An Octave-Range, Watt-Level, Fully-Integrated CMOS Switching Power Mixer Array for Linearization and Back-Off-Efficiency Improvement

The power mixer array is presented as a novel power generation approach for non-constant envelope signals. It comprises several power mixer units that are dynamically turned on and off to improve the linearity and back-off efficiency. At the circuit level, the power mixer unit can operate as a switching amplifier to achieve high peak power efficiency. Additional circuit level linearization and back-off efficiency improvement techniques are also proposed. To demonstrate the feasibility of this idea, a fully-integrated octave-range CMOS power mixer array is implemented in a 130 nm CMOS process. It is operational between 1.2 GHz and 2.4 GHz and can generate an output power of +31.3 dBm into an external 50 Ω load with a PAE of 42% and a gain compression of only 0.4 dB at 1.8 GHz. It achieves a PAE of 25%, at an average output power of +26.4 dBm, and an EVM of 4.6% with a non-constant-envelope 16 QAM signal. It can also produce arbitrary signal levels down to -70 dBm of output power with the 16 QAM-modulated signal without any RF gain control circuit

Guest editorial: Special issue on selected papers from IEEE BioCAS 2018

The papers in this special section were presented at the 2018 IEEE Biomedical Circuits and Systems Conference (BioCAS 2018) that was held in in Cleveland, OH, from October 17–19, 2018

A CMOS Broadband Power Amplifier With a Transformer-Based High-Order Output Matching Network

A transformer-based high-order output matching network is proposed for broadband power amplifier design, which provides optimum load impedance for maximum output power within a wide operating frequency range. A design methodology to convert a canonical bandpass network to the proposed matching configuration is also presented in detail. As a design example, a push-pull deep class-AB PA is implemented with a third-order output network in a standard 90 nm CMOS process. The leakage inductances of the on-chip 2:1 transformer are absorbed into the output matching to realize the third-order network with only two inductor footprints for area conservation. The amplifier achieves a 3 dB bandwidth from 5.2 to 13 GHz with +25.2 dBm peak P_sat and 21.6% peak PAE. The EVM for QPSK and 16-QAM signals both with 5 Msample/s are below 3.6% and 5.9% at the output 1 dB compression point. This verifies the PA’s capability of amplifying a narrowband modulated signal whose center-tone can be programmed across a large frequency range. The measured BER for transmitting a truly broadband PRBS signal up to 7.5 Gb/s is less than 10^(-13) , demonstrating the PA’s support for an instantaneous wide operation bandwidth

Efficient DSP and Circuit Architectures for Massive MIMO: State-of-the-Art and Future Directions

Massive MIMO is a compelling wireless access concept that relies on the use of an excess number of base-station antennas, relative to the number of active terminals. This technology is a main component of 5G New Radio (NR) and addresses all important requirements of future wireless standards: a great capacity increase, the support of many simultaneous users, and improvement in energy efficiency. Massive MIMO requires the simultaneous processing of signals from many antenna chains, and computational operations on large matrices. The complexity of the digital processing has been viewed as a fundamental obstacle to the feasibility of Massive MIMO in the past. Recent advances on system-algorithm-hardware co-design have led to extremely energy-efficient implementations. These exploit opportunities in deeply-scaled silicon technologies and perform partly distributed processing to cope with the bottlenecks encountered in the interconnection of many signals. For example, prototype ASIC implementations have demonstrated zero-forcing precoding in real time at a 55 mW power consumption (20 MHz bandwidth, 128 antennas, multiplexing of 8 terminals). Coarse and even error-prone digital processing in the antenna paths permits a reduction of consumption with a factor of 2 to 5. This article summarizes the fundamental technical contributions to efficient digital signal processing for Massive MIMO. The opportunities and constraints on operating on low-complexity RF and analog hardware chains are clarified. It illustrates how terminals can benefit from improved energy efficiency. The status of technology and real-life prototypes discussed. Open challenges and directions for future research are suggested.Comment: submitted to IEEE transactions on signal processin

