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197732 https://hdl.handle.net/2286/R.2.N.197732 http://rightsstatements.org/vocab/InC/1.0/ All Rights Reserved 2024 150 pages Doctoral Dissertation Academic theses Text eng Venkataramani, Adarsh Akkshai Bliss, Daniel W Alkhateeb, Ahmed Dasarathy, Gautam Michelusi, Nicolò Arizona State University Partial requirement for: Ph.D., Arizona State University, 2024 Field of study: Electrical Engineering Power amplifiers (PA) are often operated near saturation to meet the demands of both current and future wireless standards, including 4G, 5G NR, LTE, WCDMA, future 6G, and WiFi 7, leading to non-linear behavior either intentionally or unintentionally. The intentional use of high peak-to-average power ratio (PAPR) modulation schemes in these systems enables higher data rates, and reduced communication latency, but requires digital pre-distortion (DPD) to maintain high linearity and power efficiency. Conversely, in applications such as in-band full-duplex (IBFD) communication, amplifiers may unintentionally saturate due to strong self-interference (SI) between transmit and receive antennas. This saturation necessitates the use of digital SI cancellers, which regenerate the SI in order to recover the signal of interest. Both scenarios require accurate and low-complexity estimation and equalization of the PA channel to maintain linearity and power efficiency. Existing methods equalize using a large number of channel coefficients, posing challenges for low-latency applications with size, weight, power, and cost (SWaP-C) constraints. This dissertation addresses these challenges by proposing a novel two-box channel estimation and DPD architectures that uses basis functions inspired by amplifier physics. The proposed architecture is both theoretically studied and practically demonstrated using Ettus SDR and is at least ten times faster compared to the baseline in-direct learning architecture (ILA) DPD. Additionally, this dissertation addresses the challenge of capturing amplifier data cost-effectively by establishing the use of commercial-off-the-shelf (COTS) SDRs as measurement devices, along with design of novel calibration techniques. Traditional methods are often expensive, inflexible, and typically conducted under laboratory conditions with static waveforms and channels that are unrepresentative of real-world scenarios. The proposed calibration techniques minimize SDR system noise while accurately capturing the amplifier channel behavior. Theoretical and practical aspects of time, frequency, and phase alignment for high-quality data capture are investigated and demonstrated using Ettus N320 SDRs. The calibrated measurements are also used to demonstrate DPD using SDRs. Finally, the dissertation demonstrates IBFD by utilizing the proposed two-box channel architecture and SDR measurement setup in S-band. The combined techniques achieve performance comparable to baseline Hammerstein cancellers but with significantly reduced time complexity. Electrical Engineering Calibration digital pre-distortion in-band full-duplex nonlinear basis functions nonlinear model software defined radios Physically Inspired Digital Pre-Distortion and In-Band Full-Duplex Cancellation with Software-Defined Radios