A 423.5-450 MHz low-power OOK/FSK/QPSK wireless transmitter is proposed with multi-phase injection locking and frequency multiplication techniques. A low-frequency phase-rotation-based frequency synthesizer is employed to provide multichannel support and FSK modulation. The far-out phase noise caused by the quantization noise of the$\Delta \Sigma $modulator is filtered through a proposed N-path filter and two-stage injection-locked ring oscillators (ILROs). Phase modulation is achieved by changing the offset frequency between the oscillator free-running frequency and the injected frequency to control the steady-state phase offset of the injection-locked oscillator. Finally, a current mode class-D edge-combining power amplifier with high energy efficiency is used to achieve 5X frequency multiplication to generate the required carrier frequency. A prototype transmitter is fabricated in TSMC 90 nm CMOS process. It is shown that the device delivers an output power of −7 dBm with a power consumption of$870 \mu \text{W}$under a 0.75 V supply voltage and supports data rates of 40/5/80 Mbps under OOK/BFSK/QPSK modulation, respectively, achieving the energy efficiency of 11 pJ/bit and 23% global efficiency.

Fundamental limits on the error probability of the social learning rule proposed by Lalitha et al. [1] and its variants for decentralized detection over a directed graph is investigated. We show that while social learning algorithms enjoy the benefits that each node in the graph weights the messages received from its neighbors locally to form its private belief and only requires knowledge of the data generating distributions of its own observation, it suffers a gap in the achievable error exponent compared to the centralized case. We propose a generalization of the social learning rule achieving the error exponent in centralized detection with the aid of slight global knowledge. A further analysis reveals that the price of decentralization is at most a constant term in the higher-order asymptotics. To obtain the slight global knowledge needed at each node for achieving the centralized error exponent, we develop a decentralized estimation method for each node to come up with a local estimate of that piece of global knowledge.

For implanted neural-sensing devices, one of the remaining challenges is to transmit stable power/data (P/D) transmission for high spatiotemporal resolution neural data. This paper presents a miniaturized implantable 128-channel wireless neural-sensing microsystem using TSV-embedded dissolvable μ-needle array, a flexible interposer and 4 dies by 2.5D/3D TSV heterogeneous SiP technology. The 4 dies are 2 neural-signal acquisition ICs implemented by 90nm CMOS, 1 neural-signal processor by 40nm CMOS and 1 wireless P/D transmission circuitry by 0.18μm CMOS. Thus, the proposed wireless microsystem realizes 128-channel neural-signal sensing within the area of 5mm × 5mm, neural feature extraction and wireless P/D transmission using an on-interposer inductor. The overall average power of the circuits in this microsystem is only 9.85mW.

With the increasing demand of super high scale of integration and small form factor in advanced semiconductor products, especially those that integrate DRAM and logic dies, 3D IC and Wafer-Level Chip-Scale Packaging (WLCSP) are considered promising approaches. In Integrated Fan-Out (InFO) WLCSP, a large number of fine-pitch pads, where neighboring pads cannot be probed simultaneously due to insufficient pitch, are used as the contact interfaces of inter-die interconnections. If the fine-pitch pads cannot be probed, the interconnections between the pads and boundary scan cells (BSCs) cannot be tested, which can lead to higher defect level. From industrial investigation, untested fine-pitch pads lead to 1-2% test coverage loss. To improve the overall test coverage, in this paper, we propose a pre-bond probing methodology for fine-pitch pads of InFO WLCSP. By the proposed probing schemes, open/short faults on the interconnects between the fine-pitch pads and BSCs can be all tested by the ATE. Moreover, for short faults that only occur between adjacent pads (interconnects), we propose a grouping method to determine the test patterns at each probing stage, which can minimize the test time. We also show that our method can achieve 100% test coverage of open/short faults.

Highly integrated neural sensing microsystems are crucial to capture accurate signals for brain function investigations. In this paper, a 256-channel/25 mm2 neural sensing microsystem is presented based on through-silicon-via (TSV) 2.5D integration. This microsystem composes of dissolvable μ-needles, TSV-embedded μ-probes, 256-channel neural amplifiers, 11-bit area-power-efficient SAR ADCs and serializers. Based on the dissolvable μ-needles and TSV 2.5D integration, this microsystem can detect 256 ECoG/LFP signals within the small area of 5mm × 5mm. Additionally, the neural amplifier realizes 57.8dB gain with only 9.8μW for each channel, and the 9.7-bit ENOB of the SAR ADC at 32kS/s can be achieved with 0.42μW and 0.036 mm2. The overall power of this microsystem is only 3.79mW for 256-channel neural sensing.

