Browsing by Author "Chi, Taiyun"

Now showing 1 - 11 of 11
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    A 120-GHz Power Amplifier in 45-nm SiGe
    (2022-12-02) Morrison, James Allen; Chi, Taiyun
    As 5G cellular technologies are in the deployment stage and 6G technology is entering the research arena, the need for more bandwidth allocation has led to the drastic increase in frequency that has crossed the threshold into the sub-terahertz (sub-THz) region. This spectrum allows for larger bandwidths, but also brings challenges for implementation due to the physical phenomenon associated with these EM (electromagnetic) waves. One challenge is to efficiently provide high output power for antennas on a single chip or as part of a larger IC (Integrated Circuit) [1]. This work evaluates a promising new SiGe (Silicon-Germanium) fabrication process that addresses the power generation issue by utilizing an HBT (hetero-junction bipolar transistor) that is half the size of the previous generation, but still has an appreciable supply voltage and offers the use of topologies that allow the voltage swing to remain high despite its smaller size. The main contributions of this paper are as follows: (a) The design flow used to evaluate this new process, (b) A chip design that evaluates the performance of the HBT in a 2-stage common-base differential amplifier configuration.
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    A Millimeter-Wave Three-Way Doherty Power Amplifier for 5G NR OFDM
    (2023-03-31) Zhang, Xiaohan; Chi, Taiyun
    We present a mmWave three-way Doherty output network and its silicon implementation at 38 GHz for 5G NR OFDM. The proposed network synthesis methodology can realize close-to-ideal dual-peaking Doherty active load mod ulation, reduce the impedance transformation ratio at back-off, and directly absorb the device parasitic capacitance. Its design procedure and trade-offs are discussed in detail. A 38-GHz PA prototype is implemented in the GlobalFoundries 45-nm CMOS SOI process, achieving 13.7% / 11.0% PAE at the 9.5-dB / 11.5-dB back-off, which are among the highest compared to recently reported silicon PAs operating at 30 GHz and above. Tested under 1-CC and 2-CC 5G NR FR2 64-QAM OFDM signals in the Band n260, the PA demonstrates state-of-the-art average output power(11.3 dBm) and average efficiency (14.7%) with -25 dB EVM. The design robustness and reliability is further demonstrated through the testing of multiple samples and PA lifetime
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    A Systematic Approach to Designing Broadband Millimeter-Wave Low Noise Amplifiers
    (2022-12-02) Hu, yaolong hu; Chi, Taiyun
    There is a growing interest in wideband mmWave transceivers to simultaneously cover multiple mmWave 5G bands. These 5G bands centered at 26, 28, 39, and 41 GHz. Compared to narrowband designs, broadband 5G transceivers can enable a few unique application scenarios, such as inter-band carrier aggregation to increase the data throughput, global multi-standard coverage for international roaming, and agile frequency hopping. In addition to high-speed wireless communication, emerging wireless sensing applications, such as 3D mmWave imaging and radar, also favor broadband transceivers, since the range resolution is inversely proportional to BW. As the first stage of the receiver, LNA plays an important role in defining the receiver bandwidth. In my master thesis, our goal is to establish a systematic yet intuitive design methodology to extend mmWave LNA bandwidth. Since the LNA bandwidth is defined as the intersection of 3 dB gain bandwidth and -10 dB return loss bandwidth, so we will cover two circuit innovations in this thesis. First, we will go through how to synthesize dual-resonant input matching. And second, a broadband transformer-based output network synthesis methodology is presented. A 26-47-GHz LNA prototype is fabricated with GlobalFoundries 45RFSOI process and its measurement results are also included in this thesis.
