scholarly journals Reinforcement Learning-Based Routing Protocol to Minimize Channel Switching and Interference for Cognitive Radio Networks

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-24
Author(s):  
Tauqeer Safdar Malik ◽  
Mohd Hilmi Hasan
Keyword(s):  
Reinforcement Learning ◽  
Cognitive Radio ◽  
Routing Protocol ◽  
Channel Selection ◽  
Network Simulator ◽  
Mac Layer ◽  
Channel Switching ◽  
Network Layer ◽  
Switching Event ◽  
Channel Information

In the existing network-layered architectural stack of Cognitive Radio Ad Hoc Network (CRAHN), channel selection is performed at the Medium Access Control (MAC) layer. However, routing is done on the network layer. Due to this limitation, the Secondary/Unlicensed Users (SUs) need to access the channel information from the MAC layer whenever the channel switching event occurred during the data transmission. This issue delayed the channel selection process during the immediate routing decision for the channel switching event to continue the transmission. In this paper, a protocol is proposed to implement the channel selection decisions at the network layer during the routing process. The decision is based on past and expected future routing decisions of Primary Users (PUs). A learning agent operating in the cross-layer mode of the network-layered architectural stack is implemented in the spectrum mobility manager to pass the channel information to the network layer. This information is originated at the MAC layer. The channel selection is performed on the basis of reinforcement learning algorithms such as No-External Regret Learning, Q-Learning, and Learning Automata. This leads to minimizing the channel switching events and user interferences in the Reinforcement Learning- (RL-) based routing protocol. Simulations are conducted using Cognitive Radio Cognitive Network simulator based on Network Simulator (NS-2). The simulation results showed that the proposed routing protocol performed better than all the other comparative routing protocols in terms of number of channel switching events, average data rate, packet collision, packet loss, and end-to-end delay. The proposed routing protocol implies the improved Quality of Service (QoS) of the delay sensitive and real-time networks such as Cellular and Tele Vision (TV) networks.

scholarly journals A Joint Channel Selection and Routing Protocol for Cognitive Radio Network

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Yuting Wang ◽  
Guoqiang Zheng ◽  
Huahong Ma ◽  
Yang Li ◽  
Jishun Li
Keyword(s):  
Cognitive Radio ◽  
Routing Protocol ◽  
Cognitive Radio Network ◽  
Great Influence ◽  
Channel Selection ◽  
Packet Transmission ◽  
Data Delivery ◽  
Radio Network ◽  
Channel Switching ◽  
Joint Channel

In cognitive radio network, the activities of primary users will cause great influence on the stability of multiple hops routes between cognitive users. In this regard, a joint channel selection and routing protocol, termed as CSRP, is proposed to ensure route stability and reduce route latency between cognitive users. The channel availability based on historical information and the channel switching delay are used as the channel selection criteria to choose the end-to-end shortest route which possesses high data delivery probabilities and low delays. Besides, simulation results show that the proposed protocol has a better performance in terms of packet transmission delay and data delivery rate compared with the routing protocols based on delay (TDRP) and based on joint routing and channel allocation (PUB-JRCA).

scholarly journals Reliable, Efficient, and Power Optimized Control-Channel Selection Scheme for Cognitive Radio Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Saleem Aslam ◽  
Adnan Shahid ◽  
Kyung Geun Lee
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Bit Error Rate ◽  
Error Rate ◽  
Channel Selection ◽  
Radio Networks ◽  
Control Channel ◽  
Centralized Control ◽  
Channel Switching ◽  
Selection Scheme

This paper presents a centralized control-channel selection scheme for cognitive radio networks (CRNs) by exploiting the variation in the spectrum across capacity, occupancy, and error rate. We address the fundamental challenges in the design of the control-channel for CRNs: (1) random licensed users (LUs) activity and (2) the economical and vulnerability concerns for a dedicated control-channel. We develop a knapsack problem (KP) based reliable, efficient, and power optimized (REPO) control-channel selection scheme with an optimal data rate, bit error rate (BER), and idle time. Moreover, we introduce the concept of the backup channels in the context of control-channel selection, which assists the CRs to quickly move on to the next stable channel in order to cater for the sudden appearance of LUs. Based on the KP and its dynamic programming solution, simulation results show that the proposed scheme is highly adaptable and resilient to random LU activity. The REPO scheme reduces collisions with the LUs, minimizes the alternate channel selection time, and reduces the bit error rate (BER). Moreover, it reduces the power consumed during channel switching and provides a performance, that is, competitive with those schemes that are using a static control-channel for the management of control traffic in CRNs.

scholarly journals PERFORMANCE ENHANCEMENTS OF COGNITIVE RADIO NETWORKS USING THE IMPROVED FUZZY LOGIC

2019 ◽  
Vol 2019 (2) ◽  
pp. 57-68 ◽  
Author(s):  
Dr. P Ebby Darney ◽  
Dr. I. Jeena Jacob
Keyword(s):  
Fuzzy Logic ◽  
Cognitive Radio ◽  
Spectrum Allocation ◽  
Network Simulator ◽  
Channel Switching ◽  
Secondary Users ◽  
Efficient Management ◽  
User Request ◽  
Radio Technology ◽  
Effective Decision

The rapid increase in the mobile device and the different types of wireless communication has led to the necessity of the extra spectrum allocation for the proper transmission of the information. Since the additional spectrum allocation for every network involved in the data transmission is a strenuous process, the efficient management of the spectrum allocation is preferred. The cognitive radio technology does a befitting service in the managing the allocation of the spectrum efficiently by providing the vacant spaces of the licensed users to the secondary users and vacating the secondary users when the licensed user request for the spectrum. This results in the deterioration in the performance of the secondary users due to the immediate evacuating. The conventional methods in the deciding the channel switching remains unsuitable for the cognitive radio network, so to have an effective decision on switching and selecting the channel the paper put forth the improved fuzzy logic that relies on the decision (IFDSS-GA) support system to handle both the switching of the channels and genetic algorithm to select the proper spectrum for conveyance. The evaluation of the proposed approach using the network simulator -2 determines the competency the IFDSS in terms of the throughput and switching rate.

scholarly journals CL-mWSNs: Cross Layer Model-Based QoS Centric Routing Protocol for Mission-Critical Cooperative Communication in Mobile WSNs

2019 ◽  
Vol 2 ◽  
pp. 53-63
Author(s):  
Kummathi Chenna Reddy ◽  
Geetha D. Devanagavi ◽  
Thippeswamy M. N
Keyword(s):  
Routing Protocol ◽  
Ieee 802.15.4 ◽  
Dynamic Network ◽  
Injection Rate ◽  
Service Differentiation ◽  
Link Quality ◽  
Management Service ◽  
Mac Layer ◽  
Network Layer ◽  
Mission Critical

The paper presents a robust QoS centric routing protocol for mission-critical communication over mobile Wireless Sensor Networks (CL-mWSN) that exploits dynamic network states from the different layers of the IEEE 802.15.4 protocol stack to make the routing decision. The CL-mWSN protocol exploits three key layers: application layer, network layer and MAC layer. It exhibits proactive network and node table management, service differentiation, fair resource scheduling and congestion detection, avoidance at the network layer, as well as dynamic link quality estimation and packet injection rate estimation at the MAC layer to assess its candidature as the best forwarding node for QoS-centric mission-critical communication. Simulation reveals that the proposed routing model exhibits higher throughput, minimum loss and deadline miss ratio that augments QoS provision in mobile WSNs.

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