Computer Science Engineering (CSE) Exam > Computer Science Engineering (CSE) Notes > Chapter - Probability of Bit Error in ASK/PSK, PPT, ADC, Semester, Engineering
Chapter - Probability of Bit Error in ASK/PSK, PPT, ADC, Semester, Engineering - Computer Science Engineering (CSE) PDF Download
Introduction
The slides cover the following topics:
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EE104: Lecture 25 Outline
•Announcements
•Review of Last Lecture
•Probability of Bit Error in ASK/PSK
•Course Summary
•Hot Topics in Communications
•Next-Generation Systems
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Announcements
•HW 7 due Monday at 9 pm (no late HWs)
•Solutions will be posted then.
•Final Exam is Th., 3/20, 8:30am in Gates B03 (basement)
•Exam is open book/notes, covers through today’s lecture.
•Emphasis is on material after midterm, similar to practice finals
•SCPD student must make remote arrangements w/me by this Friday
•Practice finals posted on class website
•10 bonus points if turned in by 3/20 at 8:30am (Joice has solutions)
•Final Review: Monday 7-8pm (room 380-380Y)
•Extra Office Hours
•My extra hours: M 4:30-6:30, TW 12-2, and by appointment
•Jaron: W 4-6 (Bytes), Nikola: after review and T 5-7pm (110 Packard)
•τβπ will be done at end of class (10 bonus points)
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Review of Last Lecture
•Passband Digital Modulation
- ASK/PSK special cases of DSBSC
- FSK special case of FM
•ASK/PSK Demodulator:
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Noise in ASK/PSK
Eb is average energy per bit
Probability of Bit Error in ASK/PSK------------------------------------------Next slide
Course Summary
•Communication System Block Diagram
•Fourier Series and Transforms
•Sampling
•Power Spectral Density and Autocorrelation
•Random Signals and White Noise
•AM Modulation
•FM Modulation
•Digital Modulation
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Communication System Block Diagram
Source encoder converts message into a message signal or bits. Source decoder converts back to original format.
Transmitter converts message signal or bits into a transmitted signal at some carrier frequency.
Modulation, may also include SS, OFDM, precoding.
Channel introduces distortion, noise, and interference.
Receiver converts back to message signal or bits.
Demodulation (for SS and OFDM too), may also include equalization.
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Main Focus of This Class
Modulation encodes message or bits into the amplitude, phase, or frequency of carrier signal.
Channel filters signal and introduces noise
Demodulator recovers information from carrier
Need tools for manipulating and filtering signals and noise
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Fourier Series
Exponentials are basis functions for periodic signals
Can represent periodic signal in terms of FS coefficients
Complex coefficients are frequency components of signal
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Fourier Transform
Represents spectral components of a signal
Signal uniquely represented in time or frequency domain
These coefficients are frequency components of signal
Timelimited signals have infinite frequency content Bandlimited signals are infinite duration
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Key Properties of FTs
Frequency shifting (modulation)
- Multiplying signal by cosine shifts it by fc in frequency.
Multiplication in time ⇔ Convolution in Frequency
Convolution in time ⇔Multiplication in Frequency
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Filtering
Convolution defines output of LTI filters
Convolution (time) ⇔ Multiplication (freq.)
Easier to analyze filters in frequency domain
Filters characterized by time or freq. response
Exponentials are eigenfunctions of LTI filters
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Sampling
Sampling (Time):
Sampling (Frequency)
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Nyquist Sampling Theorem
A bandlimited signal [-B,B] is completely described by samples every .5/B secs.
- Nyquist rate is 2B samples/sec
Recreate signal from its samples by using a low pass filter in the frequency domain
- Sinc interpolation in time domain
- Undersampling creates aliasing
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Power Spectral Density
Distribution of signal power over frequency
PSD/autocorrelation FT pairs: Rx(t) ⇔ Sx(f)
Useful for filter and modulation analysis
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Random Signals
Not deterministic (no Fourier transform)
Signal contained in some set of possible realizations
Characterize by average PSD Sn(f)
Autocorrelation Rn(t)⇔ Sn(f) is the correlation of the random signal after time τ.
