CAJ | 학술논문

通过研究初级用户的统计传输模式提出了一种联合频谱感知算法：初级用户的统计传输模式采用舍有两状态量的马尔科夫模型；每个二级用户通过对马尔科夫链的监测进行能量检测，并且经舍噪信遭将检测结果转发给融合中心；然后，融合中心通过使用新的渐进式最大后验估计算法恢复二级用户的判决。在上述过程中，先验概率对于最大后验估计至关重要，它是通过渐进地估计马尔代夫链的传递概率得到的。另外，采用多数数据融合和或逻辑数据融合规则．推导出了虚警概率和漏检概率的解析表达式。理论分析和仿真结果表明，所提出的算法能够提供可靠和有效的频谱感知。
통과연구초급용호적통계전수모식제출료일충연합빈보감지산법：초급용호적통계전수모식채용사유량상태량적마이과부모형；매개이급용호통과대마이과부련적감측진행능량검측，병차경사조신조장검측결과전발급융합중심；연후，융합중심통과사용신적점진식최대후험고계산법회복이급용호적판결。재상술과정중，선험개솔대우최대후험고계지관중요，타시통과점진지고계마이대부련적전체개솔득도적。령외，채용다수수거융합화혹라집수거융합규칙．추도출료허경개솔화루검개솔적해석표체식。이론분석화방진결과표명，소제출적산법능구제공가고화유효적빈보감지。
This paper developed a new cooperative spectrum sensing algorithm by exploiting the statistical properties of the PU＇s transmission pattern,which was modeled with a Markov chain with two states：busy （1） and idle （0）. Each SU performs energy detection based on an observation of the Markov chain,and the detection results are for- warded to a fusion center （FC） through a noisy channel,and the FC recovers the decisions of the SUs by using a new progressive maximum a posteriori （MAP） estimation algorithm,where a priori probability essential to the MAP de- tection is obtained by progressively estimating the transition probabilities of the Markov chain. Analytical expres- sions were derived for the probabilities of false alarm and missing detection, with both the majority data fusion rule and the OR data fusion rule. Both theoretical analysis and simulation results indicated that the proposed algorithm could provide reliable and efficient spectrum sensing over a large range of system configurations.