Adaptive Baseband Pro cessing and Configurable Hardware for Wireless Communication

The world of information is literally at one’s fingertips, allowing access to previously unimaginable amounts of data, thanks to advances in wireless communication. The growing demand for high speed data has necessitated theuse of wider bandwidths, and wireless technologies such as Multiple-InputMultiple-Output (MIMO) have been adopted to increase spectral efficiency.These advanced communication technologies require sophisticated signal processing, often leading to higher power consumption and reduced battery life.Therefore, increasing energy efficiency of baseband hardware for MIMO signal processing has become extremely vital. High Quality of Service (QoS)requirements invariably lead to a larger number of computations and a higherpower dissipation. However, recognizing the dynamic nature of the wirelesscommunication medium in which only some channel scenarios require complexsignal processing, and that not all situations call for high data rates, allowsthe use of an adaptive channel aware signal processing strategy to provide adesired QoS. Information such as interference conditions, coherence bandwidthand Signal to Noise Ratio (SNR) can be used to reduce algorithmic computations in favorable channels. Hardware circuits which run these algorithmsneed flexibility and easy reconfigurability to switch between multiple designsfor different parameters. These parameters can be used to tune the operations of different components in a receiver based on feedback from the digitalbaseband. This dissertation focuses on the optimization of digital basebandcircuitry of receivers which use feedback to trade power and performance. Aco-optimization approach, where designs are optimized starting from the algorithmic stage through the hardware architectural stage to the final circuitimplementation is adopted to realize energy efficient digital baseband hardwarefor mobile 4G devices. These concepts are also extended to the next generation5G systems where the energy efficiency of the base station is improved.This work includes six papers that examine digital circuits in MIMO wireless receivers. Several key blocks in these receiver include analog circuits thathave residual non-linearities, leading to signal intermodulation and distortion.Paper-I introduces a digital technique to detect such non-linearities and calibrate analog circuits to improve signal quality. The concept of a digital nonlinearity tuning system developed in Paper-I is implemented and demonstratedin hardware. The performance of this implementation is tested with an analogchannel select filter, and results are presented in Paper-II. MIMO systems suchas the ones used in 4G, may employ QR Decomposition (QRD) processors tosimplify the implementation of tree search based signal detectors. However,the small form factor of the mobile device increases spatial correlation, whichis detrimental to signal multiplexing. Consequently, a QRD processor capableof handling high spatial correlation is presented in Paper-III. The algorithm and hardware implementation are optimized for carrier aggregation, which increases requirements on signal processing throughput, leading to higher powerdissipation. Paper-IV presents a method to perform channel-aware processingwith a simple interpolation strategy to adaptively reduce QRD computationcount. Channel properties such as coherence bandwidth and SNR are used toreduce multiplications by 40% to 80%. These concepts are extended to usetime domain correlation properties, and a full QRD processor for 4G systemsfabricated in 28 nm FD-SOI technology is presented in Paper-V. The designis implemented with a configurable architecture and measurements show thatcircuit tuning results in a highly energy efficient processor, requiring 0.2 nJ to1.3 nJ for each QRD. Finally, these adaptive channel-aware signal processingconcepts are examined in the scope of the next generation of communicationsystems. Massive MIMO systems increase spectral efficiency by using a largenumber of antennas at the base station. Consequently, the signal processingat the base station has a high computational count. Paper-VI presents a configurable detection scheme which reduces this complexity by using techniquessuch as selective user detection and interpolation based signal processing. Hardware is optimized for resource sharing, resulting in a highly reconfigurable andenergy efficient uplink signal detector

Digitally-Enhanced Software-Defined Radio Receiver Robust to Out-of-Band Interference

A software-defined radio (SDR) receiver with improved robustness to out-of-band interference (OBI) is presented. Two main challenges are identified for an OBI-robust SDR receiver: out-of-band nonlinearity and harmonic mixing. Voltage gain at RF is avoided, and instead realized at baseband in combination with low-pass filtering to mitigate blockers and improve out-of-band IIP3. Two alternative “iterative” harmonic-rejection (HR) techniques are presented to achieve high HR robust to mismatch: a) an analog two-stage polyphase HR concept, which enhances the HR to more than 60 dB; b) a digital adaptive interference cancelling (AIC) technique, which can suppress one dominating harmonic by at least 80 dB. An accurate multiphase clock generator is presented for a mismatch-robust HR. A proof-of-concept receiver is implemented in 65 nm CMOS. Measurements show 34 dB gain, 4 dB NF, and 3.5 dBm in-band IIP3 while the out-of-band IIP3 is + 16 dBm without fine tuning. The measured RF bandwidth is up to 6 GHz and the 8-phase LO works up to 0.9 GHz (master clock up to 7.2 GHz). At 0.8 GHz LO, the analog two-stage polyphase HR achieves a second to sixth order HR > dB over 40 chips, while the digital AIC technique achieves HR > 80 dB for the dominating harmonic. The total power consumption is 50 mA from a 1.2 V supply

