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As the number of antenna elements increases in massive multiple-input multiple-output-based radios such as fifth generation mobile technology (5G), designing true multi-band base-station transmitter, with efficient physical size, power consumption and cost in emerging cellular frequency bands up to 10 GHz, is becoming a challenge. This demands a hard integration of radio components, particularly the radio's digital application-specific integrated circuits (ASIC) with high performance multi-band data converters. In this work, a novel radio frequency digital-to-analog converter (RF DAC) solution is presented, that is also capable of monolithic integration into today's digital ASIC due to its digital-in-nature architecture. A voltage-mode conversion method is used as output stage, and configurable mixing logic is employed in the data path to create a higher frequency lobe and utilize the output signal in the first or the second Nyquist zone. This 12-bit RF DAC is designed in a 22 nm FDSOI CMOS process, and shows excellent linearity performance for output frequencies up to 10 GHz, with no calibration and no trimming techniques. The achieved linearity performance is able to fulfill the high requirements of 5G base-station transmitters. Extensive Monte-Carlo analysis is performed to demonstrate the performance reliability over mismatch and process variation in the chosen technology.

Optimization problem formulation for semi-digital FIR digital-to-analog converter (SDFIR DAC) is investigated in this work. Magnitude and energy metrics with variable coefficient precision are defined for cascaded digital RD modulators, semi-digital FIR filter, and Sinc roll-off frequency response of the DAC. A set of analog metrics as hardware cost is also defined to be included in SDFIR DAC optimization problem formulation. It is shown in this work, that hardware cost of the SDFIR DAC, can be significantly reduced by introducing flexible coefficient precision while the SDFIR DAC is not over designed either. Different use-cases are selected to demonstrate the optimization problem formulations. A combination of magnitude metric, energy metric, coefficient precision and analog metrics are used in different use cases of optimization problem formulation and solved to find out the optimum set of analog FIR taps. A new method with introducing the variable coefficient precision in optimization procedure was proposed to avoid non-convex optimization problems. It was shown that up to 22% in the total number of unit elements of the SDFIR filter can be saved when targeting the analog metric as the optimization objective subject to magnitude constraint in pass-band and stop-band.