Recent Advances in Neural Recording Microsystems

The accelerating pace of research in neuroscience has created a considerable demand for neural interfacing microsystems capable of monitoring the activity of large groups of neurons. These emerging tools have revealed a tremendous potential for the advancement of knowledge in brain research and for the development of useful clinical applications. They can extract the relevant control signals directly from the brain enabling individuals with severe disabilities to communicate their intentions to other devices, like computers or various prostheses. Such microsystems are self-contained devices composed of a neural probe attached with an integrated circuit for extracting neural signals from multiple channels, and transferring the data outside the body. The greatest challenge facing development of such emerging devices into viable clinical systems involves addressing their small form factor and low-power consumption constraints, while providing superior resolution. In this paper, we survey the recent progress in the design and the implementation of multi-channel neural recording Microsystems, with particular emphasis on the design of recording and telemetry electronics. An overview of the numerous neural signal modalities is given and the existing microsystem topologies are covered. We present energy-efficient sensory circuits to retrieve weak signals from neural probes and we compare them. We cover data management and smart power scheduling approaches, and we review advances in low-power telemetry. Finally, we conclude by summarizing the remaining challenges and by highlighting the emerging trends in the field

Guest Editorial Special Issue on Selected Papers From IEEE ISCAS 2020

No abstract available

Always-On 674uW @ 4GOP/s Error Resilient Binary Neural Networks with Aggressive SRAM Voltage Scaling on a 22nm IoT End-Node

Binary Neural Networks (BNNs) have been shown to be robust to random bit-level noise, making aggressive voltage scaling attractive as a power-saving technique for both logic and SRAMs. In this work, we introduce the first fully programmable IoT end-node system-on-chip (SoC) capable of executing software-defined, hardware-accelerated BNNs at ultra-low voltage. Our SoC exploits a hybrid memory scheme where error-vulnerable SRAMs are complemented by reliable standard-cell memories to safely store critical data under aggressive voltage scaling. On a prototype in 22nm FDX technology, we demonstrate that both the logic and SRAM voltage can be dropped to 0.5Vwithout any accuracy penalty on a BNN trained for the CIFAR-10 dataset, improving energy efficiency by 2.2X w.r.t. nominal conditions. Furthermore, we show that the supply voltage can be dropped to 0.42V (50% of nominal) while keeping more than99% of the nominal accuracy (with a bit error rate ~1/1000). In this operating point, our prototype performs 4Gop/s (15.4Inference/s on the CIFAR-10 dataset) by computing up to 13binary ops per pJ, achieving 22.8 Inference/s/mW while keeping within a peak power envelope of 674uW - low enough to enable always-on operation in ultra-low power smart cameras, long-lifetime environmental sensors, and insect-sized pico-drones.Comment: Submitted to ISICAS2020 journal special issu

Programmable Active Mirror: A Scalable Decentralized Router

This work proposes and demonstrates the scalable router array that eliminates the internal centralization of conventional arrays, unlocking scalability, and the potential for a system composed of spatially separated elements that do not share a common timing reference. Architectural variations are presented, and their specific tradeoffs are discussed. The general operation, steering capabilities, signal and noise considerations, and timing control advantages are evaluated through analysis, simulation, and measurements. An element-level CMOS radio frequency integrated circuit (RFIC) is developed and used to demonstrate a four-element 25 GHz prototype router. The RFIC's programmable true time delay (TTD) control is used to correct path-length-difference-induced intersymbol interference (ISI) and improve a rerouted 270-Mb/s 64-QAM constellation from a completely scrambled state to an EVM of 4% rms (-28 dB). The prototype scalable router's concurrent dual-beam capabilities are demonstrated by simultaneously steering two full power beams at 24.9 and 25 GHz in two different directions in a free-space electromagnetic setup

High-Density Solid-State Memory Devices and Technologies

This Special Issue aims to examine high-density solid-state memory devices and technologies from various standpoints in an attempt to foster their continuous success in the future. Considering that broadening of the range of applications will likely offer different types of solid-state memories their chance in the spotlight, the Special Issue is not focused on a specific storage solution but rather embraces all the most relevant solid-state memory devices and technologies currently on stage. Even the subjects dealt with in this Special Issue are widespread, ranging from process and design issues/innovations to the experimental and theoretical analysis of the operation and from the performance and reliability of memory devices and arrays to the exploitation of solid-state memories to pursue new computing paradigms