Design, Testing, and Analysis of Advanced Massive MIMO Transmitters

Abstract

The evolution of Fifth Generation (5G) wireless systems is driven by the need for higher data rates, lower latency, and improved coverage. Massive Multiple Input, Multiple Output (MIMO) transmitter front-ends have emerged as a key enabling technology, employing multiple parallel transmitter chains—each comprising Digital Signal Processing (DSP), Power Amplifiers (PAs), and antenna elements—to exploit spatial multiplexing and enable multi-user beamforming, at the cost of increased system complexity.

The PA is a critical component in each transmitter chain, as its efficiency dominates energy consumption and its output power determines coverage. However, PA performance is highly sensitive to load impedance. While isolators in 4G systems maintain a constant 50 Ω load, their use in massive MIMO arrays is impractical due to cost, size, bandwidth, and integration constraints. Consequently, antenna mismatches and mutual coupling introduce dynamic load variations that degrade PA and overall system performance, motivating a holistic system-level design approach.

The first objective of this thesis is to develop tools for system-level analysis of massive MIMO transmitters under realistic excitation. A multidisciplinary co-simulation frame- work integrating DSP, Radio Frequency (RF), and electromagnetic domains is proposed to capture signal processing, PA nonlinearities, and antenna coupling within a unified environment. Experimental validation using a four-channel fully digital MIMO transmit- ter demonstrates accurate prediction of system-level trends. A sixteen-channel testbed is further developed to validate design strategies and capture hardware-specific effects.

The second objective is to enable PA design under realistic system conditions. To mitigate the computational complexity of large-scale simulations, an emulation platform is developed that reproduces massive MIMO loading conditions using a single PA. This approach enables efficient characterization and optimization under dynamic impedance environments. Combined with the co-simulation framework, it supports PA design directly at the system level rather than under idealized 50 Ω assumptions.

The third objective is to investigate the impact of precoding on PA behavior. Con- ventional Digital Pre-Distortion (DPD) linearizes PAs using uncorrelated signals prior to precoding, implicitly assuming invariant load conditions. However, precoding alters signal correlation and power distribution, thereby modifying the load impedance seen by each PA in the presence of mutual coupling, which degrades linearization performance. To ad- dress this, an alternative architecture is explored in which precoding precedes linearization, enabling improved robustness and reduced DPD complexity under dynamic conditions.