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    Advanced Millimeter-wave Doherty Power Amplifier Architectures for 5G Communications and Beyond
    (2024-08-08) Zhang, Xiaohan; Chi, Taiyun
    Millimeter-wave (mmWave) wireless communication is moving to 5G and 6G to increase its data rate and channel capacity. In a wireless transmitter, power amplifier (PA) is widely considered to be the most critical building block, as it serves as the final stage and often dominates the overall transmitter efficiency and linearity. As a result, mmWave 5G and 6G require spectrum efficient modulation signals such as quadrature amplitude modulation (QAM), orthogonal frequency-division multiplexing (OFDM) together with carrier aggregation (CA) with a large peak-to-average power ratio (PAPR). Such high PAPR signals seldom operate at their peak power level. While a classic linear PA, such as a Class-AB PA, achieves its highest efficiency at the peak power, its average efficiency can drop significantly when handling these modulated signals with high PAPR. Therefore, it is necessary to develop PAs with efficiency enhancement techniques for back-off power while maintaining high linearity. Such advancements could significantly improve the average efficiency of PAs, especially when amplifying spectrum efficient modulated signals, making them better suited to meet the demands of modern wireless communication systems. Among various back-off efficiency enhancement techniques, Doherty PA architecture is one of the most popular approaches at mmWave frequency band due to its minimum digital computation overhead. Although significant research has been conducted on Doherty PA in the literature, it remains a challenge to design Doherty PAs with high power, high linearity, low loss, deep back-off efficiency enhancement, and over-GHz modulation bandwidth (BW). In this doctoral thesis, I will first give a brief introduction of PA design challenges at mmWave and some existing back-off efficiency enhancement techniques in chapter 1. Then, in chapter 2, I will present a review of the Doherty PA architecture, from its original invention to its modern CMOS implementations. I will also introduce a few uncommon interpretations of the Doherty architecture from different perspectives to facilitate a more intuitive understanding of its operation. Following this, in chapter 3-5, I will introduce three Doherty PA prototypes designed during my PhD study, aiming to address the power, efficiency, and bandwidth challenges for mmWave PAs. Finally, chapter 6 concludes this thesis and discusses some potential future research directions. Chapter 7 summarizes the publications and experiences of the author during the PhD.
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    Advances in non-invasive biosensing measures to monitor wound healing progression
    (Frontiers Media S.A., 2022) Short, Walker D.; Olutoye, Oluyinka O.; Padon, Benjamin W.; Parikh, Umang M.; Colchado, Daniel; Vangapandu, Hima; Shams, Shayan; Chi, Taiyun; Jung, Jangwook P.; Balaji, Swathi
    Impaired wound healing is a significant financial and medical burden. The synthesis and deposition of extracellular matrix (ECM) in a new wound is a dynamic process that is constantly changing and adapting to the biochemical and biomechanical signaling from the extracellular microenvironments of the wound. This drives either a regenerative or fibrotic and scar-forming healing outcome. Disruptions in ECM deposition, structure, and composition lead to impaired healing in diseased states, such as in diabetes. Valid measures of the principal determinants of successful ECM deposition and wound healing include lack of bacterial contamination, good tissue perfusion, and reduced mechanical injury and strain. These measures are used by wound-care providers to intervene upon the healing wound to steer healing toward a more functional phenotype with improved structural integrity and healing outcomes and to prevent adverse wound developments. In this review, we discuss bioengineering advances in 1) non-invasive detection of biologic and physiologic factors of the healing wound, 2) visualizing and modeling the ECM, and 3) computational tools that efficiently evaluate the complex data acquired from the wounds based on basic science, preclinical, translational and clinical studies, that would allow us to prognosticate healing outcomes and intervene effectively. We focus on bioelectronics and biologic interfaces of the sensors and actuators for real time biosensing and actuation of the tissues. We also discuss high-resolution, advanced imaging techniques, which go beyond traditional confocal and fluorescence microscopy to visualize microscopic details of the composition of the wound matrix, linearity of collagen, and live tracking of components within the wound microenvironment. Computational modeling of the wound matrix, including partial differential equation datasets as well as machine learning models that can serve as powerful tools for physicians to guide their decision-making process are discussed.
