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Summary: The PLL‐based charge control scheme is optimized and implemented in a single‐inductor multiple‐output (SIMO) Buck DC‐DC in this paper. In order to decrease cross regulation (CR) during heavy load transient, the gain adaptive charge pump (GACP) is optimized to speed up the regulation of inductor current, and the current loop off‐time (CLOT) control is introduced to prevent the PLL‐based structure from frequency unlock. The proposed SIMO is designed in a 0.18 μm standard CMOS process. Experimental results show that the worst CR performance is 0.026 mV/mA, which is a 50% improvement of PLL‐based charge control scheme and 61.19% advantage above the existing charge‐controlled SIMO. [ABSTRACT FROM AUTHOR]

This article presents a novel hybrid bidirectional buck–boost converter (HBBC) for lithium-ion battery management. Unlike the conventional four-switch buck–boost converter (FBBC), whose power efficiency is greatly limited at heavy loads mainly due to high conduction loss from a high dc resistance (DCR) inductor, the proposed HBBC adopts assisted capacitive paths to reduce the current stress on the main inductive path. Thus, the conductive loss of inductor's DCR is greatly reduced in both the buck and boost modes. To verify the effectiveness of the proposed structure, detailed analyses on both the loop performance and conduction loss are provided. Compared with FBBC, the conversion efficiency of the proposed HBBC is increased by 23.3% in the boost mode, and the peak efficiency is up to 97.8% with an adopted inductor with a DCR of 270 mΩ. [ABSTRACT FROM AUTHOR]

Recently, Graph Neural Networks (GNNs) using aggregating neighborhood collaborative information have shown effectiveness in recommendation. However, GNNs-based models suffer from over-smoothing and data sparsity problems. Due to its self-supervised nature, contrastive learning has gained considerable attention in the field of recommendation, aiming at alleviating highly sparse data. Graph contrastive learning models are widely used to learn the consistency of representations by constructing different graph augmentation views. Most current graph augmentation with random perturbation destroy the original graph structure information, which mislead embeddings learning. In this paper, an effective graph contrastive learning paradigm CollaGCL is proposed, which constructs graph augmentation by using singular value decomposition to preserve crucial structure information. CollaGCL enables perturbed views to effectively capture global collaborative information, mitigating the negative impact of graph structural perturbations. To optimize the contrastive learning task, the extracted meta-knowledge was propagate throughout the original graph to learn reliable embedding representations. The self-information learning between views enhances the semantic information of nodes, thus alleviating the problem of over-smoothing. Experimental results on three real-world datasets demonstrate the significant improvement of CollaGCL over state-of-the-art methods. [ABSTRACT FROM AUTHOR]

This paper introduces a hybrid inductor‐current sensor with fast response and high accuracy using online calibration for 25 MHz BUCK DC‐DC converter. The proposed inductor‐current sensor combines the high accuracy of the senseFET sensing method with the lossless and real‐time response characteristics of the RC filter technique. Comparing to exist techniques, the proposed calibration scheme can make filter coefficient converge even in unsteady state, which improve its effectiveness in practical application. Moreover, the proposed inductor‐current sensor utilizes sample‐based senseFET‐based current sensing to offer calibration reference, which avoid the use of high bandwidth amplifier. Digital current balance control is seamlessly integrated into the 25 MHz 2‐phase digital adaptive time‐controlled (AOT) BUCK DC‐DC converter through the utilization of the proposed hybrid inductor‐current sensor. The 2‐phase BUCK DC‐DC converter is implemented in a standard 0.18‐µm CMOS process. After online calibration, proposed hybrid inductor‐current sensor outputs a full‐wave waveform with high accuracy and low propagation delay of only 9 ns in post‐layout simulation. [ABSTRACT FROM AUTHOR]

This article presents a capacitor‐less low dropout (LDO) regulator with a high power supply rejection (PSR) for system‐on‐chip (SoC) applications. With the proposed adaptive bulk‐driven feedforward (ABDFF) technique, in which the ripples are injected adaptively to the bulk of power transistor, the LDO maintains a steady PSR enhancement in wide load conditions, and a lower quiescent current and faster load transient response are realized. Post‐layout simulation results show that the proposed LDO regulator achieves −75‐dB PSR at 1 MHz from 1 to 100 mA and 60‐fs figure of merit (FoM) with a 100‐pF load capacitor. [ABSTRACT FROM AUTHOR]

In this work, a low cost Bluetooth Low Energy (BLE) transceiver for wireless sensor network (WSN) applications, with a receiver (RX)-matching network-reusing power amplifier (PA) load inductor, is presented. In order to decrease the die area, only two inductors were used in this work. Besides the one used in the voltage control oscillator (VCO), the PA load inductor was reused as the RX impedance matching component in the front-end. Proper controls have been applied to achieve high transmitter (TX) input impedance when the transceiver is in the receiving mode, and vice versa. This allows the TRX-switch/matching network integration without significant performance degradation. The RX adopted a low-IF structure and integrated a single-ended low noise amplifier (LNA), a current bleeding mixer, a 4th complex filter and a delta-sigma continuous time (CT) analog-to-digital converter (ADC). The TX employed a two-point PLL-based architecture with a non-linear PA. The RX achieved a sensitivity of -93 dBm and consumes 9.7 mW, while the TX achieved a 2.97% error vector magnitude (EVM) with 9.4 mW at 0 dBm output power. This design was fabricated in a 0.11 μm complementary metal oxide semiconductor (CMOS) technology and the front-end circuit only occupies 0.24 mm². The measurement results verify the effectiveness and applicability of the proposed BLE transceiver for WSN applications.