7 research outputs found

    Technology aware circuit design for smart sensors on plastic foils

    Get PDF

    Circuit design in complementary organic technologies

    Get PDF

    A low power wideband varactorless VCO using tunable active inductor

    Get PDF
    This paper presents a wideband varactorless voltage controlled oscillator (VCO) based on tunable active inductor in 90 nm CMOS process which yields a tuning range of 1.22 GHz to 3.7 GHz having a tuning scope of 100.5%. The designed VCO can be used for wideband wireless applications. The proposed VCO consumes a very low power (1.05 ~ 2.5) mW with the change of tuning voltages (0.3 ~ 0.9) V and provides a differential output power of (1.17 ~ -5.13) dBm. The VCO exhibits phase noise of -80.50 dBc/[email protected] GHz and the Figure of Merit (FOM) is -147.73 dBc/Hz @2.74 GHz at 1MHz offset frequency. Achievement of high tuning range by altering the inductance of inductor which paves the way for eliminating the MOS varactor that recedes the overall silicon area consumption, is the noteworthy outcome of the proposed VCO. Furthermore, considering the dc power consumption, figure of merit (FOM) and consistency of performance parameters over tuning range, the proposed VCO outstrips the other referred VCOs

    Shifting the Frontiers of Analog and Mixed-Signal Electronics

    Get PDF

    Circuit design for low-cost smart sensing applications based on printed flexible electronics

    Get PDF

    An organic VCO-Based ADC for quasi-static signals achieving 1LSB INL at 6b resolution

    No full text
    Smart sensors embedded in packaging films for food or pharmaceuticals, and read out using RFID protocols, are an important future application of large-area organic electronics. The first steps towards flexible organic electronics were code generators for RFID tags [1]. To realize flexible smart sensors it is also essential to develop analog sensor interfaces and ADCs, which will enable the integration of sensors, data processing and RF communication (Fig. 6.6.1) on the same plastic foil [2]. This paper focuses on the design of an organic ADC for quasi-static signals, like the ones provided by chemical and temperature sensors. Only a few ADCs made with organic TFTs (OTFTs) have been reported [3,4] so far. Their linearity is limited by the poor matching typical of organic technologies and reached an INL of 2.6LSB at 6b resolution before calibration. This paper addresses an ADC whose linearity is not related to the matching of OTFTs or capacitances, but relies on the electrical properties of a transconductor. Even without calibration, the INL is 1LSB and the DNL is 0.6LSB at 6b resolution. The converter is manufactured in a double-gate p-type OTFT technology [5], which provides two gates to control the semiconductor channel, G and TG (Fig. 6.6.1): a voltage applied to the top gate TG produces a linearly proportional shift of the threshold voltage

    Collective Communications and Computation Mechanisms on the RF Channel for Organic Printed Smart Labels and Resource-limited IoT Nodes

    Get PDF
    Radio Frequency IDentification (RFID) and Wireless Sensor Networks (WSN) are seen as enabler technologies for realizing the Internet of Things (IoT). Organic and printed Electronics (OE) has the potential to provide low cost and all-printable smart RFID labels in high volumes. With regard to WSN, power harvesting techniques and resource-efficient communications are promising key technologies to create sustainable and for the environment friendly sensing devices. However, the implementation of OE smart labels is only allowing printable devices of ultra-low hardware complexity, that cannot employ standard RFID communications. And, the deployment of current WSN technology is far away from offering battery-free and low-cost sensing technology. To this end, the steady growth of IoT is increasing the demand for more network capacity and computational power. With respect to wireless communications research, the state-of-the-art employs superimposed radio transmission in form of physical layer network coding and computation over the MAC to increase information flow and computational power, but lacks on practicability and robustness so far. With regard to these research challenges we developed in particular two approaches, i.e., code-based Collective Communications for dense sensing environments, and time-based Collective Communications (CC) for resource-limited WSNs. In respect to the code-based CC approach we exploit the principle of superimposed radio transmission to acquire highly scalable and robust communications obtaining with it at the same time as well minimalistic smart RFID labels, that can be manufactured in high volume with present-day OE. The implementation of our code-based CC relies on collaborative and simultaneous transmission of randomly drawn burst sequences encoding the data. Based on the framework of hyper-dimensional computing, statistical laws and the superposition principle of radio waves we obtained the communication of so called ensemble information, meaning the concurrent bulk reading of sensed values, ranges, quality rating, identifiers (IDs), and so on. With 21 transducers on a small-scale reader platform we tested the performance of our approach successfully proving the scalability and reliability. To this end, we implemented our code-based CC mechanism into an all-printable passive RFID label down to the logic gate level, indicating a circuit complexity of about 500 transistors. In respect to time-based CC approach we utilize the superimposed radio transmission to obtain resource-limited WSNs, that can be deployed in wide areas for establishing, e.g., smart environments. In our application scenario for resource-limited WSN, we utilize the superimposed radio transmission to calculate functions of interest, i.e., to accomplish data processing directly on the radio channel. To prove our concept in a case study, we created a WSN with 15 simple nodes measuring the environmental mean temperature. Based on our analysis about the wireless computation error we were able to minimize the stochastic error arbitrarily, and to remove the systematic error completely
    corecore