2 research outputs found

    Digital Background Self-Calibration Technique for Compensating Transition Offsets in Reference-less Flash ADCs

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    This Dissertation focusses on proving that background calibration using adaptive algorithms are low-cost, stable and effective methods for obtaining high accuracy in flash A/D converters. An integrated reference-less 3-bit flash ADC circuit has been successfully designed and taped out in UMC 180 nm CMOS technology in order to prove the efficiency of our proposed background calibration. References for ADC transitions have been virtually implemented built-in in the comparators dynamic-latch topology by a controlled mismatch added to each comparator input front-end. An external very simple DAC block (calibration bank) allows control the quantity of mismatch added in each comparator front-end and, therefore, compensate the offset of its effective transition with respect to the nominal value. In order to assist to the estimation of the offset of the prototype comparators, an auxiliary A/D converter with higher resolution and lower conversion speed than the flash ADC is used: a 6-bit capacitive-DAC SAR type. Special care in synchronization of analogue sampling instant in both ADCs has been taken into account. In this thesis, a criterion to identify the optimum parameters of the flash ADC design with adaptive background calibration has been set. With this criterion, the best choice for dynamic latch architecture, calibration bank resolution and flash ADC resolution are selected. The performance of the calibration algorithm have been tested, providing great programmability to the digital processor that implements the algorithm, allowing to choose the algorithm limits, accuracy and quantization errors in the arithmetic. Further, systematic controlled offset can be forced in the comparators of the flash ADC in order to have a more exhaustive test of calibration

    Reconfigurable Receiver Front-Ends for Advanced Telecommunication Technologies

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    The exponential growth of converging technologies, including augmented reality, autonomous vehicles, machine-to-machine and machine-to-human interactions, biomedical and environmental sensory systems, and artificial intelligence, is driving the need for robust infrastructural systems capable of handling vast data volumes between end users and service providers. This demand has prompted a significant evolution in wireless communication, with 5G and subsequent generations requiring exponentially improved spectral and energy efficiency compared to their predecessors. Achieving this entails intricate strategies such as advanced digital modulations, broader channel bandwidths, complex spectrum sharing, and carrier aggregation scenarios. A particularly challenging aspect arises in the form of non-contiguous aggregation of up to six carrier components across the frequency range 1 (FR1). This necessitates receiver front-ends to effectively reject out-of-band (OOB) interferences while maintaining high-performance in-band (IB) operation. Reconfigurability becomes pivotal in such dynamic environments, where frequency resource allocation, signal strength, and interference levels continuously change. Software-defined radios (SDRs) and cognitive radios (CRs) emerge as solutions, with direct RF-sampling receivers offering a suitable architecture in which the frequency translation is entirely performed in digital domain to avoid analog mixing issues. Moreover, direct RF- sampling receivers facilitate spectrum observation, which is crucial to identify free zones, and detect interferences. Acoustic and distributed filters offer impressive dynamic range and sharp roll off characteristics, but their bulkiness and lack of electronic adjustment capabilities limit their practicality. Active filters, on the other hand, present opportunities for integration in advanced CMOS technology, addressing size constraints and providing versatile programmability. However, concerns about power consumption, noise generation, and linearity in active filters require careful consideration.This thesis primarily focuses on the design and implementation of a low-voltage, low-power RFFE tailored for direct sampling receivers in 5G FR1 applications. The RFFE consists of a balun low-noise amplifier (LNA), a Q-enhanced filter, and a programmable gain amplifier (PGA). The balun-LNA employs noise cancellation, current reuse, and gm boosting for wideband gain and input impedance matching. Leveraging FD-SOI technology allows for programmable gain and linearity via body biasing. The LNA's operational state ranges between high-performance and high-tolerance modes, which are apt for sensitivityand blocking tests, respectively. The Q-enhanced filter adopts noise-cancelling, current-reuse, and programmable Gm-cells to realize a fourth-order response using two resonators. The fourth-order filter response is achieved by subtracting the individual response of these resonators. Compared to cascaded and magnetically coupled fourth-order filters, this technique maintains the large dynamic range of second-order resonators. Fabricated in 22-nm FD-SOI technology, the RFFE achieves 1%-40% fractional bandwidth (FBW) adjustability from 1.7 GHz to 6.4 GHz, 4.6 dB noise figure (NF) and an OOB third-order intermodulation intercept point (IIP3) of 22 dBm. Furthermore, concerning the implementation uncertainties and potential variations of temperature and supply voltage, design margins have been considered and a hybrid calibration scheme is introduced. A combination of on-chip and off-chip calibration based on noise response is employed to effectively adjust the quality factors, Gm-cells, and resonance frequencies, ensuring desired bandpass response. To optimize and accelerate the calibration process, a reinforcement learning (RL) agent is used.Anticipating future trends, the concept of the Q-enhanced filter extends to a multiple-mode filter for 6G upper mid-band applications. Covering the frequency range from 8 to 20 GHz, this RFFE can be configured as a fourth-order dual-band filter, two bandpass filters (BPFs) with an OOB notch, or a BPF with an IB notch. In cognitive radios, the filter鈥檚 transmission zeros can be positioned with respect to the carrier frequencies of interfering signals to yield over 50 dB blocker rejection
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