This paper presents a wireless on-lens intraocular pressure monitoring system, comprising a capacitance-to-digital converter and a wirelessly powered radio-frequency identification (RFID)-compatible communication system, for sensor control and data communication. The capacitive sensor was embedded on a soft contact lens of 200 μm thickness using commercially available biocompatible lens material, to improve compliance and reduce user discomfort. The sensor chip was shown to achieve effective number of bits greater than 10 over a capacitance range up to 50 pF while consuming only 64-μW power. The on-lens capacitive sensor could detect dielectric variation caused by changes in water content from a distance of 2 cm by using incident power from an RFID reader at 20 dBm. The maximum detectable distance was 11 cm with 30-dBm incident RF power. The rise in eye tissue temperature under 30-dBm RF exposure over an interval of 1 s was simulated and found to be less than 0.01°C.

Healthcare issues arose from population aging. Meanwhile, electrocardiogram (ECG) is a powerful measurement tool. The first step of ECG is to detect QRS complexes. A state-of-the-art QRS detection algorithm was modified and implemented. By the dedicated architecture design, the novel ASIC is proposed with 2.21 μW power consumption and 0.68mm2core area. It is the smallest QRS detection ASIC so far in the world. In addition, the positive prediction of the ASIC is 99.36% based on the MIT/BIH arrhythmia database certification.

Spectrum sensing is considered to be one of the most important tasks in cognitive radio. Many sensing detectors have been proposed in the literature, with the common assumption that the primary user is either fully present or completely absent within the window of observation. In reality, there are scenarios where the primary user signal only occupies a fraction of the observed window. This paper aims to analyse the effect of the primary user duty cycle on spectrum sensing performance through the analysis of a few common detectors. Simulations show that the probability of detection degrades severely with reduced duty cycle regardless of the detection method. Furthermore we show that reducing the duty cycle has a greater degradation on performance than lowering the signal strength.

The rapid advance of semiconductor technology exposes multifrequency designs to severe reliability loss due to incomplete at-speed testing, which is induced by ignorance of timing-related defects between clocks. However, the reduced testability caused by core-based design strategy also aggravates the difficulty in applying on-chip at-speed testing. Although previous works were able to successfully increase the quality of the at-speed testing, the diversity of on-chip clock control schemes from different components may complicate the test integration, increasing the test costs. Therefore, to accelerate the time-to-market and the time-to-volume, the development of a plug-and-play at-speed testing based on a well-defined test interface has become increasingly urgent. In this paper, a fast test integration approach for multi-clock-domain at-speed testing based on IEEE Standard 1500 is proposed. The proposed framework has been successfully integrated into an IEEE 1500-wrapped ultrawide-band design and a simple SoC design. Experiment results also confirm the feasibility of the proposed approach.

Heart rate variability (HRV) is a measure of variation in the heart rate. Over the last 25 years, HRV analysis has became utilized more often as a non-invasive research and clinical tool for indirectly investigating both cardiac and autonomic nervous system (ANS) functions in health and disease. In our experiment, 22 healthy subjects and four testing rhythm patterns are studied. How the three musical-rhythmic characteristics of tempo, complexity and drum sample affect the performance of HRV is discussed and a computational model with four factors is proposed. This relationship can help us to improve our life and health by music.

Branch power equalization and increased system robustness against antenna orientation in transmit polarization diversity systems is achieved through the precoded transmission of elliptical polarization. Elliptical polarization offers two main benefits over traditional polarization diversity systems. Firstly, it is able to facilitate power coupling between orthogonal polarizations and reduce the system sensitivity to antenna orientation. Secondly, when the operation parameters for elliptical polarization are chosen carefully based on channel information, branch power equalization is achieved for arbitrary transmitter orientation. In this paper, we articulate the parameters which need to be precoded at the transmitter to achieve power balance. The closed form solutions for optimal cross polarization discrimination are presented, assuming the full knowledge of channel statistics.

A JPEG XR chip for HD-Photo is implemented with 25 mm2area in TSMC 0.18 um CMOS 1P6M technology at 100 MHz. According to the simulation results, the 4:4:4 1920x1080 HD-Photo 20 frames/sec can be encoded smoothly.

Heart rate variability (HRV) is a measure of variations in the heart rate. Over the last 25 years, HRV analysis has became popular as a non-invasive research and clinical tool for indirectly investigating both cardiac and autonomic nervous system (ANS) function in both health and disease area. How the musical rhythmic characteristics, tempo and complexity, affect the performance of HRV is studied in this work. By understanding the relationship between music and the function of ANS, the novel biomedical entertainment platform is proposed and used for relaxation.