Channel: nischay malhan

Bit error rate BER) measurement using the Rohde & Schwarz FSV Signal and Spectrum Analyzer

Published: 2013/09/21

Channel: testequity

Bit Error Rate of PLC over one Km distance using ACSR conductor as signal wire

Published: 2016/08/25

Channel: Lalit Mohan Saini

Bit Error Rate (BER) in Digital Communication using MatLab in Arabic

Published: 2017/08/29

Channel: Free Courses

AWGN Performance analysis | BER

Published: 2014/05/09

Channel: TechPacs.com

Lecture 1: Noise Sources L Q factor and BER

Published: 2014/01/14

Channel: Leslie Rusch

How-To: B.E.R. testing

Published: 2013/01/14

Channel: Klasmeno_Fasoli

Matlab Script for Bit Error Rate (BER) by Dr. K. Vinoth Babu, VIT University

Published: 2017/08/01

Channel: DigiComm Matlab

Ber Analysis | WSN | Simulink Model | Wimax

Published: 2014/05/08

Channel: TechPacs.com

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In digital transmission, the number of **bit errors** is the number of received bits of a data stream over a communication channel that have been altered due to noise, interference, distortion or bit synchronization errors.

The **bit error rate** (**BER**) is the number of bit errors per unit time. The **bit error ratio** (also **BER**) is the number of bit errors divided by the total number of transferred bits during a studied time interval. Bit error ratio is a unitless performance measure, often expressed as a percentage.^{[1]}

The **bit error probability** *p _{e}* is the expectation value of the bit error ratio. The bit error ratio can be considered as an approximate estimate of the bit error probability. This estimate is accurate for a long time interval and a high number of bit errors.

As an example, assume this transmitted bit sequence:

0 1 1 0 0 0 1 0 1 1

and the following received bit sequence:

0 __0__ 1 0 __1__ 0 1 0 __0__ 1,

The number of bit errors (the underlined bits) is, in this case, 3. The BER is 3 incorrect bits divided by 10 transferred bits, resulting in a BER of 0.3 or 30%.

The **packet error ratio** (PER) is the number of incorrectly received data packets divided by the total number of received packets. A packet is declared incorrect if at least one bit is erroneous. The expectation value of the PER is denoted **packet error probability** *p _{p}*, which for a data packet length of

- ,

assuming that the bit errors are independent of each other. For small bit error probabilities and large data packets, this is approximately

Similar measurements can be carried out for the transmission of frames, blocks, or symbols.

In a communication system, the receiver side BER may be affected by transmission channel noise, interference, distortion, bit synchronization problems, attenuation, wireless multipath fading, etc.

The BER may be improved by choosing a strong signal strength (unless this causes cross-talk and more bit errors), by choosing a slow and robust modulation scheme or line coding scheme, and by applying channel coding schemes such as redundant forward error correction codes.

The *transmission BER* is the number of detected bits that are incorrect before error correction, divided by the total number of transferred bits (including redundant error codes). The *information BER*, approximately equal to the **decoding error probability**, is the number of decoded bits that remain incorrect after the error correction, divided by the total number of decoded bits (the useful information). Normally the transmission BER is larger than the information BER. The information BER is affected by the strength of the forward error correction code.

The BER may be evaluated using stochastic (Monte Carlo) computer simulations. If a simple transmission channel model and data source model is assumed, the BER may also be calculated analytically. An example of such a data source model is the Bernoulli source.

Examples of simple channel models used in information theory are:

- Binary symmetric channel (used in analysis of decoding error probability in case of non-bursty bit errors on the transmission channel)
- Additive white gaussian noise (AWGN) channel without fading.

A worst-case scenario is a completely random channel, where noise totally dominates over the useful signal. This results in a transmission BER of 50% (provided that a Bernoulli binary data source and a binary symmetrical channel are assumed, see below).

In a noisy channel, the BER is often expressed as a function of the normalized carrier-to-noise ratio measure denoted Eb/N0, (energy per bit to noise power spectral density ratio), or Es/N0 (energy per modulation symbol to noise spectral density).

For example, in the case of QPSK modulation and AWGN channel, the BER as function of the Eb/N0 is given by: .^{[2]}

People usually plot the BER curves to describe the performance of a digital communication system. In optical communication, BER(dB) vs. Received Power(dBm) is usually used; while in wireless communication, BER(dB) vs. SNR(dB) is used.

Measuring the bit error ratio helps people choose the appropriate forward error correction codes. Since most such codes correct only bit-flips, but not bit-insertions or bit-deletions, the Hamming distance metric is the appropriate way to measure the number of bit errors. Many FEC coders also continuously measure the current BER.

A more general way of measuring the number of bit errors is the Levenshtein distance. The Levenshtein distance measurement is more appropriate for measuring raw channel performance before frame synchronization, and when using error correction codes designed to correct bit-insertions and bit-deletions, such as Marker Codes and Watermark Codes.^{[3]}

The BER is the likelihood of a bit misinterpretation due to electrical noise . Considering a bipolar NRZ transmission, we have

for a "1" and for a "0". Each of and has a period of .

