Fast and Efficient Calibration for Phased Arrays and Beamforming Circuits using Novel Constellation Characterization Method and Channel Transformation Technique

Abstract

Traditional phased array calibration methods, like exhaustive search, are time-consuming. This thesis proposes a novel, efficient technique that significantly reduces calibration time without sacrificing performance.

The proposed approach utilizes a constellation characterization method. It extracts and describes element responses using a set of mapping functions based on a strategically chosen data subset. A custom solver then generates control codes for desired beam patterns. For robustness, a closed-loop calibration routine is introduced to verify the solutions. Additionally, a taper awareness scheme is incorporated to optimize the output power by accounting for element variations and the desired tapering profile. The proposed method demonstrates significant speed-up compared to the exhaustive search method. On two beamforming integrated circuits (BFICs) and two test arrays, it achieves improvements of up to 1100 times while maintaining performance.

Furthermore, a channel transformation technique is proposed to leverage similarities between array elements. This technique reduces measurements by transferring mapping functions between array elements, avoiding full characterization for each element. A sequencing technique is also introduced to optimize the transformation route, maximizing success rates and further minimizing measurements. Experimental validation shows significant reductions in addition to the savings achieved via the proposed characterization method. Compared to the exhaustive search method, reductions of up to 3000 times are achieved.

This thesis presents significant advancements to phased array calibration, paving the way for efficient and scalable solutions in future high-resolution massive multiple input and multiple output (MIMO) systems.