RF BiST för att detektera IQ-imbalanser avseende överhörningseffekter för avancerade antennsystem

Abstract: Internet of Things (IoT) is a network constituted by uniquely identifiable commodity objects or devices equipped with some sensing system. To achieve high data rates required for IoT devices, a modern wireless communication system, known as Advanced Antenna Systems(AAS), leads to significant improvement, by increasing not only the data rate but also spectrum efficiency and the channel capacity. A certain type of analog signal distortions, i.e. the in-phase (I) and quadrature-phase (Q) imbalances can severely damage the performance of the RF transceivers. The IQ imbalances refer to gain mismatch, phase mismatch, DC offset in the I and Q branches. IQ Imbalances affect the efficiency and performance of the Radio Frequency (RF) Transceivers, present in the AAS. Hence a need for test architectures arises. In this thesis an existing BiST circuitry for one transmission chain is chosen, implemented and further extended to multiple transmission chains (up to 4). As the number of transmission chains increase, mutual coupling phenomenon leading to crosstalk effects are to be considered. Along with designed test signal, this BiST circuitry enables us to detect the transmitter impairment with low computational complexity. In this thesis work 3 different cases have been implemented which are – one antenna setup, 2x1 antenna array setup and 4x1 antenna array setup. The first case has one transmission chain. We have utilized the Generalized Memory Polynomial (GMP) power amplifier model, and the BiST circuitry, called as Self-Mixing Envelope Detector method is implemented in Matlab. In the case of 2x1 Antenna array, implementation is partly carried out using the RF equipment for the signal generation stage, power amplifier stage, crosstalk effects (mutual coupling), and BiST circuitry stage, which was previously implemented in Matlab is utilized. The 4x1 antenna array setup, just like the one antenna setup, is entirely implemented in Matlab. Additionally, the coupling coefficients are extracted to model the mutual coupling phenomenon. In the one antenna setup & the 4x1 antenna array setup, the RMSE% of IQ imbalances are calculated. In the 2x1 antenna array setup, gain mismatch, phase mismatch, both the DC offsets are measured up to a certain accuracy. The results obtained in all the three cases advocate that this method, successfully detect the IQ impairments present in the advanced antenna system, even when the crosstalk effects are considered.