Bulletin of Electrical Engineering and Informatics Vol. 13, No. 1, February 2024, pp. 215~221 ISSN: 2302-9285, DOI: 10.11591/eei.v13i1.5222  215 Journal homepage: http://beei.org Link stability based multipath routing and effective mobility prediction in cognitive radio enabled vehicular ad hoc network Sami AbdulJabbar Rashid 1 , Mustafa Maad Hamdi 2 , Aymen Jalil AbdulElah 1 , Yasir Jasim Ahmed Rajab 1 , Khalid AbdulHakeem Zaaile 1 1 Department of Computer Engineering Techniques, Al-Maarif University College, Ramadi, Iraq 2 Department of Computer Science, College of Computer Science and Information Technology, University of Anbar, Ramadi, Iraq Article Info ABSTRACT Article history: Received Nov 13, 2022 Revised Dec 16, 2022 Accepted Feb 3, 2023 Vehicular ad hoc networks (VANETs) provide a robust infrastructure for intelligent transportation system (ITS) applications. VANET communication involves vehicle-to-vehicle and vehicle-to-infrastructure connections, primarily with roadside units (RSUs). Analyzing cognitive radio (CR)- VANET studies revealed two key performance issues: high energy consumption and latency. To address these challenges, we propose a novel approach: link stability and mobility prediction-based clustered CR- VANETs, known as LMCCR-VANET. LMCCR-VANET consists of four main components: CR-VANET construction, clustering model, speed-based mobility prediction, and link-based multipath routing. Initially, we establish cluster-based CR-VANETs to analyze and mitigate spectrum scarcity and power utilization problems in VANETs. Mobility prediction evaluates vehicle speed variations and predictions. Finally, employing link stability- based multipath routing (LSMR) in conjunction with the fuzzy interference model and ad hoc on-demand multipath distance vector (AOMDV) routing protocol ensures stable and efficient routing. Experimental results showcase the superiority of LMCCR-VANET. It exhibits enhanced energy efficiency, delivery rates, reduced energy consumption, end-to-end latency, and routing overhead when compared to recent works such as SCCR-VANET, CFCR- VANET, and MMCR-VANET. Keywords: Clustering Cognitive radio Extended link stability Mobility prediction Vehicular ad hoc networks This is an open access article under the CC BY-SA license. Corresponding Author: Sami AbdulJabbar Rashid Department of Computer Engineering Techniques, Al-Maarif University College Ramadi, Iraq Email: sami25.6.1989@gmail.com 1. INTRODUCTION Nowadays vehicular ad hoc networks (VANETs) become an important part of the intelligent transportation system (ITS) based application. The communication is performed in VANETs through a dedicated short-range communication with the IEEE 802.11 and IEEE 1609.4 as well as it helps to carry out the basic communication modules of VANETs such as vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication [1]. The usage of vehicles is enormously increased which provides the way to the creation of new technologies and algorithms as well as spectrum utilization and allocation in VANETs has become a complicated task. For that reason, a key enabling technology called cognitive radio (CR) is introduced in VANETs that allows devices to sense and use the spectrum and the licensed channels. CR-VANETs help to reduce the complicity which is created due to spectrum scarcity and they can able to provide safe road traffic and low congestion during the usage of next-generation autonomous-driving vehicles [2]–[4]. CR technology is an effective solution to overcome the spectrum-related issues in the network because in general in CR the