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There has been much interest in replacing traditional information supports with more technological solutions in recent years. New technologies which allow paper-like perception with minimal power needs have emerged as low-power wireless scenarios. A priority for these new supports is to create the architecture for a scalable solution which maintains minimal power requirements. The retail industry demands a new information infrastructure that improves customer and employee satisfaction. In this work, authors propose an information provision architecture based on E-Paper and carry out an experiment where different smart labeling architectures based on Paper, E-Paper, LED liquid crystal display (LCD) and Dot-matrix LCD were tested in order to determine which is best suited for a real labeling environment. Enclosed in a research project called SMARKET, the authors pilot-tested the work in a real supermarket, having the opportunity to survey employees and customers about satisfaction and frustration with the use of the architectures proposed in this research work. [ABSTRACT FROM AUTHOR]

This paper presents a shock detection device for packages in the supply chain. The primary purpose is to identify package damage during storage, delivery, and handling. Additionally, products are likely to be damaged if dropped from a certain height, which sometimes does not appear on the package. By continuously measuring package vibrations and detecting shocks in the supply chain, consumers can gain an insight into the state of the product upon delivery. This paper presents the Smart Sticker implementation for ultra-low-power shock detection in the supply chain. The overall energy consumption must be kept as low as possible while continuously sensing the presence of shock to ensure that the Smart Sticker's battery lasts as long as possible. The Smart Sticker functions in three modes to meet the established constraints: low-power, active, and data transfer mode. While detecting the shock, the low-power mode uses the least amount of energy needed. If the shock exceeds the threshold, the Smart Sticker enters active mode, stores the detected g force value in memory, and then switches back to low-power mode. Finally, employing Near Field Communication (NFC) and energy harvesting, the data transfer mode allows the consumer to read the recorded data. The results show that the Smart Sticker for shock detection performs according to set requirements and successfully monitors and detects shock for packages in the supply chain. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) and blockchain are emerging technologies that have attracted attention in many industries, including healthcare, automotive, and supply chain. IoT networks and devices are typically low-powered and susceptible to cyber intrusions. However, blockchains hold considerable potential for securing low-power IoT networks. Blockchain networks provide security features such as encryption, decentralisation, time stamps, and ledger functions. The integration of blockchain and IoT technologies may address many of the security concerns. However, integrating blockchain with IoT raises several issues, including the security vulnerabilities and anomalies of blockchain-based IoT networks. In this paper, we report on our experiments using our blockchain test bed to demonstrate that blockchains on IoT platforms are vulnerable to DDoS attacks, which can also potentially lead to device hardware failures. We show that a number of anomalies are visible during either a DDoS attack or IoT device failure. In particular, the temperature of IoT hardware devices can exceed 90 °C during a DDoS attack, which could lead to hardware failure and potential fire hazards. We also found that the Block Transaction Rate (BTR) and network block loss percentage can increase due to corrupted hardware, with the BTR dropping to nearly zero blocks/sec and a block loss percentage of over 50 percent for all evaluated blockchains, and as high as 81.3 percent in one case. Our experiments demonstrate that anomalous temperature, latency, bandwidth, BTR, and network block loss percentage can potentially be used to identify DDoS attacks. [ABSTRACT FROM AUTHOR]

A low-power, low-voltage universal multi-mode Gm-C filter using a 180 nm TSMC technology node is presented in this paper. The proposed filter employs only three transconductance operational amplifiers (OTAs) operating in the sub-threshold region with a supply voltage of 0.5 V, resulting in a power consumption of 32 nW. Moreover, without additional active elements, the proposed circuit can operate various functional modes, such as voltage, current, transconductance, and trans-resistance. The filter's frequency, centered at 462 Hz, and a compact and low-power solution showing only 93.5 µVrms input-referred noise make the proposed filter highly suitable for bio-signal processing. [ABSTRACT FROM AUTHOR]

Edge computing enables prompt responses in IoT environments, such as the operation of autonomous vehicles and unmanned aerial vehicles. However, with the increase in sensor nodes, the computational burden on the computing node also increases. Specifically, data filtering and reduction at application nodes add to the energy burden for battery-operated devices. In this paper, we propose a preprocessing system at the application node that requires low power consumption for data transmission reduction. Based on our simulations, we identify the minimum data size needed to preserve the signal. We first design the preprocessing system using a hardware description language to evaluate its performance. Then, we implement the open-library-based MCU system, including the proposed preprocessing IP, to assess its operation and overhead. Our implementation of the preprocessing system reduces data transmission by 50% with acceptable information loss. Additionally, the area and power consumption after the logic synthesis of the preprocessing IP within the entire MCU system are evaluated at only 3.6% and 13.1%, respectively. By performing preprocessing using the MCU and proposed IP, nearly 74.4% power reduction is achieved compared to using the existing MCU core. [ABSTRACT FROM AUTHOR]

Brain-inspired flexible neuromorphic devices are of great significance for next-generation high-efficiency wearable sensing and computing systems. In this paper, we propose a flexible organic electrochemical transistor using poly[(bithiophene)-alternate-(2,5-di(2-octyldodecyl)- 3,6-di(thienyl)-pyrrolyl pyrrolidone)] (DPPT-TT) as the organic semiconductor and poly(methyl methacrylate) (PMMA)/LiClO4 solid-state electrolyte as the gate dielectric layer. Under gate voltage modulation, an electric double layer (EDL) forms between the dielectric layer and the channel, allowing the device to operate at low voltages. Furthermore, by leveraging the double layer effect and electrochemical doping within the device, we successfully mimic various synaptic behaviors, including excitatory post-synaptic currents (EPSC), paired-pulse facilitation (PPF), high-pass filtering characteristics, transitions from short-term plasticity (STP) to long-term plasticity (LTP), and demonstrate its image recognition and storage capabilities in a 3 × 3 array. Importantly, the device's electrical performance remains stable even after bending, achieving ultra-low-power consumption of 2.08 fJ per synaptic event at −0.001 V. This research may contribute to the development of ultra-low-power neuromorphic computing, biomimetic robotics, and artificial intelligence. [ABSTRACT FROM AUTHOR]

