Research on Differential Unitary Space-Time Coding Techniques in MIMO Wireless Communication Systems

Differential Unitary Space-Time Coding (DUSTC) represents a critical research area in MIMO wireless communication systems, primarily addressing the dependency of traditional space-time coding on Channel State Information (CSI). This master's thesis from Xidian University provides an in-depth exploration of the design principles and implementation methodologies of this technology, offering both theoretical foundations and practical solutions for reliable transmission in CSI-free scenarios.

The thesis systematically compares the performance boundaries of various space-time coding techniques, with particular emphasis on analyzing the advantages of differential unitary space-time coding under unknown channel conditions. The technology constructs codewords through differential operations of unitary matrices, enabling the receiver to perform decoding without real-time channel estimation, thereby significantly reducing system overhead. The implementation typically involves matrix multiplication operations and constellation mapping algorithms in codebook generation.

In the encoding/decoding scheme section, the research proposes optimized designs for differential unitary space-time modulation, including improvements in codebook construction and Maximum Likelihood (ML) detection algorithms. The ML detector implementation often employs distance metric calculations and search algorithms to minimize decoding errors. Simulation experiments validate the technology's robustness in Rayleigh fading channels through performance indicators such as Bit Error Rate (BER) curves and spectral efficiency, providing quantitative basis for practical deployment. The simulation code typically involves channel modeling, noise generation, and iterative decoding processes.

This research holds significant reference value for designing low-complexity, high-reliability transmission schemes in 5G and future communication systems, particularly in scenarios where channel estimation is challenging or impractical.