Measures how fast random signal changes
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Filtering and Modulation
Same PSD effect as for deterministic signals
Filtering
Modulation (no bandwidth constraint on Sn)
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White Noise
Signal changes very fast
Uncorrelated after infinitesimally small delay
Good approximation in practice
Filtering white noise: introduces correlation
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Amplitude Modulation
Constant added to signal m(t)
- Simplifies demodulation if 1>|kam(t)|
- Constant is wasteful of power
Modulated signal has twice the BW of m(t)
Simple modulators use nonlinear devices
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Double Sideband Suppressed Carrier (DSBSC)
Modulated signal is s(t)=Accos(2πfct)m(t)
Generated by a product or ring modulator
Requires coherent detection (φ2»φ1)
- Costas Loop
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Noise in DSBSC Receivers
Probability of Bit Error in ASK/PSK------------------------------------------Next slide
Single Sideband
Transmits upper or lower sideband of DSBSC
Reduces bandwidth by factor of 2
Uses same demodulator as DSBSC
Coherent detection required.
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FM Modulation
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FM Bandwidth and Carson’s Rule
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Generating FM Signals
NBFM
- Circuit based on product modulator
WBFM
- Direct Method: Modulate a VCO with m(t)
- Indirect Method: Use a NBFM modulator, followed by a nonlinear device and BPF
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FM Generation and Detection
Differentiator/Discriminator and Env. Detector
Zero Crossing Detector
- Uses rate of zero crossings to estimate fi
Phase Lock Loop (PLL)
- Uses VCO and feedback to extract m(t)
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ASK, PSK, and FSK
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ASK/PSK Demodulation
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FSK Demodulation (HW 7)
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Megathemes in EE104
Fourier analysis simplifies the study of communication systems
Modulation encodes information in phase, frequency, or amplitude of carrier
Noise and distortion introduced by the channel makes it difficult to recover signal
The communication system designer must design clever techniques to compensate for channel impairments or make signal robust to these impairments.
Ultimate goal is to get high data rates with good quality and low cost.
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Hot Topics in Communications
All-optical networks
Components (routers, switches) hard to build
Need very good lasers
Communication schemes very basic
Evolving to more sophisticated techniques
Advanced Radios
Adaptive techniques for multimedia
Direct conversion radios
Software radios
Low Power (last years on a battery)
Ultra wideband
Wireless Communications
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Future Wireless Systems
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FAQs on Chapter - Probability of Bit Error in ASK/PSK, PPT, ADC, Semester, Engineering - Computer Science Engineering (CSE)
| 1. What is the probability of bit error in ASK/PSK modulation schemes? |  |
Ans. The probability of bit error in ASK/PSK modulation schemes is influenced by various factors such as noise, interference, and the modulation scheme itself. It is typically calculated using the bit error rate (BER) formula, which takes into account the signal-to-noise ratio (SNR) and the modulation scheme. A higher SNR results in a lower probability of bit error.
| 2. How does the probability of bit error in ASK/PSK relate to the signal-to-noise ratio (SNR)? | |
Ans. The probability of bit error in ASK/PSK is inversely related to the signal-to-noise ratio (SNR). As the SNR increases, the probability of bit error decreases. This is because a higher SNR means that the signal is stronger compared to the background noise and interference, making it easier to detect and decode the transmitted bits accurately.
| 3. How does the probability of bit error in ASK/PSK affect the data transmission reliability? | |
Ans. The probability of bit error in ASK/PSK directly affects the data transmission reliability. A higher probability of bit error implies a higher chance of incorrect bit decoding, leading to data corruption. Therefore, in order to ensure reliable data transmission, it is important to minimize the probability of bit error by optimizing the signal quality, reducing noise, and employing error correction techniques.
| 4. What is the role of analog-to-digital converters (ADCs) in data transmission? | |
Ans. Analog-to-digital converters (ADCs) play a crucial role in data transmission by converting analog signals into digital form. In the context of ASK/PSK modulation, ADCs are used at the receiver end to convert the received analog signal, which may be distorted by noise and interference, into a digital representation. This allows for further processing and decoding of the received signal, enabling accurate recovery of the transmitted data.
| 5. How does the semester influence the study of computer science engineering? | |
Ans. The semester system in computer science engineering provides a structured approach to learning and progressing through the curriculum. Each semester focuses on specific subjects and topics, building upon the knowledge gained in previous semesters. It allows students to have a well-rounded understanding of computer science engineering concepts and skills over the course of their studies. The semester system also facilitates the evaluation and assessment of students' progress through regular examinations and assignments.
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