Bluetooth Low Energy Mesh (BLE Mesh) enables Bluetooth flexibility and coverage by introducing Low-Power Nodes (LPNs) and enhanced networking protocol. It is also a commonly used communication method in sensor networks. In BLE Mesh, LPNs are periodically woken to exchange messages in a stop-and-wait way, where the tradeoff between energy and efficiency is a hard problem. Related works have reduced the energy consumption of LPNs mainly in the direction of changing the bearer layer, improving time synchronization and broadcast channel utilization. These algorithms improve communication efficiency; however, they cause energy loss, especially for the LPNs. In this paper, we propose a constrained flooding algorithm based on time series prediction and lightweight GBN (Go-Back-N). On the one hand, the wake-up cycle of the LPNs is determined by the time series prediction of the surrounding load. On the other, LPNs exchange messages through lightweight GBN, which improves the window and ACK mechanisms. Simulation results validate the effectiveness of the Time series Prediction and LlightWeight GBN (TP-LW) algorithm in energy consumption and throughput. Compared with the original algorithm of BLE Mesh, when fewer packets are transmitted, the throughput is increased by 214.71%, and the energy consumption is reduced by 65.14%. [ABSTRACT FROM AUTHOR]

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The constant growth of social media, unconventional web technologies, mobile applications, and Internet of Things (IoT) devices create challenges for cloud data systems in order to support huge datasets and very high request rates. NoSQL databases, such as Cassandra and HBase, and relational SQL databases with replication, such as Citus/PostgreSQL, have been used to increase horizontal scalability and high availability of data store systems. In this paper, we evaluated three distributed databases on a low-power low-cost cluster of commodity Single-Board Computers (SBC): relational Citus/PostgreSQL and NoSQL databases Cassandra and HBase. The cluster has 15 Raspberry Pi 3 nodes with Docker Swarm orchestration tool for service deployment and ingress load balancing over SBCs. We believe that a low-cost SBC cluster can support cloud serving goals such as scale-out, elasticity, and high availability. Experimental results clearly demonstrated that there is a trade-off between performance and replication, which provides availability and partition tolerance. Besides, both properties are essential in the context of distributed systems with low-power boards. Cassandra attained better results with its consistency levels specified by the client. Both Citus and HBase enable consistency but it penalizes performance as the number of replicas increases. [ABSTRACT FROM AUTHOR]

Modern processors often face challenges when handling instructions that overwhelm the branch target buffer (BTB), leading to front-end bottlenecks. As the BTB's capacity increases, its prediction module can become slower and power-hungry. In this paper, we introduce a straightforward yet highly effective two-level prediction mechanism to mitigate the escalating power consumption in the BTB structure, achieved by reducing the number of accesses. Our approach incorporates two main elements: M-BTB and V-BTB. M-BTB encompasses the first-level prediction mechanism and a fully associative BTB, while V-BTB houses the second-level prediction mechanism and a set-associative BTB. To implement our prediction mechanism, we optimize the traditional two-level BTB structure. The first level employs the skew mechanism, and the second level dissects the tag bits to create the Partial tag. These two levels of prediction mechanism correspond to the bank/way prediction for the two-level BTB structure. Our experimental results show that the first-stage prediction mechanism reduces M-BTB accesses by 75%, while the second-stage prediction mechanism ensures that over 98% of addresses require just zero or one way of the V-BTB to achieve a hit result. Our proposed approach achieves a remarkable 86–97% reduction in power consumption, with a minimal impact on performance and an increase in overall area efficiency. [ABSTRACT FROM AUTHOR]

Digital Image Processing has dominated Digital Signal Processing at the cost of more memory, resources, and high computational power. In image processing, filtering transformations and other operations need complex multiplications, and the multiplier is one of the most resources consuming elements. Recently, mitigating the multiplier complexity in the digital signal processing (DSP) algorithms sigma-delta modulation based general purpose and adaptive DSP algorithms are developed in MATLAB and compared with its counterpart multibit algorithms for functionality and area-performance-power in FPGA. The contemporary multiplier algorithms are also optimized to overcome the multiplier complexity challenge as computation becomes simple and fast. This paper extends the reported work by investigating the sigma-delta modulation approaches for developing a computationally efficient low-power image processing algorithm. The proposed model is designed, developed, and simulated in MATLAB. The simulation results are analyzed using SNR, MSE, and Peak SNR. The simulation results show that the proposed system can better mitigate the noise effect, making it robust for noisy environment. [ABSTRACT FROM AUTHOR]

This paper presents a CNFET (Carbon Nano-tube FET) based MT (Multi-Threshold)-SRAM (Static Random Access Memory) design based on the leakage reduction mechanism. A multi-threshold logic is employed for reducing the leakage current during read/write operations. Here, the multi-threshold technique is used to insert the high threshold sleep control to the low threshold circuit. The insertion is performed in a serial manner. The high threshold transistors are very useful for deriving the low sub-threshold current. Meanwhile, the low threshold transistors are promising for improving the circuit performance. The high-low threshold transistor pairs are used to change the channel length by modifying the oxide thickness of the transistors. The overall implementation of the Multi-threshold-based SRAM cells are implemented with the help of CNFET in-order to avoid the short channel effect, mobility degradation which is occurred while considering the channel length below 32 nm in CMOS (Complementary Metal Oxide Semiconductor) devices. The paper clearly represents the performance improvement of the proposed SRAM cells with above-mentioned technologies. [ABSTRACT FROM AUTHOR]

