A low-complexity tree search detection algorithm for superposition modulation
A low-complexity tree search detection algorithm for superposition modulation
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DOI：
10.1109/istc.2012.6325216
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发表时间：
2012-10
期刊：
影响因子：
--
通讯作者：
D. Hao;P. Hoeher
中科院分区：
文献类型：
--
作者：
D. Hao;P. Hoeher
提出了一种新的叠加调制软输出检测算法。在未知层上使用高斯近似的顺序树搜索方法（TS-GA），可以识别最重要的符号并用于近似边缘后验概率。该检测器具有低的和固定的计算复杂度。仿真结果表明，最佳后验概率（APP）的性能可以接近少量的符号候选。
We present a novel soft-output detection algorithm for superposition modulation. Using a sequential tree search approach with Gaussian approximation (TS-GA) on the unknown layers, the most significant symbols can be identified and used to approximate the marginal posterior probabilities. The detector has low and fixed computational complexity. Simulation results demonstrate that the optimal a posteriori probability (APP) performance can be approached with a small number of symbol candidates.