基于可信度的节点选择算法

为了解决提高检测概率与减少网络开销间的矛盾,基于数据优化融合理论,提出了基于可信度的能量融合协同感知算法（EFCS算法）及节点选择算法。通过自适应迭代算法估计出各认知用户的感知可信度,并推导出了算法检测性能与协同用户数及感知可信度间的确定关系。算法能够在达到检测性能指标的前提下,尽可能多地删除冗余协同感知用户。仿真证明,节点选择算法在保证较高的检测概率的同时极大的节省了网络开销。

Node selection algorithm based on credibility

In order to solve the problem in improving the detect ion pro babil ity and reducing netw o rk spending , ener gy fusio n cooperative sensing algor ithm( EFCS Algo rithm) and node selection alg orithm w ere presented based o n the opt imal data fusion r ule. Adapt ive iterat ive alg orithm w as used to est imate the sensing cr edibilit ies o f all cog nit ive users. The relat ion among detect io n performance, the number of co gnit ive users and detect ion credibilit ies w er e deduced. T he node selet ion alg orithm can delete redundant co operativ e user s as many as po ssible w hile achiev ing the detect io n performance tar get . T he computer simulation show s that no de select ion algorithm can sav e netw or k spending largely and achieve hig h detection probability .