Aware Node Localization in Wireless Sensor Networks Using Harris Hawks Optimization
DOI:
https://doi.org/10.26636/jtit.2025.4.2285Keywords:
6G cognitive semantic communication, context-aware resource management, Harris hawks optimization, node positioning, semantic-aware localization, WSNAbstract
Precise and efficient localization is a key enabler for context-aware operations in emerging 6G cognitive semantic communication (CSC) systems. In AI-native and semantic-aware networks, precise node positioning improves semantic compression, context-driven routing, and adaptive spectrum allocation, positively affecting communication reliability and resource utilization efficiency. This paper addresses the problem of localization in wireless sensor networks (WSNs) in the broader context of 6G CSC, formulating it as an optimization task. Based on the previous research, we explore the application of bio-inspired metaheuristic algorithms to achieve robust and high accuracy positioning. Specifically, we propose the use of the Harris hawks optimization (HHO) algorithm to develop a semantic-aware, stable, and efficient localization framework. The proposed approach is implemented and tested within the Matlab simulation environment. Performance evaluation is conducted through comparative experiments with two widely used optimization algorithms: particle swarm optimization (PSO) and cuckoo search optimization (CSO). The simulation results demonstrate that the proposed HHO-based localization method not only improves positioning accuracy by up to 25% compared to the benchmarks, but also provides enhanced stability, enabling its integration with CSC architectures for intelligent resource management in next-generation networks.
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Copyright (c) 2025 Seddik Rabhi
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