The survival rate for sudden cardiac arrest (SCA) is low, and patients with long-term risks of SCA are not adequately alerted. Understanding SCA's characteristics will be key to developing preventive strategies. Many lives could be saved if SCA's early onset could be detected or predicted. Monitoring heart signals continuously is essential for diagnosing sporadic cardiac dysfunction. An electrocardiogram (ECG) can be used to continuously monitor heart function without having to go to the hospital. A zeolite-based dry electrode can provide safe on-skin ECG acquisition while the subject is out-of-hospital and facilitate long-term monitoring. To the ECG signal, a low-power 1 μW read-out circuit was designed and implemented in our prior work. However, having long-term ECG monitoring outside the hospital, i.e., high battery life, and low power consumption while transmission and reception of ECG signal are crucial. This paper proposes a prototype with a 10-bit resolution ADC and nRF24L01 transceivers placed 5 m apart. The system uses the 2.4 GHz worldwide ISM frequency band with GFSK modulation to wirelessly transmit digitized ECG bits at 250 kbps data rate to a physician's computer (or similar) for continuous monitoring of ECG signals; the power consumption is only 11.2 mW and 4.62 mW during transmission and reception, respectively, with a low bit error rate of ≤0.1%. Additionally, a subject-wise cross-validated, three-fold, optimized convolutional neural network (CNN) model using the Physionet-SCA dataset was implemented on NVIDIA Jetson to identify the irregular heartbeats yielding an accuracy of 89% with a run time of 5.31 s. Normal beat classification has an F1 score of 0.94 and a ROC score of 0.886. Thus, this paper integrates the ECG acquisition and processing unit with low-power wireless transmission and CNN model to detect irregular heartbeats. [ABSTRACT FROM AUTHOR]

This paper proposes a modified Schmitt-trigger (ST)-based single-ended 11 T (MST11T) SRAM cell. The proposed cell is best suited to ultra-low voltage applications. Two ST-based cross-coupled inverters comprise the storage cell of the proposed MST11T bit cell. In comparison with conventional inverters, ST-based inverters have sharp voltage transfer characteristics. As a result, the proposed bit cell's stability performance increases. The proposed SRAM cell's leakage power consumption is reduced because of the use of stacked N-type transistors. For the read operation of the proposed bit cell, the read decoupled technique is used. As a result, the read static noise margin (RSNM) has greatly improved. The proposed bit cell's write static noise margin (WSNM) is increased by adopting feedback-cutting methodology. The performance of the proposed bit cell is compared with that of conventional 6 T, conventional 8 T, Schmitt-trigger 10 T (known as ST2), modified PMOS-PMOS-NMOS-based cell core 10 T (MPPN10T), feedback-cutting 11 T (FC11T), Schmitt-trigger 11 T (ST11), and Schmitt-trigger 12 T (ST12T) cells. According to the simulation results, the proposed MST11T SRAM cell has RSNM of 2.42, 1.18, 1.71, 1.30, and 1.80 times higher when compared to 6 T, FC11T, ST2, MPPN10T, and ST12T, respectively. The WSNM of the proposed bit cell has been increased by 1.56, 2.44, 1.28, 1.71, 1.35, 1.52, and 1.02 times, respectively, over 6 T, 8 T, ST2, MPPN10T, FC11T, ST11T, and ST12T. Furthermore, the suggested cell has a read delay that is 1.32, 1.79, and 1.53 times lower than ST11T, FC11T, and ST12T, respectively. The proposed bit cell has a write delay that is 1.14 and 1.63 times lower than FC11T and ST11T, respectively. The proposed MST11T bit-cell consumes 3.74, 1.56, 4.59, 5.38, and 4.83 times less leakage power than the 8 T, ST2, MPPN10T, FC11T, and ST12 bit-cells, respectively. When compared to 8 T/ST2/MPPN10T/ST12T at 0.2 V supply voltage, the enhanced facts incur a 4.87/3.79/3.78/1.97 penalty in write delay. The figure of merit (FOM) is derived as a result of this extensive access to the revolutionary SRAM cell performance, i.e., offering greater values at a 0.2 V DC supply voltage. In addition, the paper examines the impact of manufacturing process and temperature changes on MST11T cell enactment, as well as the circuit robustness using HSPICE with 7-nm FinFET technology. [ABSTRACT FROM AUTHOR]

Numerous functionalities are provided by smartphones and prolonging their battery lifetime is an undeniably critical support issue. In this paper, we propose a low-power scheme called unnecessary region freezing (URF) that achieves significant total power consumption reduction in smartphones by reducing unnecessary drawing computation that originates from a user’s uninteresting display region. We implement URF on a real smartphone (Nexus 6). Then, we evaluate our scheme on top of an existing low-power scheme, partial display darkening (PDD). The results indicate that the URF scheme reduces total power consumption by average 5.1% through 12.5% depending on the size of the unnecessary region, compared with the PDD scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the use of approximate fixed-width and static segment multipliers in the design of Delayed Least Mean Square (DLMS) adaptive filters based on the sign–magnitude representation for the error signal. The fixed-width approximation discards part of the partial product matrix and introduces a compensation function for minimizing the approximation error, whereas the static segmented multipliers reduce the bit-width of the multiplicands at runtime. The use of sign–magnitude representation for the error signal reduces the switching activity in the filter learning section, minimizing power dissipation. Simulation results reveal that, by properly sizing the two approaches, a steady state mean square error practically unchanged with respect to the exact DLMS can be achieved. The hardware syntheses in a 28 nm CMOS technology reveal that the static segmented multipliers perform better in the learning section of the filter and are the most efficient approach to reduce area occupation, while the fixed-width multipliers offer the best performances in the finite impulse response section and provide the lowest power dissipation. The investigated adaptive filters overcome the state-of-the-art, exhibiting an area and power reduction with respect to the standard implementation up to −18.0% and −64.1%, respectively, while preserving the learning capabilities. [ABSTRACT FROM AUTHOR]

