Enhanced Harris Hawk Multi-Objective Optimization Algorithm for Cognitive Radio-Vehicular Ad Hoc Networks
Abstract
In this paper is presented an Enhanced Harris Hawk Multi-Objective Optimization (EH-HHO) algorithm for joint spectrum allocation, interference mitigation, and energy efficiency optimization in Cognitive Radio–Vehicular Ad Hoc Networks (CR-VANETs). EH-HHO integrates adaptive exploration, dynamic switching, and crowding-distance preservation to avoid premature convergence and obtain well-distributed Pareto-optimal solutions. Extensive simulations, using the SUMO–OMNeT++, VEINS/ns-3, and hardware-in-the-loop experiments, show superior spectrum utilization, energy savings, and convergence speed compared to NSGA-II and MOPSO. Statistical validation confirms performance significance, highlighting the EH-HHO as an efficient non–deep learning framework for CR-VANET optimization.
Fields of Study & Subjects
Cognitive Radio Networks and Spectrum Sensing
Vehicular Ad Hoc Networks (VANETs)
Advanced Multi-Objective Optimization Algorithms
Publication details
- Journal / source
- Communications - Scientific letters of the University of Zilina
- Volume
- 28
- Issue
- 2
- Pages
- E21–E32
- Publication date
- 3 February 2026
- Language
- EN