Digitally-Assisted RF IC Design Techniques for Reliable Performance

Semiconductor industries have competitively scaled down CMOS devices to attain benefits of low cost, high performance, and high integration density in digital integrated circuits. On the other hand, deep scaled technologies inextricably accompany a large process variation, supply voltage scaling, and reduction in breakdown voltages of transistors. When it comes to RF/analog IC design, CMOS scaling adversely affects its reliability due to large performance variation and limited linearity. For addressing the issues related to variations and linearity, this research proposes the following digitally-assisted RF circuit design techniques: self-calibration system for RF phase shifters and wide dynamic range LNAs. Due to PVT variations in scaled technologies, RF phase shifter design becomes more challenging with device scaling. In the proposed self-calibration topology, we devised a novel phase sensing method and a pulsewidth-to-digital converter. The feedback controller is also designed in digital domain, which is robust to PVT variations. These unique techniques enable a sensing/control loop tolerant to PVT variations. The self-calibration loop was applied to a 7 to 13GHz phase shifter. With the calibration, the estimated phase error is less than 2 degrees. To overcome the linearity issue in scaled technologies, a digitally-controlled dual-mode LNA design is presented. A narrowband (5.1GHz) and a wideband (0.8 to 6GHz) LNA can be toggled between high-gain and high-linearity modes by digital control bits according to the input signal power. A compact design, which provides negligible performance degradation by additional circuitry, is achieved by sharing most of the components between the two operation modes. The narrowband and the wideband LNA achieves an input-referred P1dB of -1.8dBm and +4.2dBm, respectively

Flexible Receivers in CMOS for Wireless Communication

Consumers are pushing for higher data rates to support more services that are introduced in mobile applications. As an example, a few years ago video-on-demand was only accessed through landlines, but today wireless devices are frequently used to stream video. To support this, more flexible network solutions have merged in 4G, introducing new technical problems to the mobile terminal. New techniques are thus needed, and this dissertation explores five different ideas for receiver front-ends, that are cost-efficient and flexible both in performance and operating frequency. All ideas have been implemented in chips fabricated in 65 nm CMOS technology and verified by measurements. Paper I explores a voltage-mode receiver front-end where sub-threshold positive feedback transistors are introduced to increase the linearity in combination with a bootstrapped passive mixer. Paper II builds on the idea of 8-phase harmonic rejection, but simplifies it to a 6-phase solution that can reject noise and interferers at the 3rd order harmonic of the local oscillator frequency. This provides a good trade-off between the traditional quadrature mixer and the 8- phase harmonic rejection mixer. Furthermore, a very compact inductor-less low noise amplifier is introduced. Paper III investigates the use of global negative feedback in a receiver front-end, and also introduces an auxiliary path that can cancel noise from the main path. In paper IV, another global feedback based receiver front-end is designed, but with positive feedback instead of negative. By introducing global positive feedback, the resistance of the transistors in a passive mixer-first receiver front-end can be reduced to achieve a lower noise figure, while still maintaining input matching. Finally, paper V introduces a full receiver chain with a single-ended to differential LNA, current-mode downconversion mixers, and a baseband circuity that merges the functionalities of the transimpedance amplifier, channel-select filter, and analog-to-digital converter into one single power-efficient block

EKGNet: A 10.96{\mu}W Fully Analog Neural Network for Intra-Patient Arrhythmia Classification

We present an integrated approach by combining analog computing and deep learning for electrocardiogram (ECG) arrhythmia classification. We propose EKGNet, a hardware-efficient and fully analog arrhythmia classification architecture that archives high accuracy with low power consumption. The proposed architecture leverages the energy efficiency of transistors operating in the subthreshold region, eliminating the need for analog-to-digital converters (ADC) and static random access memory (SRAM). The system design includes a novel analog sequential Multiply-Accumulate (MAC) circuit that mitigates process, supply voltage, and temperature variations. Experimental evaluations on PhysioNet's MIT-BIH and PTB Diagnostics datasets demonstrate the effectiveness of the proposed method, achieving average balanced accuracy of 95% and 94.25% for intra-patient arrhythmia classification and myocardial infarction (MI) classification, respectively. This innovative approach presents a promising avenue for developing low-power arrhythmia classification systems with enhanced accuracy and transferability in biomedical applications.Comment: Accepted on IEEE Biomedical Circuits and Systems (BioCAS) 202

Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications

With the advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors, new opportunities are emerging for applying deep and Spiking Neural Network (SNN) algorithms to healthcare and biomedical applications at the edge. This can facilitate the advancement of the medical Internet of Things (IoT) systems and Point of Care (PoC) devices. In this paper, we provide a tutorial describing how various technologies ranging from emerging memristive devices, to established Field Programmable Gate Arrays (FPGAs), and mature Complementary Metal Oxide Semiconductor (CMOS) technology can be used to develop efficient DL accelerators to solve a wide variety of diagnostic, pattern recognition, and signal processing problems in healthcare. Furthermore, we explore how spiking neuromorphic processors can complement their DL counterparts for processing biomedical signals. After providing the required background, we unify the sparsely distributed research on neural network and neuromorphic hardware implementations as applied to the healthcare domain. In addition, we benchmark various hardware platforms by performing a biomedical electromyography (EMG) signal processing task and drawing comparisons among them in terms of inference delay and energy. Finally, we provide our analysis of the field and share a perspective on the advantages, disadvantages, challenges, and opportunities that different accelerators and neuromorphic processors introduce to healthcare and biomedical domains. This paper can serve a large audience, ranging from nanoelectronics researchers, to biomedical and healthcare practitioners in grasping the fundamental interplay between hardware, algorithms, and clinical adoption of these tools, as we shed light on the future of deep networks and spiking neuromorphic processing systems as proponents for driving biomedical circuits and systems forward.Comment: Submitted to IEEE Transactions on Biomedical Circuits and Systems (21 pages, 10 figures, 5 tables

Design of Low-Voltage Digital Building Blocks and ADCs for Energy-Efficient Systems

Increasing number of energy-limited applications continue to drive the demand for designing systems with high energy efficiency. This tutorial covers the main building blocks of a system implementation including digital logic, embedded memories, and analog-to-digital converters and describes the challenges and solutions to designing these blocks for low-voltage operation

Parametric analog signal amplification applied to nanoscale cmos wireless digital transceivers

Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer Engineering by the Universidade Nova de Lisboa,Faculdade de Ciências e TecnologiaSignal amplification is required in almost every analog electronic system. However noise is also present, thus imposing limits to the overall circuit performance, e.g., on the sensitivity of the radio transceiver. This drawback has triggered a major research on the field, which has been producing several solutions to achieve amplification with minimum added noise. During the Fifties, an interesting out of mainstream path was followed which was based on variable reactance instead of resistance based amplifiers. The principle of these parametric circuits permits to achieve low noise amplifiers since the controlled variations of pure reactance elements is intrinsically noiseless. The amplification is based on a mixing effect which enables energy transfer from an AC pump source to other related signal frequencies. While the first implementations of these type of amplifiers were already available at that time, the discrete-time version only became visible more recently. This discrete-time version is a promising technique since it is well adapted to the mainstream nanoscale CMOS technology. The technique itself is based on the principle of changing the surface potential of the MOS device while maintaining the transistor gate in a floating state. In order words, the voltage amplification is achieved by changing the capacitance value while maintaining the total charge unchanged during an amplification phase. Since a parametric amplifier is not intrinsically dependent on the transconductance of the MOS transistor, it does not directly suffer from the intrinsic transconductance MOS gain issues verified in nanoscale MOS technologies. As a consequence, open-loop and opamp free structures can further emerge with this additional contribution. This thesis is dedicated to the analysis of parametric amplification with special emphasis on the MOS discrete-time implementation. The use of the latter is supported on the presentation of several circuits where the MOS Parametric Amplifier cell is well suited: small gain amplifier, comparator, discrete-time mixer and filter, and ADC. Relatively to the latter, a high speed time-interleaved pipeline ADC prototype is implemented in a,standard 130 nm CMOS digital technology from United Microelectronics Corporation (UMC). The ADC is fully based on parametric MOS amplification which means that one could achieve a compact and MOS-only implementation. Furthermore, any high speed opamp has not been used in the signal path, being all the amplification steps implemented with open-loop parametric MOS amplifiers. To the author’s knowledge, this is first reported pipeline ADC that extensively used the parametric amplification concept.Fundação para a Ciência e Tecnologia through the projects SPEED, LEADER and IMPAC