This paper proposes a novel analog front end to filter edges in captured images. The proposed architecture employs the Sobel algorithm and uses a 3 × 3 kernel to process the input images. We used 180 nm Semi-Conductor Laboratory (SCL) CMOS fabrication technology for implementation with a power supply of 1.8 V. The proposed design employs six analog differential pairs in each horizontal and vertical gradient unit. The inputs to the differential pairs are the active signals fed from the 3 × 3 kernel using the Sobel weight masks. We connected the differential datum pairs in cascade to estimate the gradient index in horizontal/vertical direction using the net difference current between the output terminals. The horizontal and vertical gradient units, viz., G H and G V , respectively, are configured based on the polarity of weights in respective Sobel masks. The gradient (G) of the processing pixel (PP) is estimated using the net difference current in the combined circuitry employing G H and G V cells. The key advantages of the proposed design are very low area realization, high accuracy, and low power dissipation. The efficacy of the proposed edge filter analog front end is estimated through simulations and analysis with two sets of test signals in the processing window. [ABSTRACT FROM AUTHOR]

This paper presents radiation hardened SRAM (namely LPDNUR and HSDNUR), both of which can self-recover from single-node and double-node upsets. LPDNUR uses a two-input C-element structure, which reduces the average power consumption because the stacked effect. Moreover, in order to reduce read access time (RAT) and write access time (WAT), the paper proposes HSDNUR, which uses a combination of NMOS and PMOS as the transistor for one-node data transmission, an approach that increases the current drive capability and reduces transmission delays. Compared to the state-of-the-art radiation-hardened SRAM design, such as QUCCE10T, QUCCE12T, We-Quatro, etc. The model results show that the average power consumption of LPDNUR is reduced by 24.59% on average, and the RAT and WAT of HSDNUR are reduced by an average of 35.71% and 24.14% respectively. • LPDNUR and HSDNUR fully achieve SNU and DNU recovery. • Average power of LPDNUR is 24.59% lower on average than other SRAM hardened since stack structure. • WAT and RAT of HSDNUR are 24.14% and 35.71% lower than other SRAM hardened on average by using TG. [ABSTRACT FROM AUTHOR]

This paper presents static and dynamic theoretical analysis of a new Operational Transconductance Amplifier (OTA) dedicated to low-voltage and low-power applications. High linearity is obtained using signal attenuation for rail-to-rail operation. Design, layout and post-layout simulations have been carried-out with Cadence Virtuoso in a 0.18µm CMOS technology. Post-Layout Simulation (PLS) demonstrates proper operation down to ± 0.75 V supply voltage with a high open loop small-signal voltage gain of 58.26dB, a unity gain frequency of 18MHz and a total harmonic distortion of -66.55dB at 100 kHz for a peak-to-peak input voltage of 0.8V. Based on this circuit, two applications have been successfully demonstrated: on the one side, a 5th order Butterworth G mC filter and, on the other side, a voltage mode instrumentation amplifier. [ABSTRACT FROM AUTHOR]

With the emergence of the internet-of-things (IoT), many devices process data through the IEEE 802.11 wireless networks. To satisfy the increased data processing, the wireless fidelity (Wi-Fi) networks must have sufficient capacity. IEEE 802.11ax is formulated to provide higher data processing capabilities for IoT applications. The IEEE 802.11ax receiver operating at 5 GHz must be able to withstand interference from nearby IoT applications. Hence, the low-noise amplifier (LNA) employed in such receivers must have a high input-referred third-order intercept point (IIP3). This paper aims to present a wideband LNA operating at 5 GHz with high IIP3 for modern IoT transceivers using IEEE 802.11ax protocol. The LNA is designed and implemented in UMC 65 nm CMOS technology using the Cadence virtuoso design tool. The proposed LNA can provide a maximum gain of 17.64 dB while consuming 8.18 mW of power from a 1.2 V supply. It can be noted that the minimum noise figure (NF) achieved is 3.67 dB and the corresponding IIP3 is 9.44 dBm at 5 GHz from the pre-layout simulations. [ABSTRACT FROM AUTHOR]

Clock trees are commonly used to deliver clock signals to sequential elements in circuits. However, by construction, tree structures are inherently prone to failure caused by variations. The robustness of a clock tree can be improved by inserting redundancy in the form of cross links or multilevel fusion trees. Such near-tree structures can provide robustness at low cost. In this paper, we establish that the locations of the inserted redundancy are crucial in providing cost-effective robustness. We present two methods to systematically insert redundancy. The redundancy is realized by either inserting cross links or performing local merges. Moreover, we present a vertex reduction method that reduces the amount of redundancy that needs to be inserted in our near-tree structures. Empirical results show that our structures are more robust to variations and have lower power consumption compared to the state-of-the-art clock networks. Furthermore, our near-tree structures provide smooth trade-offs between cost and robustness, reducing clock skews by 11%–39% at an expense of 3%–68% higher power consumption. [ABSTRACT FROM PUBLISHER]

Portable applications and battery-operated devices require highly reliable, stable, and low-power nanometer-sized embedded cache static random access memory (SRAM) cells. The conventional 6-transistor (6 T) SRAM cell and its variants suffer from malfunctioning during the read/write operations, and instability, and are vulnerable to the multi-bit soft-error rate at scaled technology node and low supply voltage (VDD). In this regard, this paper proposes an 12 T SRAM cell with reliable functioning and reduced multi-bit soft-errors appropriate for low-power portable applications. This cell performs single-end bitline decoupled read operation and write data-dependent feedback-cutting-aware differential write operation to improve the read static noise margin (RSNM) and write static noise margin (WSNM), respectively. The presence of stack transistors in the cell core and read path, and also high virtual ground (VGND) minimize the leakage power dissipation. The proposed cell is compared with other state-of-the-art SRAM cells at VDD = 0.7 V and under harsh process, voltage, and temperature (PVT) variations. It offers at least 1.18X higher RSNM, 1.27X higher WSNM, and 2.02X lower leakage power dissipation. It also shows the second-best read power and incurs a penalty in write power. This cell shows at least 1.17X, 1.32X, and 1.04X smaller spread in read delay, RSNM, and WSNM, respectively, when subjected to PVT variations. In addition, the proposed cell eliminates the write half-select disturbance by employing a separate gate to drive the access transistors and thus column-interleaving structure and error correction coding can be applied to reduce multiple-bit upset and increase soft-error immunity. The soft-error in the proposed cell is reduced by at least 1.37X in critical charge. Generally, the proposed cell offers the best overall performance among all the compared cells by showing the highest proposed figure of merit. [ABSTRACT FROM AUTHOR]

