CRN and 5G based IoT: Applications, Challenges and Opportunities

Siddikov, Ilkhom; Khujamatov, Khalimjon; Reypnazarov, Ernazar; Khasanov, Doston

doi:10.1109/icisct52966.2021.9670105

Cited by 30 publications

(5 citation statements)

References 12 publications

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“…The policy 𝜋(𝑠) is defined as a deterministic mapping of observation from S T to A T , such that: A T = 𝜇(S T ). The algorithm updates the policy function iteratively using the following equation: (3) 𝑄(S T , A T ) = 𝑅(S T , A T ) + 𝛾 𝑄 (S T+1 , 𝜇(S T+1 )) , where S T+1 is the next state, and 𝜇(S T+1 ) is the next action A T taken by the agent Ag in state S T+1 . The agent uses the actor-critic method to estimate the optimal policy, where the actor estimates the policy function and the critic estimates the Q-value function.…”

Section: Proposed Systemmentioning

confidence: 99%

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A Novel Self-Exploration Scheme for Learning Optimal Policies against Dynamic Jamming Attacks in Cognitive Radio Networks

Sudha,

Sarasvathi

2023

Cybernetics and Information Technologies

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Cognitive Radio Networks (CRNs) present a compelling possibility to enable secondary users to take advantage of unused frequency bands in constrained spectrum resources. However, the network is vulnerable to a wide range of jamming attacks, which adversely affect its performance. Several countermeasures proposed in the literature require prior knowledge of the communication network and jamming strategy that are computationally intensive. These solutions may not be suitable for many real-world critical applications of the Internet of Things (IoT). Therefore, a novel self-exploration approach based on deep reinforcement learning is proposed to learn an optimal policy against dynamic attacks in CRN-based IoT applications. This method reduces computational complexity, without prior knowledge of the communication network or jamming strategy. A simulation of the proposed scheme eliminates interference effectively, consumes less power, and has a better Signal-to-Noise Ratio (SNR) than other algorithms. A platform-agnostic and efficient anti-jamming solution is provided to improve CRN’s performance when jamming occurs.

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Section: Proposed Systemmentioning

confidence: 99%

“…However, the increased number of devices and the need for higher data rates require efficient utilization of the spectrum resources [2]. Cognitive Radio Network (CRN) can address these challenges by dynamically allocating and managing the spectrum resources to IoT devices based on their requirements and availability [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

A Novel Self-Exploration Scheme for Learning Optimal Policies against Dynamic Jamming Attacks in Cognitive Radio Networks

Sudha,

Sarasvathi

2023

Cybernetics and Information Technologies

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“…Nonrepudiation: Communicating parties in the CRN infrastructure do not want the receiver to deny receiving a message (destination nonrepudiation), and the sender to deny sending a message (source destination). Cryptology can be deployed to ensure, for example, that a CRN cannot deny it has received a request for a spectrum from PUs and SUs, and a CRN cannot deny a message received from a BS [19].…”

Section: Security In Crnmentioning

confidence: 99%

Analysis of Secure Cognitive Radio Network with Optimal Resource Management

Kumar,

Sharanya

2023

ijmst

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During the last decade, Cognitive Radio Network (CRN) technology has been a significant advance in addressing the ever-increasing spectrum demand. As the number of licensed and unlicensed users in a network rises to complete a certain activity, the information exchange between various types of traffic becomes more complex and difficult. Congestion in CRN is also caused by the conflict among several users for channel access (PUs and SUs). In a very crowded network, many applications perform badly owing to packet collisions and, as a result, packet loss before significant buffer queue building. This circumstance is aggravated by an increase in network users. Congestion control is a vital and essential aspect of the present research issue in communication networks. Several recent reviews in the literature indicate that the congestion issue in the CRN has not been thoroughly studied. Thus, effective and efficient congestion control strategies are sought to optimize network resource usage and management. To prevent congestion, it is crucial for CRN to do research on the creation of an efficient congestion management system. This will improve the network's resource consumption and performance. "Performance improvement via efficient spectrum management through optimum resource management and congestion control in the CRN by mitigating different threats" is the primary target of this project. This research also focused on enhancing performance by addressing security issues in an IoT-based CRN environment. This study provides a comprehensive review of several similar studies and their limitations, which may be used to formulate a new research target.

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“…To make effective use of wasted spectrums, cognitive radio networks (CRNs) have received more research and development [ [1] , [2] , [3] ]. Sorted by network access priority, CRNs mainly include two types of users: primary users (PUs) and secondary users (SUs) [ 4 , 5 ]. Cognitive radio (CR) can minimize the interference ratio between the two types of users in an effective way to make better use of the available spectrums [ 6 ].…”

Section: Introductionmentioning

confidence: 99%