Komal Punia, Emy Mariam George, K. Vinoth Babu, G. Ramachandra Reddy
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引用次数: 3
摘要
空间复用(SM) MIMO系统可以实现高数据速率传输。接收端的空间解复用是一项困难的任务。因此,一些研究工作已经发展为解复用和解码。本文实现了零强迫(Zero-Forcing, ZF)、最小均方误差(Minimum Mean Squared Error, MMSE)和最大似然(Maximum Likelihood, ML)三种信号检测方法。在零强迫方法中,噪声增强是一个问题。实现ZF和MMSE的复杂性要低得多,但它们的性能明显不如ML检测。许多活跃的研究人员都在开发基于机器学习检测标准的信号检测方法,同时仍然旨在以低复杂度实现接近最优的性能。针对二值相移键控(BPSK)、正交相移键控(QPSK)和16正交调幅(QAM)三种数字调制方案,对三种方法进行了比较研究。仿真结果还表明,与ZF和MMSE检测方法相比,ML具有更好的性能。
Signal detection for Spatially Multiplexed multi input multi output (MIMO) systems
High-data-rate transmission can be achieved by Spatially Multiplexed (SM) MIMO systems. Spatial demultiplexing at the receiver end is a difficult task. Thus, several research works has been developed for demultiplexing and decoding. In this paper three signal detection methods namely Zero-Forcing (ZF), Minimum Mean Squared Error (MMSE) and Maximum Likelihood (ML) are implemented. In Zero-Forcing method, noise enhancement is the problem. The complexity of implementing ZF and MMSE is much low but their performance is remarkably inferior to ML detection. Many active researchers are done to develop the signal detection methods based on the ML detection criterion while still aimed to achieve a near-optimal performance with low complexity. The comparative study of three methods is done in relevance to three digital modulation schemes namely Binary Phase Shift Keying (BPSK), Quadrature Phase Shift Keying (QPSK) and 16-Quadrature Amplitude Modulation (QAM). Simulation results also state that ML gives better performance as compared to ZF and MMSE detection methods.