This paper presents a sub-microwatt sub-bandgap voltage and current reference that can generate proportional-to-absolute-temperature (PTAT) and complementary-to-absolute-temperature (CTAT) currents concurrently. The voltage reference is derived from the process-insensitive silicon bandgap voltage of a bipolar junction transistor, whereas the current reference is made by combining PTAT and CTAT currents. Line regulation is improved by incorporating cascode devices without an operational amplifier (opamp). Fabricated in a standard 0.18-µm CMOS process, the proposed bandgap reference occupies an active area of 0.4 mm2. The current and voltage reference ( I REF and V REF ) are measured as 170 mV and 21 nA, respectively, while the start-up settling response is measured as 20 ms at room temperature. The average temperature coefficient of I REF and V REF is 79.8 ppm/°C and 87.93 ppm/°C across the temperature range from − 40 to 120 °C, respectively. The power consumption is 134 nW at the minimum supply voltage of 1.2 V. The power supply ripple rejection of V REF is measured as − 10 dB at 100 kHz without any filtering capacitor, when the 1.6 V input line voltage is distorted by a 300-mVp-p ripple. The measured line sensitivity of the voltage and current reference is 0.142%/V and 0.757%/V, respectively. [ABSTRACT FROM AUTHOR]

Scaling down technology demotes the parameters of AC-coupled neural amplifiers, such as increasing the low-cutoff frequency due to the short-channel effects. To improve the low-cutoff frequency, one solution is to increase the feedback capacitors' value. This solution is not desirable, as the input capacitors have to be increased to maintain the same gain, which increases the area and decreases the input impedance of the neural amplifier. We analytically analyze the small-signal behavior of the neural amplifier and prove that the main reason for the increase of the low-cutoff frequency in advanced CMOS technologies is the reduction of the input resistance of the operational transconductance amplifier (OTA). We also show that the reduction of the input resistance of the OTA is due to the increase in the gate oxide leakage in the input transistors. In this paper, we explore this fact and propose two solutions to reduce the low-cutoff frequency without increasing the value of the feedback capacitor. The first solution is performed by only simulation and is called cross-coupled positive feedback that uses pseudoresistors to provide a negative resistance to increase the input resistance of the OTA. As an advantage, only standard CMOS transistors are used in this method. Simulation results show that a low-cutoff frequency of 1.5 Hz is achieved while the midband gain is 30.4 dB at 1 V. In addition, the power consumption is 0.6 μW. In the second method, we utilize thick-oxide MOS transistors in the input differential pair of the OTA. We designed and fabricated the second method in the 65 nm TSMC CMOS process. Measured results are obtained by in vitro recordings on slices of mouse brainstem. The measurement results show that the bandwidth is between 2 Hz and 5.6 kHz. The neural amplifier has 34.3 dB voltage gain in midband and consumes 3.63 μ W at 1 V power supply. The measurement results show an input-referred noise of 6.1 μ V rms and occupy 0.04 mm 2 silicon area. [ABSTRACT FROM AUTHOR]

In this paper, a low-power structure as an inverter-base circuit is reported for broadband applications. The focus in this study is in obtaining a low-power structure. By applying cascoded structure to an inverter as a feedforward network in the structure, the DC current and hence the power dissipation are decreased. Also, by adding a two-stage active feedback, which yields no miller capacitance, to the cascoded inverter, the structure of the TIA is completed. Simulation results in HSPICE using 90nm CMOS technology parameters show 41 dBΩ transimpedance gain, 6.5 GHz frequency bandwidth and 2.7 µArms input referred noise, which consumes only 1.67mw power at 1V supply. Results and analysis indicate that the proposed TIA is suitable to work as a low-power 10 Gbps transimpedance amplifier in an optical receiver. [ABSTRACT FROM AUTHOR]

IoT and wearable medical devices frequently require ultra-low power solutions that can support long spells of inactivity. This study presents a buck converter to control power stages using a novel pulse frequency modulation (PFM) system that reduces switching losses for low-power systems. The modulation of high and low-frequencies was demonstrated, where the high-frequencies exhibited better energy transformation between the inductor and capacitor, and the low-frequencies could be adjusted for different current loads, to reduce switching losses. This circuit is optimized for light load applications. Using voltage control oscillation (VCO), the frequency range of 0.5 MHz – 2.0 MHz can be adjusted to influence conversion efficiency for different loads. The design was simulated and then fabricated using TSMC 0.18um process. The core size was about 1500 × 1000um that includes power MOS. Measurements result an average conversion efficiency of 91% under a load of 0.1 mA – 10 mA. This chip is suitable for battery-based IoT systems, or wearable medical devices. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the performances of an Enhanced Static Segment Multiplier (ESSM) when the inputs have both uniform and non-uniform distribution. The enhanced segmentation divides the multiplicands into a lower, a middle, and an upper segment. While the middle segment is placed at the center of the inputs in other implementations, we seek the optimal position able to minimize the approximation error. To this aim, two design parameters are exploited: m, defining the size and the accuracy of the multiplier, and q, defining the position of the middle segment for further accuracy tuning. A hardware implementation is proposed for our generalized ESSM (gESSM), and an analytical model is described, able to find m and q which minimize the mean square approximation error. With uniform inputs, the error slightly improves by increasing q, whereas a large error decrease is observed by properly choosing q when the inputs are half-normal (with a NoEB up to 18.5 bits for a 16-bit multiplier). Implementation results in 28 nm CMOS technology are also satisfactory, with area and power reductions up to 71% and 83%. We report image and audio processing applications, showing that gESSM is a suitable candidate in applications with non-uniform inputs. [ABSTRACT FROM AUTHOR]