Knowing that the noise has a bilateral spectral density ,

is

and is .

Returning to BER, we have the likelihood of a bit misinterpretation .

and

where is the threshold of decision, set to 0 when .

We can use the average energy of the signal to find the final expression :

±§

**BERT** or **bit error rate test** is a testing method for digital communication circuits that uses predetermined stress patterns consisting of a sequence of logical ones and zeros generated by a test pattern generator.

A BERT typically consists of a test pattern generator and a receiver that can be set to the same pattern. They can be used in pairs, with one at either end of a transmission link, or singularly at one end with a loopback at the remote end. BERTs are typically stand-alone specialised instruments, but can be personal computer–based. In use, the number of errors, if any, are counted and presented as a ratio such as 1 in 1,000,000, or 1 in 1e06.

**PRBS**(pseudorandom binary sequence) – A pseudorandom binary sequencer of N Bits. These pattern sequences are used to measure jitter and eye mask of TX-Data in electrical and optical data links.**QRSS**(quasi random signal source) – A pseudorandom binary sequencer which generates every combination of a 20-bit word, repeats every 1,048,575 words, and suppresses consecutive zeros to no more than 14. It contains high-density sequences, low-density sequences, and sequences that change from low to high and vice versa. This pattern is also the standard pattern used to measure jitter.**3 in 24**– Pattern contains the longest string of consecutive zeros (15) with the lowest ones density (12.5%). This pattern simultaneously stresses minimum ones density and the maximum number of consecutive zeros. The D4 frame format of 3 in 24 may cause a D4 yellow alarm for frame circuits depending on the alignment of one bits to a frame.**1:7**– Also referred to as*1 in 8*. It has only a single one in an eight-bit repeating sequence. This pattern stresses the minimum ones density of 12.5% and should be used when testing facilities set for B8ZS coding as the 3 in 24 pattern increases to 29.5% when converted to B8ZS.**Min/max**– Pattern rapid sequence changes from low density to high density. Most useful when stressing the repeater’s ALBO feature.**All ones (or mark)**– A pattern composed of ones only. This pattern causes the repeater to consume the maximum amount of power. If DC to the repeater is regulated properly, the repeater will have no trouble transmitting the long ones sequence. This pattern should be used when measuring span power regulation. An unframed all ones pattern is used to indicate an AIS (also known as a*blue alarm*).**All zeros**– A pattern composed of zeros only. It is effective in finding equipment misoptioned for AMI, such as fiber/radio multiplex low-speed inputs.**Alternating 0s and 1s**- A pattern composed of alternating ones and zeroes.**2 in 8**– Pattern contains a maximum of four consecutive zeros. It will not invoke a B8ZS sequence because eight consecutive zeros are required to cause a B8ZS substitution. The pattern is effective in finding equipment misoptioned for B8ZS.**Bridgetap**- Bridge taps within a span can be detected by employing a number of test patterns with a variety of ones and zeros densities. This test generates 21 test patterns and runs for 15 minutes. If a signal error occurs, the span may have one or more bridge taps. This pattern is only effective for T1 spans that transmit the signal raw. Modulation used in HDSL spans negates the bridgetap patterns' ability to uncover bridge taps.**Multipat**- This test generates five commonly used test patterns to allow DS1 span testing without having to select each test pattern individually. Patterns are: all ones, 1:7, 2 in 8, 3 in 24, and QRSS.**T1-DALY**and**55 OCTET**- Each of these patterns contain fifty-five (55), eight bit octets of data in a sequence that changes rapidly between low and high density. These patterns are used primarily to stress the ALBO and equalizer circuitry but they will also stress timing recovery. 55 OCTET has fifteen (15) consecutive zeroes and can only be used unframed without violating one's density requirements. For framed signals, the T1-DALY pattern should be used. Both patterns will force a B8ZS code in circuits optioned for B8ZS.

A bit error rate tester (BERT), also known as a *bit error ratio tester*^{[citation needed]} or *bit error rate test solution* (BERTs) is electronic test equipment used to test the quality of signal transmission of single components or complete systems.

The main building blocks of a BERT are:

- Pattern generator, which transmits a defined test pattern to the DUT or test system
- Error detector connected to the DUT or test system, to count the errors generated by the DUT or test system
- Clock signal generator to synchronize the pattern generator and the error detector
- Digital communication analyser is optional to display the transmitted or received signal
- Electrical-optical converter and optical-electrical converter for testing optical communication signals

**^**Jit Lim (14 December 2010). "Is BER the bit error ratio or the bit error rate?". EDN. Retrieved 2015-02-16.**^**Digital Communications, John Proakis, Massoud Salehi, McGraw-Hill Education, Nov 6, 2007**^**"Keyboards and Covert Channels" by Gaurav Shah, Andres Molina, and Matt Blaze (2006?)

This article incorporates public domain material from the General Services Administration document "Federal Standard 1037C" (in support of MIL-STD-188).

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