东南大学学报（英文版）2018，Vol.34Issue(3)：281-287,7.DOI:10.3969/j.issn.1003-7985.2018.03.001
认知无线网络中基于加权选择融合的协作频谱预测策略
A weighted selection combining scheme for cooperative spectrum prediction in cognitive radio networks
摘要
Abstract
A weighted selection combining (WSC) scheme is proposed to improve prediction accuracy for cooperative spectrum prediction in cognitive radio networks by exploiting spatial diversity.First,a genetic algorithm-based neural network (GANN) is designed to perform spectrum prediction in consideration of both the characteristics of the primary users (PU) and the effect of fading.Then,a fusion selection method based on the iterative self-organizing data analysis (ISODATA) algorithm is designed to select the best local predictors for combination.Additionally,a reliability-based weighted combination rule is proposed to make an accurate decision based on local prediction results considering the diversity of the predictors.Finally,a Gaussian approximation approach is employed to study the performance of the proposed WSC scheme,and the expressions of the global prediction precision and throughput enhancement are derived.Simulation results reveal that the proposed WSC scheme outperforms the other cooperative spectrum prediction schemes in terms of prediction accuracy,and can achieve significant throughput gain for cognitive radio networks.关键词
认知无线网络/协作频谱预测/基于遗传算法的神经网络/迭代自组织数据分析算法/加权选择融合Key words
cognitive radio network/cooperative spectrum prediction/genetic algorithm-based neural network/iterative self-organizing data analysis algorithm/weighted selection combining分类
信息技术与安全科学引用本文复制引用
李茜,宋铁成,章跃跃,陈国骏,胡静..认知无线网络中基于加权选择融合的协作频谱预测策略[J].东南大学学报（英文版）,2018,34(3):281-287,7.基金项目
The National Natural Science Foundation of China (No.61771126,61372104),the Science and Technology Project of State Grid Corporation of China (No.SGRIXTKJ[2015] 349). （No.61771126,61372104）
