Cooperative Learning for Spectrum Management in Railway Cognitive Radio Network

2019 ◽  
Vol 68 (6) ◽  
pp. 5809-5819
Author(s):  
Cheng Wu ◽  
Cheng Wang ◽  
Jie Sheng ◽  
Yiming Wang
Author(s):  
Bhuvaneswari P. T. V. ◽  
Bino J.

Cognitive radio network (CRN) is an upcoming networking technology that can utilize both radio spectrum and wireless resources efficiently based on the information gathered from the past experience. There are two types of users in CRN, namely primary and secondary. PUs (PU) have the license to operate in certain spectrum band while the secondary (SU) or cognitive radio (CR) users do not have the license to operate in the desired band. However, they can opportunistically utilize the unused frequency bands. Spectrum sensing, spectrum management, spectrum sharing, and spectrum mobility are the four major functions of cognitive radio systems. The main objective of spectrum sensing is to provide better spectrum access to CR users, without causing any harmful interference to PUs. Sensing accuracy is considered as the most important factor to determine the performance of cognitive radio network. In this chapter, the challenges and requirement involved in spectrum sensing are detailed. Further, various spectrum sensing basic techniques are also discussed in detail.


Author(s):  
K. R. Damindra S. Bandara ◽  
Anthony P. Melaragno ◽  
Duminda Wijesekara ◽  
Paulo Costa

Positive Train Controller (PTC) is a communication based system designed to enforce PTC safety objectives for trains such as train-to-train collisions, train derailments, and ensure railroad worker safety. Existing PTC designs consider risks due to operational environment such as location of other trains, switches, and speed limits. We propose to enhance PTC by using a multi-tiered cognitive radio network that considers multiple risks such as those due to bandwidth congestion, packet length limitations, propagation losses, detectable exploitation of Software Defined Radio vulnerabilities, and protocol vulnerabilities. Radios operating at PTC nodes (such as train, WIU and Base station) is equipped with a cognitive layer, which communicates with other nodes to create a cognitive radio network. The proposed network as a whole strives to provide spectrum management and security for the radio communication system, which can enhance the PTC functionality. Each cognitive radio in our proposed network consists of multiple tiers. The upper tier consists of a master cognitive engine that holistically evaluates the operational risks of the network and acts to mitigate them using the lower tiers. The lower tier (immediate slave tier to the master) consists of sub cognitive engines for cryptographic operations and spectrum management. The traditional PTC protocol is implemented at a lower tier module that interface with the master Cognitive Engine (CE). The master-slave communications within one radio is implemented using middleware. The proposed cognitive radio network can be modeled as a cyber-physical system by incorporating train movement dynamics, radio transmission characteristics and cryptographical computations, thereby constituting a distributed system of communicating hybrid automatons. This design enables us to verify safety and the security of the system using formal methods, which constitutes our ongoing work. We also discuss potential issues such as FRA mandated safety cases that needs to be addressed if the proposed features are to be added to the PTC systems.


2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Muddasir Rahim ◽  
Riaz Hussain ◽  
Irfan Latif Khan ◽  
Ahmad Naseem Alvi ◽  
Muhammad Awais Javed ◽  
...  

In this paper, we propose an innovative self-organizing medium access control mechanism for a distributed cognitive radio network (CRN) in which utilization is maximized by minimizing the collisions and missed opportunities. This is achieved by organizing the users of the CRN in a queue through a timer and user ID and providing channel access in an orderly fashion. To efficiently organize the users in a distributed, ad hoc network with less overhead, we reduce the sensing period through parallel sensing wherein the users are divided into different groups and each group is assigned a different portion of the primary spectrum band. This consequently augments the number of discovered spectrum holes which then are maximally utilized through the self-organizing access scheme. The combination of two schemes augments the effective utilization of primary holes to above 95%, even in impasse situations due to heavy primary network loading, thereby achieving higher network throughput than that achieved when each of the two approaches are used in isolation. By efficiently combining parallel sensing with the self-organizing MAC (PSO-MAC), a synergy has been achieved that affords the gains which are more than the sum of the gains achieved through each one of these techniques individually. In an experimental scenario with 50% primary load, the network throughput achieved with combined parallel sensing and self-organizing MAC is 50% higher compared to that of parallel sensing and 37% better than that of self-organizing MAC. These results clearly demonstrate the efficacy of the combined approach in achieving optimum performance in a CRN.


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