Cognitive Radio Architecture MCQs

Welcome to our comprehensive collection of Multiple Choice Questions (MCQs) on Cognitive Radio Architecture, a fundamental topic in the field of Cognitive Radio. Whether you're preparing for competitive exams, honing your problem-solving skills, or simply looking to enhance your abilities in this field, our Cognitive Radio Architecture MCQs are designed to help you grasp the core concepts and excel in solving problems.

In this section, you'll find a wide range of Cognitive Radio Architecture mcq questions that explore various aspects of Cognitive Radio Architecture problems. Each MCQ is crafted to challenge your understanding of Cognitive Radio Architecture principles, enabling you to refine your problem-solving techniques. Whether you're a student aiming to ace Cognitive Radio tests, a job seeker preparing for interviews, or someone simply interested in sharpening their skills, our Cognitive Radio Architecture MCQs are your pathway to success in mastering this essential Cognitive Radio topic.

Note: Each of the following question comes with multiple answer choices. Select the most appropriate option and test your understanding of Cognitive Radio Architecture. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

So, are you ready to put your Cognitive Radio Architecture knowledge to the test? Let's get started with our carefully curated MCQs!

Cognitive Radio Architecture MCQs | Page 3 of 15

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Q21.
Which among the following modes should be invoked when a considerable period of disuse is expected?

a.

Off

b.

Prayer

c.

Sleeping

d.

On

Discuss
Answer: (c).Sleeping Explanation:When long periods of disuse are predicted, the cognitive radio should enter into sleeping behaviour by itself. The cognitive radio is trained to identify situations that require sleeping behaviour. It may seek permission before entering sleep mode.
Q22.
What type of operations is performed in sleeping behaviour?

a.

No operation

b.

Non incremental machine learning

c.

Incremental machine learning

d.

Current knowledge generation

Discuss
Answer: (b).Non incremental machine learning Explanation:During sleeping behaviour, the radio processes the experience accumulated during the waking behaviour. This is accomplished by using non-incremental machine learning algorithms. It will map the present case integrated knowledge to overall integrated knowledge.
Q23.
What is the responsibility of prayer behaviour?

a.

Invoke sleeping behaviour

b.

Invoke waking behaviour

c.

Resolve conflicts

d.

Erase present input-response behaviour

Discuss
Answer: (c).Resolve conflicts Explanation:When the user chooses to disregard the decision taken by the cognitive radio, it is added to a list of conflicts. These conflicts may be resolved using overall knowledge developed during sleeping behaviour. Otherwise it is added to a list of unresolved conflicts which is resolved during praying behaviour.
Q24.
What language is used by prayer behaviour to work with the home network while resolving a conflict?

a.

Web Ontology Language

b.

Radio Knowledge Representation Language

c.

RoXen Macro Language

d.

Knowledge Query and Manipulation Language

Discuss
Answer: (d).Knowledge Query and Manipulation Language Explanation:Prayer behaviour resolves conflict with the help of home network. The conflict is presented to the network using Knowledge Query and Manipulation Language. If the conflict is resolved, it is integrated into overall knowledge.
Q25.
The entrance of a stimulus invokes a new cognition cycle.

a.

True

b.

False

c.

May be True or False

d.

Can't say

Discuss
Answer: (a).True Explanation:The entrance of a stimulus invokes a new cognition cycle during the waking behaviour. It is also invoked by the completion of cognition cycle which was already in process. The stimulus is obtained by monitoring the information signals such as voices, images, radio signals, etc.
Q26.
What is the full form of NP complexity?

a.

Non-deterministic polynomial time

b.

Non-linear polynomial time

c.

Non-probabilistic polynomial time

d.

Non-trainable polynomial time

Discuss
Answer: (a).Non-deterministic polynomial time Explanation:The non-deterministic polynomial time is a complexity class in the computational complexity theory. It is used to differentiate decision problems. NP is a collection of decision problems. When a decision results in action, it must have proof that can be confirmed in polynomial time by a deterministic Turing machine.
Q27.
Which among the following is a characteristic that need not be compulsorily present to overcome self-referential inconsistency in cognitive radio?

a.

Definition of process as a priori tightly bounded time epochs

b.

Step counting function

c.

Susceptible to Gödel-Turing condition

d.

Pre-defined actions that uses O (1) resources

Discuss
Answer: (c).Susceptible to Gödel-Turing condition Explanation:In order to computationally support real time transmission and reception, a process must be defined in priori tightly bounded time epochs. A pre-defined action that uses O (1) resources is defined in advance and a reliable step counting function must be present. This will help in avoiding unpredictable usage of resources and unpredictable self-referential loops.
Q28.
Why is the RXML statement <Self/> added in cognitive radio?

a.

To add cognitive architecture to cognitive radio

b.

To define functions

c.

To define interfaces

d.

To eliminate components

Discuss
Answer: (a).To add cognitive architecture to cognitive radio Explanation:The cognitive radio must evaluate, monitor, and access all resources including affirming downloads. The statement <Self/> is a self-referential component. It is used to add the aware, adaptive, and cognitive radio architecture to aware, adaptive and cognitive radio.
Q29.
What capability demand was boosted upon introduction of machine learning in cognitive radio?

a.

RF sensing

b.

Haptic sensing

c.

Knowledge acquisition

d.

Resource acquisition

Discuss
Answer: (c).Knowledge acquisition Explanation:Availability of knowledge of a certain degree is essential in cognitive radio to extract user knowledge pertaining to information services. The repeated occurrences of similar activity are considered as learning opportunities. This is exploited by machine learning for incremental knowledge acquisition.
Q30.
Which among the following methods enable identification of learning opportunities in machine learning in cognitive radio?

a.

Gamma distribution

b.

Joint probability statistics

c.

Variance

d.

Uniform distribution

Discuss
Answer: (b).Joint probability statistics Explanation:Machine learning uses joint probability statistics for exploiting learning opportunities that arise due to repeated occurrence of similar situation. High quality use cases help to locate classes of user and knowledge that fine tune the set of services being provided.
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