An ultra-low power CMOS random number generator

This paper proposes an ultra-low power CMOS random number generator (RING), which is based on an oscillator-sampling architecture. The noisy oscillator consists of a dual-drain MOS transistor, a noise generator and a voltage control oscillator. The dual-drain MOS transistor can bring extra-noise to the drain current or the output voltage so that the jitter of the oscillator is much larger than the normal oscillator. The frequency division ratio of the high-frequency sampling oscillator and the noisy oscillator is small. The RNG has been fabricated in a 0.35 mu m CMOS process. It can produce good quality bit streams without any post-processing. The bit rate of this RNG could be as high as 100 kbps. It has a typical ultra-low power dissipation of 0.91 mu W. This novel circuit is a promising unit for low power system and communication applications. (c) 2007 Elsevier Ltd. All rights reserved.

A novel ultra low power temperature sensor for UHF RFID tag chip

A novel ultra low power temperature sensor for UHF RFID tag chip is presented. The sensor consists of a constant pulse generator, a temperature related oscillator, a counter and a bias. Conversion of temperature to digital output is fulfilled by counting the number of the clocks of the temperature related oscillator in a constant pulse period. The sensor uses time domain comparing, where high power consumption bandgap voltage references and traditional ADCs are not needed. The sensor is realized in a standard 0.18 mu m CMOS process, and the area is only 0.2mm(2). The accuracy of the temperature sensor is +/- 1 degrees C after calibration. The power consumption of the sensor is only 0.9 mu W.

An Embedded Ultra Low Power Nonvolatile Memory in a Standard CMOS Logic Process

This paper proposes an embedded ultra low power nonvolatile memory in a standard CMOS logic process. The memory adopts a bit cell based on the differential floating gate PMOS structure and a novel operating scheme. It can greatly improve the endurance and retention characteristic and make the area/bit smaller. A new high efficiency all-PMOS charge pump is designed to reduce the power consumption and to increase the power efficiency. It eliminates the body effect and can generate higher output voltage than conventional structures for a same stage number. A 32-bit prototype chip is fabricated in a 0.18 mu m 1P4M standard CMOS logic process and the core area is 0.06 mm(2). The measured results indicate that the typical write/erase time is 10ms. With a 700 kHz clock frequency, power consumption of the whole memory is 2.3 mu A for program and 1.2 mu A for read at a 1.6V power supply.

An Ultra Low Power Non-volatile Memory in Standard CMOS Process for Passive RFID Tags

An ultra low power non-volatile memory is designed in a standard CMOS process for passive RFID tags. The memory can operate in a new low power operating scheme under a wide supply voltage and clock frequency range. In the charge pump circuit the threshold voltage effect of the switch transistor is almost eliminated and the pumping efficiency of the circuit is improved. An ultra low power 192-bit memory with a register array is implemented in a 0.18 mu M standard CMOS process. The measured results indicate that, for the supply voltage of 1.2 volts and the clock frequency of 780KHz, the current consumption of the memory is 1.8 mu A (3.6 mu A) at the read (write) rate of 1.3Mb/s (0.8Kb/s).

Improving the ultra-low-power performance of IEEE 802.15.6 by adaptive synchronisation

In ultra-low data rate wireless sensor networks (WSNs) waking up just to listen to a beacon every superframe can be a major waste of energy. This study introduces MedMAC, a medium access protocol for ultra-low data rate WSNs that achieves significant energy efficiency through a novel synchronisation mechanism. The new draft IEEE 802.15.6 standard for body area networks includes a sub-class of applications such as medical implantable devices and long-term micro miniature sensors with ultra-low power requirements. It will be desirable for these devices to have 10 years or more of operation between battery changes, or to have average current requirements matched to energy harvesting technology. Simulation results are presented to show that the MedMAC allows nodes to maintain synchronisation to the network while sleeping through many beacons with a significant increase in energy efficiency during periods of particularly low data transfer. Results from a comparative analysis of MedMAC and IEEE 802.15.6 MAC show that MedMAC has superior efficiency with energy savings of between 25 and 87 for the presented scenarios. © 2011 The Institution of Engineering and Technology.

Localization Algorithm Performance in Ultra Low Power Active RFID Based Patient Tracking

Indoor personnel localization research has generated a range of potential techniques and algorithms. However, these typically do not account for the influence of the user's body upon the radio channel. In this paper an active RFID based patient tracking system is demonstrated and three localization algorithms are used to estimate the location of a user within a modern office building. It is shown that disregarding body effects reduces the accuracy of the algorithms' location estimates and that body shadowing effects create a systematic position error that estimates the user's location as closer to the RFID reader that the active tag has line of sight to.