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    EMvelop stimulation: minimally invasive deep brain stimulation using temporally interfering electromagnetic waves
    (IOP Publishing, 2022) Ahsan, Fatima; Chi, Taiyun; Cho, Raymond; Sheth, Sameer A.; Goodman, Wayne; Aazhang, Behnaam
    Objective. Recently, the temporal interference stimulation (TIS) technique for focal noninvasive deep brain stimulation (DBS) was reported. However, subsequent computational modeling studies on the human brain have shown that while TIS achieves higher focality of electric fields than state-of-the-art methods, further work is needed to improve the stimulation strength. Here, we investigate the idea of EMvelop stimulation, a minimally invasive DBS setup using temporally interfering gigahertz (GHz) electromagnetic (EM) waves. At GHz frequencies, we can create antenna arrays at the scale of a few centimeters or less that can be endocranially implanted to enable longitudinal stimulation and circumvent signal attenuation due to the scalp and skull. Furthermore, owing to the small wavelength of GHz EM waves, we can optimize both amplitudes and phases of the EM waves to achieve high intensity and focal stimulation at targeted regions within the safety limit for exposure to EM waves. Approach. We develop a simulation framework investigating the propagation of GHz EM waves generated by line current antenna elements and the corresponding heat generated in the brain tissue. We propose two optimization flows to identify antenna current amplitudes and phases for either maximal intensity or maximal focality transmission of the interfering electric fields with EM waves safety constraint. Main results. A representative result of our study is that with two endocranially implanted arrays of size × each, we can achieve an intensity of 12 V m−1 with a focality of at a target deep in the brain tissue. Significance. In this proof-of-principle study, we show that the idea of EMvelop stimulation merits further investigation as it can be a minimally invasive way of stimulating deep brain targets and offers benefits not shared by prior methodologies of electrical or magnetic stimulation.
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    Experimental Evaluation of AoA Estimation for UAV to Massive MIMO
    (2023-04-19) Rice, Tarence; Knightly, Edward; Sabharwal, Ashutosh; Chi, Taiyun
    Massive MIMO (multiple-input, multiple-output) base stations are widely used for wireless networks to deploy multiple antennas, increasing their quality, throughput, and radio link capacity. Unmanned aerial vehicles (UAV) are prevalent due to their low cost and ease of use. Unmanned aerial vehicles (UAV) are prevalent due to their low cost and ease of use, allowing for multiple use cases that provide telemetry information to civilian, commercial, and military applications. In particular, we implement a suite of Angle of Arrival (AoA) estimation algorithms exploring their performance for UAV communication networks. From the evaluation of the five AoA estimations, Beamscan offers a spatial, spectral response that enables us to analyze both secondary propagation paths and the most likely AoA, providing us with a complete picture of the environment. We discovered with convergence time that when under-sampled, the AoA estimator detects the multi-path with a higher normalized power, impacting the AoA estimate result. We estimated azimuth AoA via horizontal subarrays and its effects on the multi-path AoA estimates for hovering drones. We discovered the effects of Rice football stadium seats as we decreased the number of antennas. We find that when evaluating hovering drones' azimuth and elevation AoA estimation, elevation estimation yields a median error of 13.8\degree higher error than azimuth for the 5x5 antenna scenario. Evaluated was the performance of the 2-D Beamscan spatial spectrum estimator. It provides higher accuracy between the two different channels of azimuth and elevation. This work will inform system designers on specifications from AoA estimations when designing a Massive MIMO to drone network.
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    Integrated Microheater Array for Localized Heating of Magnetic Nanoparticles
    (2022-12-01) Fan, Yingying; Chi, Taiyun
    There is a growing interest in leveraging microwave technology for biomedical applications including non-invasive imaging, respiratory and heartbeat radar detection, and spectroscopy. While most of these applications are sensing-oriented, my research focuses on microwave actuation, particularly heat generation. It enables a novel non-invasive approach for applications such as tumor ablation and neural stimulations. A variety of techniques have been employed to raise the local temperature for these emerging biomedical applications including dielectric heating and ohmic heating. However, they suffer from poor material specificity and undesired damage to the surrounding tissues. Our key idea is to explore magnetic heating induced by magnetic nanoparticles (MNP) which offers superior heating specificity. We proposed and demonstrated a miniaturized microheater array utilizing ferromagnetic resonance of the MNP at GHz to enable localized yet accurate temperature manipulation in living cells and tissues.