A low-noise and -power readout integrated circuit (IC) for two-electrode electrocardiogram (ECG) recording is developed in this study using a common-mode charge pump (CMCP) for a robust 20-VPP common-mode interference (CMI). Two-electrode ECG recording offers more comfort than three-electrode ECG recording. Contrasting to the three-electrode ECG recording, the two-electrode ECG recording is affected by CMI during measurements; the intervention of a large CMI will distort the ECG signal measurement. To achieve robustness for the CMI, the proposed ECG readout IC adopts CMCP—it uses switched capacitors that store and subtract CMI by control logic. In this paper, a window comparator structure is applied to CMCP to obtain a signal with less distortion. The window voltage ranges were set between the input common-mode ranges in which IA can operate. Therefore, a signal with less distortion was obtained by stopping the operation of CMCP between the window voltage ranges. It also reduced additional current consumption. To achieve this, the proposed circuit is implemented using a chopper stabilization technique. The chopper implemented in the amplifier can reduce low-frequency noise components, such as 1/f noise, and it comprises a CMCP, current feedback instrumentation amplifier, QRS peak detector, relaxation oscillator, voltage reference, timing generator, and serial peripheral interface on a single chip. The proposed circuit was designed using a standard 0.18 μm CMOS process with an active area of 0.54 mm2. The proposed CMCP achieves a CMI robustness of 20 VPP at 60 Hz. The measured input-referred noise level was 119 nV/√Hz at 1 Hz, and the power consumption was 23.83 μW with a 1.8 V power supply. [ABSTRACT FROM AUTHOR]

This paper presents the first implementation of a spiking neural network (SNN) for the extraction of cepstral coefficients in structural health monitoring (SHM) applications and demonstrates the possibilities of neuromorphic computing in this field. In this regard, we show that spiking neural networks can be effectively used to extract cepstral coefficients as features of vibration signals of structures in their operational conditions. We demonstrate that the neural cepstral coefficients extracted by the network can be successfully used for anomaly detection. To address the power efficiency of sensor nodes, related to both processing and transmission, affecting the applicability of the proposed approach, we implement the algorithm on specialised neuromorphic hardware (Intel ® Loihi architecture) and benchmark the results using numerical and experimental data of degradation in the form of stiffness change of a single degree of freedom system excited by Gaussian white noise. The work is expected to open a new direction of SHM applications towards non-Von Neumann computing through a neuromorphic approach. [ABSTRACT FROM AUTHOR]

This paper proposes a new discrete cosine transform (DCT) processor. The micro-rotation section of the architecture is based on a shared-resource improved coordinate rotation digital computer (CORDIC) unit, in an enhanced scalable DCT engine. To reduce the resources, and utilization area all micro-rotation operations have implemented as one united block in overlapped form. Using one processing element, the memory-based architecture has reduced the power consumption. Inputs and outputs of the processor are in-order which can be taken into account as an advantage for the proposed design. The processor has a low-complexity and distributed controller. Furthermore, due to the shared-resource implementation of CORDIC-II unit, by reduction of adding, shifting operations both in size, and number, the processor has high capabilities in short word lengths in comparison with state-of-the-art DCT processors. Compared to existing prominent DCT processors, the proposed processor achieves better results with limited hardware resources. [ABSTRACT FROM AUTHOR]

A close correlation between CO2 concentration and aerosol enables the wide utilization of CO2 concentration as a good representation of Severe Acute Respiratory Syndrome-Coronavirus-2 infection airborne transmission. On the other side, many indoor air-quality monitoring devices have been developed for indoor monitoring applications. However, most of them are multiparameter air-quality sensor systems and tend to consume relatively high power, are relatively large devices, and are fairly expensive; therefore, they not meet the requirement for indoor monitoring applications. This paper presents a smart wireless sensor node that can measure and monitor CO2 concentration levels. The node was designed to meet the requirements of indoor air-quality monitoring applications by considering several factors, such as compact size, low cost, and low power, as well as providing real-time, continuous, reliable, and remote measurement. Furthermore, the commercial off-the-shelf and low-power consumption components are chosen to fit with the low-cost development and reduce energy consumption. Moreover, a low-power algorithm and cloud-based data logger also were applied to minimize the total power consumption. This power strategy was applied as a preliminary development toward an autonomous sensor node. The node has a compact size and consumes low energy for one cycle of CO2 measurement, accompanied by high accuracy with very low measurement error. The experiment result revealed the node could measure and monitor in real-time continuous, reliable, and remote CO2 concentration levels in indoor and outdoor environments. A user interface visualizes CO2 concentration graphically and numerically using the Adafruit platform for easy accessibility over the Internet of Things. The developed node is very promising and suitable for indoor CO2 monitoring applications with the acquired data that could be utilized as an indicator to minimize the risk of indoor Severe Acute Respiratory Syndrome-Coronavirus-2 airborne transmission. [ABSTRACT FROM AUTHOR]

