Linearizability Assessment of a 3.5 GHz 16-Chain Fully Digital MIMO Transmitter Under Wideband Modulated Signals

This paper investigates the linearizability of a custom-built 16 -chain fully digital MIMO transmitter system. The transmitter front-end consists of multistage, Class-AB power amplifiers (PAs) and a stacked patch antenna array. To assess the linearizability of the RF front end, an iterative learning control (ILC) solution is proposed to identify the predistorted signal that results in the desired modulated signal with the least distortion at the output. ILC is then applied to the 16 -chain transmitter front-end for orthogonal frequency-division multiplexing (OFDM) signals of 8 dB peak-to-average ratio (PAPR) and instantaneous modulation bandwidths of $60,80,100$, and 120 MHz. The experimental results show that the average root normalized mean square error (RNMSE) of all 16 chains can be reduced from values up to $28 \%$ to values below $2 \%$ across all 16 chains for all bandwidths, while the average adjacent channel power ratio (ACPR) is improved from -36 dB to $-54,-52,-51,-48 \mathrm{~dB}$ for $60,80,100$, and 120 MHz, respectively. The performance of pruned Volterra-based single-input single-output (SISO) and multiple-input single-output (MISO) digital predistortion (DPD) is compared against the ILC benchmark. Compared to the ILC benchmark, pruned-Volterra SISO and MIMO DPD exhibited significantly degraded performance. These results suggest that current DPD modeling approaches, potentially formulated based on smaller MIMO systems, need to be revisited to account for non-idealities impacting linearizability in larger-scale massive MIMO transmitters. The proposed linearizability assessment methodology can support the development of future massive MIMO RF front-end designs and DPD linearization techniques for improved system-level performance.