An Efficient Probe Weighting Method for MIMO OTA Testing

In the research of over-the-air (OTA) performance testing, the multi-probe anechoic chamber (MPAC) method is crucial, which reconstructs the target channel by controlling the position and power weight of the probes. Investigating and optimizing the combination of probes and their power weights constitutes an indispensable step in the testing process of MPAC systems. Under the premise of a selected probe combination, most existing related studies typically employ a convex optimization toolbox called CVX to solve for the probe weights. However, with the trend of massive and large-scale wireless communication, CVX may not be the best option for large-scale optimization due to memory and speed limitations. This paper proposes a decomposed and alternating updated augmented Lagrangian multiplier (DAU-ALM) method for probe weighting, which decomposes the target problem and optimizes it. Besides, a dynamic adjustment penalty parameter mechanism is used to accelerate the convergence speed. Simulation results show that the proposed algorithm improves the computational efficiency of probe weighting with the same accuracy as CVX.