A design flow using the / methodology with the adaptive particle swarm optimization (PSO) algorithm is proposed for the modern analog circuit in this paper. For the advanced CMOS process, / methodology is suitable to the long channel and short channel design in all transistor operation regions. Different from the classical PSO algorithm, the adaptive PSO algorithm features the better search efficiency and faster convergence speed over the global search. Two amplifiers were designed and implemented in a standard 0.11m CMOS process using MATLAB and HSPICE. Using the thermal noise coefficient and the corner frequency , this paper explored the noise design budget of low-power multistage amplifier in different saturation modes. Detailed optimization of the objective function and constraints are classified into the mono-objective case and the multi-objective case. The total running times of simulations are 5649 s and 6813 s while the errors are less than 9% and 10%, respectively. Compared with CODE, GAPF and DEPF algorithms, it can save more running time and improve the accuracy of the design. Moreover, it provides more design freedom for the trade-off among gain, the gain-bandwidth (GBW) product, noise and the phase margin under worst cases without extra tweaking. Not only can the methodology work in the 0.18m CMOS process, but also be migrated to the 0.11m CMOS process, even in the nanometer analog circuit. [ABSTRACT FROM AUTHOR]

With the growing demands of portable devices, it is necessary to pay attention to low-power digital integrated designs. This paper proposes a low-power MOS Current Mode Logic (MCML) design, termed as Hybrid Dynamic Current Mode Logic with modified current source (H-MDyCML). In H-MDyCML circuits, the functions are realized using complementary pass transistor logic which helps to overcome the problem of stacking of transistors in multiple levels. The dynamic current source has also been modified from an NMOS transistor to a PMOS transistor-driven current source which leads to the elimination of the use of CMOS inverter. H-MDyCML circuits are compared with other existing designing styles: Dynamic CML (DyCML), Hybrid DyCML (H-DyCML), and DyCML with modified current source (Dy-CML-NP). The proposed design (H-MDyCML) shows an overall improvement (in terms of Power Delay Product (PDP)) up to 94.77 % compared to DyCML, 52.17 % compared to Dy-CMLNP, and 91.40 % compared to H-DyCML, for single stage circuits. [ABSTRACT FROM AUTHOR]

As the key component of wireless network-on-chip (WiNoC), wireless router is required to handle a large number of data packets which could cause network congestion. The congestion not only reduces the network performance, but also results in additional power consumption. In this paper, a low-power WiNoC with congestion-aware wireless node is proposed. Firstly, flit counter unit and address resolution unit are added in wireless interface (WI), which can sense the congestion information and destination address information of each wireless node dynamically. Secondly, through the proposed congestion judgment algorithm, the congestion judgment unit in global network can judge the priority of each wireless node pair and set the highest-priority wireless node pair to use the channel resources preferentially. The mechanism can effectively alleviate the congestion of wireless nodes and ensure the stability of system performance. In addition, a sleep mechanism is utilized to switch off WI which fails in the wireless channel competition. Experimental results show that the proposed scheme can effectively improve the performance in terms of packets' transmission latency and network throughput. [ABSTRACT FROM AUTHOR]

This paper introduces a new class of microwave sensor architecture using direct conversion principle to eliminate data processing and provide low-power smart sensor nodes. Using a six-port circuit as the modulator, the sensing data are up-converted directly to a microwave frequency and sent by an antenna. At the receiver, a six-port circuit is used as a demodulator to down-convert the received signal and extract the sensing data. To predict the communication channel of the sensor network and provide a robust connection, a pilot sequence is sent along with the sensor data which is used in the calibration procedure at the receiver for accurate extraction of sensing data and making sensors smarter. Any kind of microwave sensors based on the variation of impedance can be used in the proposed structure. In this paper, the capacitive loading is used as a material sensor. By variation of material in the sensing area, the impedance of the load and reflection coefficient ($\Gamma$ ) are changed. Then, the amplitude and phase of $\Gamma$ are transmitted via the six-port circuit, received in the network base station, and analyzed to find the material changes. As an example, a system is fabricated and evaluated at 2.45 GHz. [ABSTRACT FROM AUTHOR]

One of the most significant agricultural tasks in beekeeping involves continually observing the conditions inside and outside the beehive. This is mainly performed for the early detection of some harmful events. There have been many studies on how to detect and prevent such occurrences by performing periodic interventions or, when the frequency of such actions is hard to enforce, by using sensory systems that record the temperature, humidity, and weight of the beehive. Nevertheless, such methods are inaccurate, and their delivered outcomes usually diverge from the actual event or false trigger and introduce more effort and damage. In this paper, the authors propose a new low-cost, low-power system called Bee Sound Detector (BeeSD). BeeSD is a low-cost, embedded solution for beehive quality control. It incorporates the sensors mentioned above as well as real-time sound monitoring. With the combination of temperature, humidity, and sound sensors, the BeeSD can spot Colony Collapse Disorder events due to famine and extreme weather events, queen loss, and swarming. Furthermore, as a system, the BeeSD uses cloud logging and an appropriate mobile phone application to push notifications of extreme measurements to the farmers. Based on achieved performance indicators, the authors present their BeeSD IoT device and system operation, focusing on its advantages of low-cost, low-power, and easy-to-install characteristics. [ABSTRACT FROM AUTHOR]

This paper investigates a novel highly stable and robust single-ended 10T SRAM cell appropriate for low-power portable applications. The cell core of the proposed design is a combination of a normal inverter with a stacked NMOS transistor and a Schmitt-trigger (ST) inverter with a double-length pull-up transistor. This improves hold stability and leakage power dissipation. The read and write operations of the proposed cell are performed with the aid of separated paths and bitlines, lowering power consumption. The strong cell core and decoupled read path eliminate the read-disturbance issue in the proposed cell, resulting in read static noise margin (RSNM) enhancement. Furthermore, the feedback-cutting write-assist technique used in the proposed design mitigates the writing '1' issue; consequently, write static noise margin (WSNM)/write margin (WM) improves. To prove the superiority of the proposed SRAM cell in various performance metrics, it is compared with state-of-the-art SRAM cells, introduced as 6T, TG9T, 10T-P1, and SB11T, using HSPICE and 16-nm CMOS technology node taking into consideration the impact of the severe process, voltage, and temperature (PVT) variations. Obtained results at VDD = 0.7 V show that the proposed design offers the highest HSNM/RSNM/WSNM (or WM). The read/write delay of the proposed cell is 3.92X/2.37X higher than that of the 6T SRAM cell due to its single-ended reading/writing structure. However, in terms of power consumption, the proposed cell exhibits 1.64X/1.54X lower than that of 6T SRAM cell. Though the proposed cell occupies a 1.24X higher area compared with the 6T SRAM cell due to its higher count of transistor, it shows the highest proposed figure of merit among all the studied SRAM cells, which is 26.90X higher than that of 6T SRAM cell. [ABSTRACT FROM AUTHOR]

