低复杂度空间调制MPSK信号的最优检测
发布时间:2018-08-06 21:23
【摘要】:针对MQAM信号,已有低复杂度的最优检测算法,但是针对MPSK信号还没有类似的最优检测算法发表,因此从二维矢量量化的ML解调角度出发,利用MPSK星座图的特性,给出了与调制符号阶数无关的ML简化算法,避免了ML联合检测算法中对调制符号空间的搜索,极大地降低了算法复杂度。新算法不仅与ML最优检测算法具有完全相同的性能,而且具有较低的复杂度,有较好的理论和实际意义。该算法在天线技术和绿色通信技术中有较好的实际应用意义。
[Abstract]:There are low complexity optimal detection algorithms for MQAM signals, but no similar optimal detection algorithms have been published for MPSK signals. Therefore, from the point of view of the ML demodulation of two-dimensional vector quantization, the characteristics of MPSK constellation diagram are utilized. A simplified ML algorithm which is independent of the order of modulation symbols is presented, which avoids the search of modulation symbol space in the ML joint detection algorithm and greatly reduces the complexity of the algorithm. The new algorithm not only has the same performance as the ML optimal detection algorithm, but also has lower complexity and has good theoretical and practical significance. The algorithm has good practical significance in antenna technology and green communication technology.
【作者单位】: 大连理工大学信息与通信工程学院;
【分类号】:TN911.3
[Abstract]:There are low complexity optimal detection algorithms for MQAM signals, but no similar optimal detection algorithms have been published for MPSK signals. Therefore, from the point of view of the ML demodulation of two-dimensional vector quantization, the characteristics of MPSK constellation diagram are utilized. A simplified ML algorithm which is independent of the order of modulation symbols is presented, which avoids the search of modulation symbol space in the ML joint detection algorithm and greatly reduces the complexity of the algorithm. The new algorithm not only has the same performance as the ML optimal detection algorithm, but also has lower complexity and has good theoretical and practical significance. The algorithm has good practical significance in antenna technology and green communication technology.
【作者单位】: 大连理工大学信息与通信工程学院;
【分类号】:TN911.3
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