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Optimal Hybrid Channel Allocation:Based On Machine Learning Algorithms

2013/09/28 by K Anand Viswanadh, K Viswanadh, Viswanadh, K +3
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Advanced Wireless Communication Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Networking and Internet Architecture (cs.NI) #Wireless Communication Networks Research #cs.LG #cs.NI

paper · pdf · doi:10.48550/arxiv.1309.7439

5 pages, 1 figure

arxiv created 2013/09/28 · openalex publication_date 2013/09/28 · arxiv updated 2013/10/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Recent advances in cellular communication systems resulted in a huge increase in spectrum demand. To meet the requirements of the ever-growing need for spectrum, efficient utilization of the existing resources is of utmost importance. Channel Allocation, has thus become an inevitable research topic in wireless communications. In this paper, we propose an optimal channel allocation scheme, Optimal Hybrid Channel Allocation (OHCA) for an effective allocation of channels. We improvise upon the existing Fixed Channel Allocation (FCA) technique by imparting intelligence to the existing system by employing the multilayer perceptron technique.

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