Inexact-aware architecture design for ultra-low power bio-signal analysis

This study introduces an inexact, but ultra-low power, computing architecture devoted to the embedded analysis of bio-signals. The platform operates at extremely low voltage supply levels to minimise energy consumption. In this scenario, the reliability of static RAM (SRAM) memories cannot be guaranteed when using conventional 6-transistor implementations. While error correction codes and dedicated SRAM implementations can ensure correct operations in this near-threshold regime, they incur in significant area and energy overheads, and should therefore be employed judiciously. Herein, the authors propose a novel scheme to design inexact computing architectures that selectively protects memory regions based on their significance, i.e. their impact on the end-to-end quality of service, as dictated by the bio-signal application characteristics. The authors illustrate their scheme on an industrial benchmark application performing the power spectrum analysis of electrocardiograms. Experimental evidence showcases that a significance-based memory protection approach leads to a small degradation in the output quality with respect to an exact implementation, while resulting in substantial energy gains, both in the memory and the processing subsystem.

Heterogeneous error-resilient scheme for spectral analysis in ultra-low power wearable electrocardiogram devices

Wearable devices performing advanced bio-signal analysis algorithms are aimed to foster a revolution in healthcare provision of chronic cardiac diseases. In this context, energy efficiency is of paramount importance, as long-term monitoring must be ensured while relying on a tiny power source. Operating at a scaled supply voltage, just above the threshold voltage, effectively helps in saving substantial energy, but it makes circuits, and especially memories, more prone to errors, threatening the correct execution of algorithms. The use of error detection and correction codes may help to protect the entire memory content, however it incurs in large area and energy overheads which may not be compatible with the tight energy budgets of wearable systems. To cope with this challenge, in this paper we propose to limit the overhead of traditional schemes by selectively detecting and correcting errors only in data highly impacting the end-to-end quality of service of ultra-low power wearable electrocardiogram (ECG) devices. This partition adopts the protection of either significant words or significant bits of each data element, according to the application characteristics (statistical properties of the data in the application buffers), and its impact in determining the output. The proposed heterogeneous error protection scheme in real ECG signals allows substantial energy savings (11% in wearable devices) compared to state-of-the-art approaches, like ECC, in which the whole memory is protected against errors. At the same time, it also results in negligible output quality degradation in the evaluated power spectrum analysis application of ECG signals.

Ultra-low power WSNs: distributed signal processing and dynamic resource management

This thesis presents several data processing and compression techniques capable of addressing the strict requirements of wireless sensor networks. After introducing a general overview of sensor networks, the energy problem is introduced, dividing the different energy reduction approaches according to the different subsystem they try to optimize. To manage the complexity brought by these techniques, a quick overview of the most common middlewares for WSNs is given, describing in detail SPINE2, a framework for data processing in the node environment. The focus is then shifted on the in-network aggregation techniques, used to reduce data sent by the network nodes trying to prolong the network lifetime as long as possible. Among the several techniques, the most promising approach is the Compressive Sensing (CS). To investigate this technique, a practical implementation of the algorithm is compared against a simpler aggregation scheme, deriving a mixed algorithm able to successfully reduce the power consumption. The analysis moves from compression implemented on single nodes to CS for signal ensembles, trying to exploit the correlations among sensors and nodes to improve compression and reconstruction quality. The two main techniques for signal ensembles, Distributed CS (DCS) and Kronecker CS (KCS), are introduced and compared against a common set of data gathered by real deployments. The best trade-off between reconstruction quality and power consumption is then investigated. The usage of CS is also addressed when the signal of interest is sampled at a Sub-Nyquist rate, evaluating the reconstruction performance. Finally the group sparsity CS (GS-CS) is compared to another well-known technique for reconstruction of signals from an highly sub-sampled version. These two frameworks are compared again against a real data-set and an insightful analysis of the trade-off between reconstruction quality and lifetime is given.

Progetto di un nodo sensore wireless ultra low-power per applicazioni di energy harvesting

Progetto di un nodo wireless, alimentato attraverso l'Energy Harvesting, in grado di misurare la temperatura ambiente ed inviarla ad un sistema ricevente che la visualizzerà su uno schermo LCD.

