In a practical compact massive multiple-input multiple-output (MIMO) transmitter array, each antenna or subarray is connected to an independent power amplifier (PA) with a modest power capacity in order to avoid the challenging demand of high-power capacity of a single PA for the whole array and to facilitate the power dissipation of the transmitter array. In this case, there is simply not enough space for an isolator between the antenna and the PA. As a result, the array mutual coupling changes the load impedances of the PAs and thus further increases the MIMO transmitter’s nonlinearity. In this work, the decoupling effect on the transmitter array’s linearity is investigated experimentally by using an array prototype with PAs. The mutual coupling of the array can be effectively suppressed using a hybrid decoupling structure. Two continuous-wave (CW) signals at different frequencies are injected into the PAs, and the output signal of each PA is measured via a coupler. The measured results show that with effective mutual coupling reduction, the PA interference is greatly suppressed by up to 16 db and the amplitude of the desired signal is enhanced by up to 10 db.
An adaptive sampling and optimized extrapolation scheme for spherical near-field antenna testing is proposed. The method relies on the partition clustering classification algorithm and Voronoi classification to divide a small amount of initial data into subclasses and cells. The sampling density and rates of variation between adjacent sampling points are used as an overall metric function to evaluate the sampling dynamics at each location. Appropriate interpolation is performed in the highly dynamic region to increase the effective data in the near-field samples. The Gerchberg-Papoulis algorithm extrapolates the unnecessary interpolation region to improve the near-field sampling accuracy. This method uses a small amount of initial near-field sampled data for near-far field conversion to achieve the same precision as uniform oversampling. The feasibility and stability of the algorithm are proved from the actual measurement results.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.