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机构地区:[1]东南大学移动通信国家重点实验室,南京210096
出 处:《东南大学学报(自然科学版)》2016年第5期912-916,共5页Journal of Southeast University:Natural Science Edition
基 金:国家自然科学基金资助项目(61571105;61501109;61223001);江苏省自然科学基金资助项目(BK20140646)
摘 要:为了减轻DCO-OFDM系统中因截断噪声对误码率性能的影响,研究了上、下限幅截断系统的检测算法优化问题.分析了ML算法在DCO-OFDM中不适用的原因,提出ML迭代算法和权重因子ML算法:ML迭代算法通过对残留限幅噪声的迭代估算更新原始估计序列,得到ML算法的析出信号;通过权重因子将限幅噪声高斯白化,使得最大似然估计检测算法满足最优线性估计条件,再通过迭代算法得出接收机析出信号.文中提出的2种算法虽然复杂度高,但相比于M L算法具有更好的链路误码率性能.To prevent the performance degradation of DC biased optical orthogonal frequency division multiplexing( DCO-OFDM) system caused by clipping distortion,the optimization of the detection algorithm in the double clipped system was studied. The considerations which are not applicable to the maximum likelihood( ML) algorithm in DCO-OFDMsystem were analyzed,and two improved iterative algorithms were proposed: 1 obtaining the precipitation signal of ML algorithm by updating the original estimate sequences on the iterative estimate of residual clipping noise; 2 whitening the clipping noise by weighted factor,makes the maximum likelihood estimation algorithm satisfy the condition of the best linear detection,and obtains the precipitation signal of the receiver by the iterative algorithm. Though the improved iterative algorithms have a high degree of complexity,compared with the ML algorithm,the system link error rate performance is improved.
关 键 词:可见光通信 光正交频分复用 迭代接收 最大似然检测
分 类 号:TN914[电子电信—通信与信息系统]
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