I will present the research and results from my PhD thesis, " Channel Characterization and Array Diagnosis for 5G and Beyond Systems." In fifth-generation (5G) and beyond communication systems, high frequencies and enhanced multiple-input multiple-output (MIMO) technologies will be the key enablers for unlocking new applications and use cases.

The trend of adopting higher frequencies, broader bandwidth, and an increased number of antenna elements in new radio systems is driving the demand for dedicated hardware facilities. This poses challenges across various techniques. This presentation delves into two main research topics i.e., channel characterization and array diagnosis. Channel characterization aims to investigate the wireless signal propagation environment, while array diagnosis focuses on assessing the working status of antennas at the link ends. Both are crucial for ensuring the optimal performance of a wireless system during deployment. The objective of this thesis is to achieve accurate channel characterization and array diagnosis with accessible and cost-effective setups, leveraging signal-processing techniques.

For channel characterization in high-frequency bands, the focus is on channel sounding schemes and channel parameter estimation algorithms for obtaining the channel temporal-spatial profiles. A directional antenna based virtual antenna array sounding scheme and an associated beamforming algorithm are proposed for mmWave channel characterization. High SNR as well as high angular resolution can be achieved with any directional antenna used in the measurements while simple and cost-effective measurement setups are required. The versatility of the proposed directional antenna based virtual array framework has also been extended and implemented in antenna de-embedding and test zone validation for multi-probe anechoic chamber (MPAC) enabled performance testing of MIMO devices, respectively.

The array diagnosis methods for large-scale arrays with subarray-structured configurations are investigated in this thesis. The failed elements within a subarray are detected by tuning the phase of subarrays and solving linear equations in a compact and cost-effective setup with high measurement efficiency. In addition, an array diagnosis method that can detect the connecting faults is proposed for beamforming antenna arrays based on using the differential strategy and matrix inversion operations. In contrast with the conventional methods, the proposed method can be achieved with only a few spatial samples in typical indoor or production line scenarios with possible scattering in the testing environments.

The presentation will include an introduction to the challenges and background knowledge in the field of channel characterization and array diagnosis as well as the motivations, methods, and results of my research.