Ultra-Low Power and Non-intrusive Wireless Monitoring for Smart Buildings

Wireless Sensor Networks (WSNs) offer a new solution for distributed monitoring, processing and communication. First of all, the stringent energy constraints to which sensing nodes are typically subjected. WSNs are often battery powered and placed where it is not possible to recharge or replace batteries. Energy can be harvested from the external environment but it is a limited resource that must be used efficiently. Energy efficiency is a key requirement for a credible WSNs design. From the power source's perspective, aggressive energy management techniques remain the most effective way to prolong the lifetime of a WSN. A new adaptive algorithm will be presented, which minimizes the consumption of wireless sensor nodes in sleep mode, when the power source has to be regulated using DC-DC converters. Another important aspect addressed is the time synchronisation in WSNs. WSNs are used for real-world applications where physical time plays an important role. An innovative low-overhead synchronisation approach will be presented, based on a Temperature Compensation Algorithm (TCA). The last aspect addressed is related to self-powered WSNs with Energy Harvesting (EH) solutions. Wireless sensor nodes with EH require some form of energy storage, which enables systems to continue operating during periods of insufficient environmental energy. However, the size of the energy storage strongly restricts the use of WSNs with EH in real-world applications. A new approach will be presented, which enables computation to be sustained during intermittent power supply. The discussed approaches will be used for real-world WSN applications. The first presented scenario is related to the experience gathered during an European Project (3ENCULT Project), regarding the design and implementation of an innovative network for monitoring heritage buildings. The second scenario is related to the experience with Telecom Italia, regarding the design of smart energy meters for monitoring the usage of household's appliances.

Caratterizzazione e progettazione di un sistema di comunicazione con ultra low power long range transceiver

Lo sviluppo di nuove tecnologie sempre più innovative e all’avanguardia ha portato ad un processo di costante rivisitazione e miglioramento di sistemi tecnologici già esistenti. L’esempio di Internet risulta, a questo proposito, interessante da analizzare: strumento quotidiano ormai diventato alla portata di tutti, il suo processo di rivisitazione ha portato allo sviluppo dell’Internet Of Things (IoT), neologismo utilizzato per descrivere l'estensione di Internet a tutto ciò che può essere trasformato in un sistema elettronico, controllato attraverso la rete mondiale che oggi può essere facilmente fruibile grazie all’utilizzo di Smartphone sempre più performanti. Lo scopo di questa grande trasformazione è quello di creare una rete ad-hoc (non necessariamente con un accesso diretto alla rete internet tramite protocolli wired o wireless standard) al fine di stabilire un maggior controllo ed una maggiore sicurezza, alla quale è possibile interfacciare oggetti dotati di opportuni sensori di diverso tipo, in maniera tale da condividere dati e ricevere comandi da un operatore esterno. Un possibile scenario applicativo della tecnologia IoT, è il campo dell'efficienza energetica e degli Smart Meter. La possibilità di modificare i vecchi contatori del gas e dell’acqua, tutt’oggi funzionanti grazie ad una tecnologia che possiamo definire obsoleta, trasformandoli in opportuni sistemi di metring che hanno la capacità di trasmettere alla centrale le letture o i dati del cliente, di eseguire operazioni di chiusura e di apertura del servizio, nonché operazioni sulla valutazione dei consumi, permetterebbe al cliente di avere sotto controllo i consumi giornalieri. Per costruire il sistema di comunicazione si è utilizzato il modem Semtech SX1276, che oltre ad essere low-power, possiede due caratteristiche rivoluzionarie e all’avanguardia: utilizza una modulazione del segnale da trasmettere innovativa e una grande capacità di rilevare segnali immersi in forti fonti di rumore ; la possibilità di utilizzare due frequenze di trasmissione diverse, 169 MHz e 868MHz.

Ultra low power analog-to-information conversion by short-time compressed sensing

Il compressed sensing è un’innovativa tecnica per l’acquisizione dei dati, che mira all'estrazione del solo contenuto informativo intrinseco di un segnale. Ciò si traduce nella possibilità di acquisire informazione direttamente in forma compressa, riducendo la quantità di risorse richieste per tale operazione. In questa tesi è sviluppata un'architettura hardware per l'acquisizione di segnali analogici basata sul compressed sensing, specializzata al campionamento con consumo di potenza ridotto di segnali biomedicali a basse frequenze. Lo studio è svolto a livello di sistema mediante l'integrazione della modulazione richiesta dal compressed sensing in un convertitore analogico-digitale ad approssimazioni successive, modificandone la logica di controllo. Le prestazioni risultanti sono misurate tramite simulazioni numeriche e circuitali. Queste confermano la possibilità di ridurre la complessità hardware del sistema di acquisizione rispetto allo stato dell'arte, senza alterarne le prestazioni.