EFFICIENTLY UTILIZE THE SPECTRUM AND LOAD BALANCING IN COGNITIVE RADIO NETWORK USING GENETIC ALGORITHM WITH COVERSET PREDICTION

S. Kavitha, Dr. R. Kaniezhil
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Abstract

Wireless communication is one of the most in-demand fields of communication nowadays. Due to people's desire to transfer data as fast and broadly as possible, most communication processes are impacted by overloading and spectrum shortage when there is significant network usage. Make use of a cognitive radio network to keep an eye on things automatically, and use the spectrum dynamically to avoid overloading. Instead of evaluating the node's fitness, the CRN will alert the secondary user (SU) of the unused spectrum. To choose the fittest node in an environment with a coverage zone, a cognitive radio network in the proposed work uses a genetic algorithm plus coverset prediction. To address these issues, this paper offers a CRN calculation strategy.
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利用遗传算法和覆盖集预测在认知无线电网络中有效利用频谱和平衡负载
无线通信是当今最热门的通信领域之一。由于人们希望尽可能快速、广泛地传输数据,当网络使用量较大时,大多数通信过程都会受到过载和频谱短缺的影响。利用认知无线电网络,可以自动监测情况,动态使用频谱,避免过载。认知无线电网络不会评估节点的适配性,而是会提醒二级用户(SU)未使用的频谱。为了在有覆盖区的环境中选择最合适的节点,本文提出的认知无线电网络使用了遗传算法和覆盖区预测。为解决这些问题,本文提出了一种 CRN 计算策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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EFFICIENTLY UTILIZE THE SPECTRUM AND LOAD BALANCING IN COGNITIVE RADIO NETWORK USING GENETIC ALGORITHM WITH COVERSET PREDICTION MISE EN PLACE D'UN SYSTEME DISTRIBUE DE PUBLICATION DES CURSUS ACADEMIQUES DES ETUDIANTS A REVIEW ON WIRELESS NETWORK AND ELECTRONIC COMMUNICATION DEVELOPMENT OF AN EFFECTIVE SYSTEM FOR DETECTING CYBERCRIMES USING MODIFIED RIPPLE DOWN RULE SYSTEM AND NEURAL NETWORK. AUTOMATED PERSONALITY PREDICTIVE MODEL FOR E-RECRUITMENT USING LOGISTIC REGRESSION TECHNIQUE
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