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WorksheetsModulation Classification Quiz
Total questions: 20
Worksheet time: 10mins
Why do companies like Qualcomm and MediaTek use ML-based modulation classification inside smartphone chipsets?
To improve battery charging speed
To detect and adapt to changing wireless channel conditions
To increase phone brightness
To reduce phone weight
DRDO uses modulation classification mainly for:
Radar/communication interception and signal intelligence
Designing new mobile apps
Smart agriculture monitoring
Manufacturing car engines
How does modulation classification contribute to the efficiency of communication systems?
By increasing the cost of devices
By reducing the number of users on a network
By simplifying hardware requirements
By enabling faster data transmission rates
In telecom companies like Jio or Airtel, ML-based signal classification helps primarily in:
Deciding customer data pack prices
Network optimization and interference management
Hiring employees
Creating advertisements
Why is Linear Regression NOT used in industry for modulation classification?
It is illegal to use
It predicts continuous values, not categories
It consumes too much power
It requires expensive hardware
In ISRO ground stations, ML-based signal classification can help:
Monitor astronaut heart rate
Automatically detect the modulation of received satellite signals
Design spacecraft colors
Estimate fuel consumption of rockets
Which global company uses ML-based modulation detection in Wi-Fi chipsets?
Starbucks
Intel
Tessolve
Bosch
In automatic modulation classification (AMC), which feature is most useful for distinguishing PSK signals?
Amplitude envelope
Instantaneous phase
Zero-crossing rate
Crest factor
The constellation diagram of a signal is most useful for distinguishing between:
Analog modulations only
Digital modulations like BPSK, QPSK, QAM
Sensor noise types
Antenna types
Which company uses adaptive modulation (QPSK, 16-QAM, 64-QAM) in LTE modem chipsets to improve spectral efficiency?
Qualcomm
Sony
Nokia
DRDO
Which modulation technique is widely used in DVB-T/DVB-T2 digital TV broadcasting?
QPSK and QAM
ASK
FSK
CSS
Why is machine learning preferred over traditional feature-based methods for modulation classification?
ML requires no data
ML works better in noisy and fading environments
ML eliminates modulation
ML avoids signal processing
Which feature is most useful for distinguishing AM and FM signals?
Symbol rate
Amplitude pattern and frequency variation
Packet size
Bit length
Which stage of the ML pipeline removes unwanted noise from raw signals?
Preprocessing
Classification
Training
Labelling
FFT-based features mainly help in analyzing which domain?
Frequency domain
Time Domain
Spatial Domain
Bit Domain
Which dataset is widely used as a benchmark for modulation classification research?
RadioML
ImageNet
COCO
MNIST
Why is normalization important in ML-based signal classification?
To increase noise
To equalize feature scales
To reduce dataset size
To change modulation type
Which modulation scheme offers higher data rate but requires better SNR?
256-QAM
ASK
QPSK
FSK
Which industry sector heavily relies on modulation classification for signal intelligence (SIGINT)?
Defence
Healthcare
Automotive
Agriculture
Which job role is most closely associated with ML-based modulation classification?
Web Developer
Signal Processing Engineer
UI Designer
Database Administrator