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    Lightweight Physical-Layer Security Primitives for 5G and Beyond
    (2022-12-02) Zhou, Qiang; Chi, Taiyun
    5G communications bring revolutionary services beyond 4G, namely enhanced Mobile Broadband (eMBB), massive Machine Type Communications (mMTC), and Ultra-Reliable Low-Latency Communications (URLLC), opening up a plethora of new applications and capabilities in defense and commercial spaces. However, the complexity and heterogeneity of 5G networks and applications also bring unprecedented security challenges that demand innovative solutions. We propose to leverage unique 5G physical-layer technologies to bring an extra layer of security protection that is orthogonal to conventional cryptography-based wireless security. More specifically, we create and demonstrate low-overhead and 5G-compliant hardware to prevent eavesdropping attacks against eMBB links with antenna subset modulation scheme and to achieve lightweight identification for mMTC devices utilizing RF fingerprinting from spectral regrowth.
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    Multifeed Lens Antennas for Next-G Communications and Sensing
    (2024-04-22) Wang, Hang; Chi, Taiyun; Sabharwal, Ashutosh
    As we edge towards higher frequencies for future communication needs, the significance of enhanced Effective Isotropic Radiated Power (EIRP) becomes paramount to counter the escalating path loss. Future 6G communications at millimeter wave frequencies typically require an EIRP of 75dBm. Consequently, minimizing DC power consumption at this high EIRP level becomes a critical issue. Moreover, constraints posted by narrow bandwidth and unpredictable user movement necessitate fast beam switching time and beam-steering decision speed. Relative to conventional lens antenna and phased array methodologies at millimeter wave frequencies, our proposed innovation offers superior DC power to EIRP efficiency, simultaneously maintaining or enhancing the achievable EIRP. This thesis initially introduces foundational knowledge concerning single lens antenna. Subsequently, a novel generalized lens array topology is developed, employing ray-tracing calculations and HFSS simulations. This design ensures high gain, broad beam steering capabilities, swift beam switching, and elevated data rates, all while ensuring maximal DC to EIRP efficiency, reduced dimensions, and compatibility with Multiple Input Multiple Output (MIMO) systems. After that, the thesis delves into the experimental efforts to overcome the hurdles in fully demonstrating a D-band lens array. The characterization of Mt77 material is undertaken to assess the inherent routing loss. A 3D antenna radiation pattern testing system is established, confirming the gain enhancement of a single lens antenna. Furthermore, tailored PCB boards featuring Flip-Chip Buffer (BF) chips were developed and assessed to elucidate the principal flip-chip losses within our packaging approach.
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    Review of wearable technologies and machine learning methodologies for systematic detection of mild traumatic brain injuries
    (IOP Publishing, 2021) Schmid, William; Fan, Yingying; Chi, Taiyun; Golanov, Eugene; Regnier-Golanov, Angelique S.; Austerman, Ryan J.; Podell, Kenneth; Cherukuri, Paul; Bentley, Timothy; Steele, Christopher T.; Schodrof, Sarah; Aazhang, Behnaam; Britz, Gavin W.; Neuroengineering Initiative (NEI)
    Mild traumatic brain injuries (mTBIs) are the most common type of brain injury. Timely diagnosis of mTBI is crucial in making ‘go/no-go’ decision in order to prevent repeated injury, avoid strenuous activities which may prolong recovery, and assure capabilities of high-level performance of the subject. If undiagnosed, mTBI may lead to various short- and long-term abnormalities, which include, but are not limited to impaired cognitive function, fatigue, depression, irritability, and headaches. Existing screening and diagnostic tools to detect acute and early-stage mTBIs have insufficient sensitivity and specificity. This results in uncertainty in clinical decision-making regarding diagnosis and returning to activity or requiring further medical treatment. Therefore, it is important to identify relevant physiological biomarkers that can be integrated into a mutually complementary set and provide a combination of data modalities for improved on-site diagnostic sensitivity of mTBI. In recent years, the processing power, signal fidelity, and the number of recording channels and modalities of wearable healthcare devices have improved tremendously and generated an enormous amount of data. During the same period, there have been incredible advances in machine learning tools and data processing methodologies. These achievements are enabling clinicians and engineers to develop and implement multiparametric high-precision diagnostic tools for mTBI. In this review, we first assess clinical challenges in the diagnosis of acute mTBI, and then consider recording modalities and hardware implementation of various sensing technologies used to assess physiological biomarkers that may be related to mTBI. Finally, we discuss the state of the art in machine learning-based detection of mTBI and consider how a more diverse list of quantitative physiological biomarker features may improve current data-driven approaches in providing mTBI patients timely diagnosis and treatment.