In this paper, a small-area low-power 64-bit integer multiplier is presented, which is suitable for portable devices or wireless applications. To save the area cost and power consumption, an input vector systolic (IVS) structure is proposed based on four 16-bit radix-8 Booth multipliers and a data input scheme is proposed to reduce the number of signal transitions. This structure is similar to a systolic array in matrix multiply units of a Convolutional Neural Network (CNN), but it reduces the number of processing elements by 3/4 concerning the same vector systolic accelerator in reference. The comparison results prove that the IVS multiplier reduces at least 61.9% of the area and 45.18% of the power over its counterparts. To increase the hardware resource utilization, a Transverse Carry Array (TCA) structure for Partial Products Accumulation (PPA) was designed by replacing the 32-bit adders with 3/17-bit adders in the 16-bit multipliers. The experiment results show that the optimization could lead to at least a 6.32% and 13.65% reduction in power consumption and area cost, respectively, compared to the standard 16-bit radix-8 Booth multiplier. In the end, the precise scale of the proposed IVS multiplier is discussed. Benefiting from the modular design, the IVS multiplier can be configured to support sixteen different kinds of multiplications at a step of 16 bits [16b, 32b, 48b, 64b] × [16b, 32b, 48b, 64b]. [ABSTRACT FROM AUTHOR]

Sensitivity is a key parameter for microspeakers, especially in low-power applications such as consumer electronics, medical devices and Internet of Things. However, the sensitivities of most reported piezoelectric MEMS speakers are inferior to those of commercially available electrodynamic speakers. Design of high-sensitivity piezoelectric MEMS speakers requires an analytical expression of sensitivity, which is not yet available. In this paper, the analytical expression is derived, and an ultrahigh-sensitivity piezoelectric MEMS speaker is designed, fabricated and characterized. The sensitivities of the speaker in an ear simulator are 107 dB/mW, 104 dB/mW and 105 dB/mW at 250 Hz, 1 kHz and 10 kHz, respectively, which are the highest among piezoelectric MEMS speakers. The analytical calculation results and measurement data are perfectly matched. Furthermore, the speaker is based on thin-film AlN instead of commonly used thin-film PZT. This work demonstrates that the ultrahigh-sensitivity piezoelectric AlN MEMS speaker consumes 10 times less power than a typical 6 mm electrodynamic speaker; and the developed analytical expressions provide valuable design insights into piezoelectric MEMS speakers for high sensitivity and low power. [2022-0063] [ABSTRACT FROM AUTHOR]

In this paper, a new high-gain operational transconductance amplifier (OTA) circuit is designed. The proposed circuit uses bulk-driven technique to reduce the required supply voltage while gain-boosting as well as positive feedback techniques are used to increase the gain of the circuit and compensate the gain reduction effect due to the use of bulk-driven transistors. The performance of the proposed circuit is simulated using 180-nm CMOS technology parameters and is optimized using an optimization algorithm for the main purpose of minimizing the power consumption of the circuit. Simulated performance of the proposed circuit for 1.2 V DC supply voltage shows 94.8 dB gain, 203-MHz bandwidth, and slew-rate of 365-V/µS while occupying die area of 1360 µm2. However, the proposed circuit is also designed for a low-voltage scenario with 0.75 V DC supply voltage that results in 73.7 dB gain, 131-MHz bandwidth, and slew-rate of 149-V/µS. [ABSTRACT FROM AUTHOR]

High-efficiency video coding (HEVC) poses a considerable challenge to hardware implementation due to its complexity. Mobile devices are powered by batteries that are limited in capacity. Therefore, reducing the power consumption arising from the implementation of sophisticated coding tools in HEVC is an especially important issue for mobile devices. In particular, motion estimation (ME) is the major contributor to the power consumption of the encoder and the calculation of the sum of absolute difference (SAD) for ME consumes more than 50% of the total ME power. In this paper, a low-power motion estimation VLSI architecture is proposed based on a novel method of calculating the SAD. By reusing the calculation, the computation complexity and, hence, the power consumption are reduced. A low-power systolic processing elements array and a novel memory hierarchy are developed, which enable real-time processing of 8K resolution video with only half of the power consumption when compared with the state-of-the-art design. [ABSTRACT FROM AUTHOR]

In this paper, a two-stage dynamic comparator circuit is proposed, which considerably reduces the power consumption as well as the power-delay product parameter, while improves the speed. Furthermore, the performance of the pre-amplifier stage in the proposed design is improved which properly reduces the kick-back noise as well as the power consumption. The proposed circuit operates at 1 V supply at the clock frequency of 6 GHz (high-speed scenario), which results in the static and dynamic power consumption of 112.77 nW and 848 μW, respectively. Moreover, the delay of the circuit is 36.6 ps, while the output offset voltage is only 8 mV, with the kick-back noise of 48 mV. On the other hand, the circuit can operate at 1 V supply and frequency of 500 MHz (low-power scenario), which results in the reduced static and dynamic power consumption of 112.77 nW and 188.9 μW, respectively while the offset of the circuit can be reduced to only 1 mv at the delay of 46.4 ps and kick-back noise of 39.75 mV. [ABSTRACT FROM AUTHOR]