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6G Networks and AI Worksheet

Total questions: 25

Worksheet time: 13mins

Name
Class
Date
1.

The primary vision of 6G networks is to support:

a)

Enhanced mobile broadband only

b)

Ultra-high data rates with intelligent connectivity

c)

Circuit-switched communication

d)

Voice-centric services

2.

One major limitation of 5G that motivates the development of 6G is:

a)

Excessive spectrum availability

b)

Inability to support massive intelligent devices

c)

Very high latency

d)

Lack of cloud integration

3.

Which AI technique is most suitable for real-time resource allocation in 6G networks?

a)

Supervised learning

b)

Reinforcement learning

c)

Unsupervised clustering

d)

Transfer learning

4.

6G networks aim to achieve latency approximately in the order of:

a)

10 ms

b)

5 ms

c)

1 ms

d)

Sub-millisecond

5.

Which architectural concept enables on-demand network services in 6G?

a)

Network slicing

b)

Packet switching

c)

Frequency hopping

d)

Circuit multiplexing

6.

The main role of AI in 6G communication systems is to:

a)

Replace wireless spectrum

b)

Enable intelligent, autonomous network operation

c)

Increase hardware complexity

d)

Eliminate edge computing

7.

A long-term vision of AI in 6G networks is to enable:

a)

Human-controlled networking

b)

Fully autonomous, self-evolving networks

c)

Static network optimization

d)

Reduced intelligence

8.

Identify the primary goal of energy-efficient 6G network architecture.

a)

Increase data rates at any cost

b)

Reduce energy consumption while maintaining performance

c)

Maximize hardware usage

d)

Eliminate network intelligence

9.

Which technology helps reduce transmission power by intelligently shaping the radio environment?

a)

Massive MIMO

b)

Intelligent Reflecting Surfaces

c)

Network slicing

d)

Optical fiber communication

10.

Which architectural approach enables energy-efficient service provisioning in 6G?

a)

Hardware-centric networking

b)

Fixed network architecture

c)

Software-Defined Networking (SDN)

d)

Circuit switching

11.

What is the primary objective of using Reinforcement Learning for energy-efficient resource allocation?

a)

Maximizing network throughput only

b)

Minimizing energy consumption while maintaining QoS

c)

Increasing hardware complexity

d)

Eliminating the need for optimization algorithms

12.

Which RL component provides feedback on energy efficiency and system performance?

a)

State

b)

Action

c)

Reward

d)

Transition

13.

Why is Reinforcement Learning suitable for energy-efficient resource allocation in wireless networks?

a)

It requires complete system models

b)

It adapts to dynamic and uncertain environments

c)

It avoids learning from experience

d)

It works only for static networks

14.

Which performance metric is most relevant in energy-efficient resource allocation?

a)

Energy per bit

b)

CPU clock speed

c)

Number of users only

d)

Signal bandwidth

15.

What does a Non-Terrestrial Network (NTN) in 6G primarily include?

a)

Only terrestrial base stations

b)

Satellites, HAPS, and UAVs

c)

Optical fiber networks

d)

Wired sensor networks

16.

Which non-terrestrial platform typically operates at the highest altitude?

a)

UAV

b)

HAPS

c)

LEO satellite

d)

Ground relay

17.

Why is AI particularly important for power management in NTNs?

a)

NTNs have static channel conditions

b)

Manual control is efficient

c)

NTNs experience highly dynamic topology and channel variations

d)

Power resources are unlimited

18.

The primary role of 6G in smart cities is to:

a)

Replace all wired networks

b)

Enable intelligent, ultra-connected, and sustainable urban services

c)

Increase energy consumption

d)

Eliminate IoT devices

19.

AI integration in 6G-enabled smart cities is mainly used to:

a)

Increase manual monitoring

b)

Reduce data analytics

c)

Optimize resource usage and automate decision-making

d)

Disable real-time services

20.

Which 6G technology supports real-time analytics close to IoT devices in smart cities?

a)

Centralized cloud computing only

b)

Batch processing

c)

Offline data storage

d)

Edge AI and edge computing

21.

Which 6G feature is MOST critical for large-scale IoT deployment in smart cities?

a)

Ultra-low latency and massive connectivity

b)

High hardware cost

c)

Fixed network topology

d)

Manual network control

22.

Which AI technique is MOST suitable for real-time slice resource optimization?

a)

Supervised learning

b)

Rule-based systems

c)

Manual configuration

d)

Reinforcement learning

23.

Which 6G service type requires ultra-low latency and high reliability?

a)

eMBB

b)

mMTC

c)

URLLC

d)

Best-effort services

24.

The main role of AI in network slicing for 6G is to:

a)

Increase network complexity

b)

Automate and optimize slice management dynamically

c)

Eliminate virtualization

d)

Fix resource allocation permanently

25.

Which 6G architecture component enables flexible network slicing?

a)

Legacy circuit switching

b)

Network Function Virtualization (NFV)

c)

Fixed hardware appliances

d)

Analog communication