Communications - Scientific letters of the University of Zilina X:X | DOI: 10.26552/com.C.2026.017

Enhanced Harris Hawk Multi-Objective Optimization Algorithm for Cognitive Radio-Vehicular Ad Hoc Networks

Md. Asif Hossain ORCID...
Southeast University, Department of Electrical and Electronic Engineering, Dhaka, Bangladesh

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.

Keywords: cognitive radio, Vehicular Ad hoc Networks (VANETS), multi-objective optimization, Harris Hawk optimization (HHO), hardware-in-the-loop experiments, spectrum allocation
Grants and funding:

The authors would like to thank Southeast University authority to support this work.

Conflicts of interest:

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Received: August 21, 2025; Accepted: December 15, 2025; Prepublished online: February 3, 2026 

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