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In recent times, wireless access technology is becoming increasinglycommonplace due to the ease of operation and installation of untetheredwireless media. The design of wireless networking is challenging due to thehighly dynamic environmental condition that makes parameter optimization acomplex task. Due to the dynamic, and often unknown, operating conditions,modern wireless networking standards increasingly rely on machine learning andartificial intelligence algorithms. Genetic algorithms (GAs) provide awell-established framework for implementing artificial intelligence tasks suchas classification, learning, and optimization. GAs are well-known for theirremarkable generality and versatility, and have been applied in a wide varietyof settings in wireless networks. In this paper, we provide a comprehensivesurvey of the applications of GAs in wireless networks. We provide both anexposition of common GA models and configuration and provide a broad rangingsurvey of GA techniques in wireless networks. We also point out open researchissues and define potential future work. While various surveys on GAs exist inliterature, our paper is the first paper, to the best of our knowledge, whichfocuses on their application in wireless networks.

Genetic Algorithms in Wireless Networking: Techniques, Applications, and Issues