MIMO Signal Detection

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Resource Overview

Application Context: The effective utilization of MIMO technology relies on rapid and accurate signal detection techniques at the receiver end, requiring detection algorithms with both low complexity and high performance. Providing MATLAB implementations of signal detection algorithms is essential. Key Technologies: Multiple detection algorithms are implemented including Zero-Forcing (ZF), Minimum Mean Square Error (MMSE), ordered MMSE detection, corresponding MMSE soft detection, Sphere Decoding (SD), soft/hard QRD-MLD algorithms, and Maximum Likelihood Detection (MLD). These algorithms enable performance comparison under 256QAM high-order modulation, providing valuable references for engineering implementation.

Detailed Documentation

Application Context

The effective implementation of MIMO technology depends on fast and accurate signal detection techniques at the receiver side. To meet this requirement, detection algorithms must combine low computational complexity with high detection performance. Providing MATLAB implementations of signal detection algorithms is particularly valuable for engineering practitioners.

Key Technologies

Multiple detection algorithms are available for comparing signal detection performance under 256QAM high-order modulation, serving as important references for engineering implementation. These algorithms include Zero-Forcing (ZF) detection, Minimum Mean Square Error (MMSE) detection, ordered MMSE detection, corresponding MMSE soft detection, Sphere Decoding (SD), soft/hard QRD-MLD algorithms, and Maximum Likelihood Detection (MLD). The MATLAB implementations feature algorithm-specific optimizations, such as matrix inversion operations for ZF, noise variance considerations for MMSE, tree-search optimization for SD, and efficient QR decomposition implementations for QRD-MLD.

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