2,933 research outputs found

    Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks

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    Cognitive radio has been widely considered as one of the prominent solutions to tackle the spectrum scarcity. While the majority of existing research has focused on single-band cognitive radio, multiband cognitive radio represents great promises towards implementing efficient cognitive networks compared to single-based networks. Multiband cognitive radio networks (MB-CRNs) are expected to significantly enhance the network's throughput and provide better channel maintenance by reducing handoff frequency. Nevertheless, the wideband front-end and the multiband spectrum access impose a number of challenges yet to overcome. This paper provides an in-depth analysis on the recent advancements in multiband spectrum sensing techniques, their limitations, and possible future directions to improve them. We study cooperative communications for MB-CRNs to tackle a fundamental limit on diversity and sampling. We also investigate several limits and tradeoffs of various design parameters for MB-CRNs. In addition, we explore the key MB-CRNs performance metrics that differ from the conventional metrics used for single-band based networks.Comment: 22 pages, 13 figures; published in the Proceedings of the IEEE Journal, Special Issue on Future Radio Spectrum Access, March 201

    Design Techniques for Energy-Quality Scalable Digital Systems

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    Energy efficiency is one of the key design goals in modern computing. Increasingly complex tasks are being executed in mobile devices and Internet of Things end-nodes, which are expected to operate for long time intervals, in the orders of months or years, with the limited energy budgets provided by small form-factor batteries. Fortunately, many of such tasks are error resilient, meaning that they can toler- ate some relaxation in the accuracy, precision or reliability of internal operations, without a significant impact on the overall output quality. The error resilience of an application may derive from a number of factors. The processing of analog sensor inputs measuring quantities from the physical world may not always require maximum precision, as the amount of information that can be extracted is limited by the presence of external noise. Outputs destined for human consumption may also contain small or occasional errors, thanks to the limited capabilities of our vision and hearing systems. Finally, some computational patterns commonly found in domains such as statistics, machine learning and operational research, naturally tend to reduce or eliminate errors. Energy-Quality (EQ) scalable digital systems systematically trade off the quality of computations with energy efficiency, by relaxing the precision, the accuracy, or the reliability of internal software and hardware components in exchange for energy reductions. This design paradigm is believed to offer one of the most promising solutions to the impelling need for low-energy computing. Despite these high expectations, the current state-of-the-art in EQ scalable design suffers from important shortcomings. First, the great majority of techniques proposed in literature focus only on processing hardware and software components. Nonetheless, for many real devices, processing contributes only to a small portion of the total energy consumption, which is dominated by other components (e.g. I/O, memory or data transfers). Second, in order to fulfill its promises and become diffused in commercial devices, EQ scalable design needs to achieve industrial level maturity. This involves moving from purely academic research based on high-level models and theoretical assumptions to engineered flows compatible with existing industry standards. Third, the time-varying nature of error tolerance, both among different applications and within a single task, should become more central in the proposed design methods. This involves designing “dynamic” systems in which the precision or reliability of operations (and consequently their energy consumption) can be dynamically tuned at runtime, rather than “static” solutions, in which the output quality is fixed at design-time. This thesis introduces several new EQ scalable design techniques for digital systems that take the previous observations into account. Besides processing, the proposed methods apply the principles of EQ scalable design also to interconnects and peripherals, which are often relevant contributors to the total energy in sensor nodes and mobile systems respectively. Regardless of the target component, the presented techniques pay special attention to the accurate evaluation of benefits and overheads deriving from EQ scalability, using industrial-level models, and on the integration with existing standard tools and protocols. Moreover, all the works presented in this thesis allow the dynamic reconfiguration of output quality and energy consumption. More specifically, the contribution of this thesis is divided in three parts. In a first body of work, the design of EQ scalable modules for processing hardware data paths is considered. Three design flows are presented, targeting different technologies and exploiting different ways to achieve EQ scalability, i.e. timing-induced errors and precision reduction. These works are inspired by previous approaches from the literature, namely Reduced-Precision Redundancy and Dynamic Accuracy Scaling, which are re-thought to make them compatible with standard Electronic Design Automation (EDA) tools and flows, providing solutions to overcome their main limitations. The second part of the thesis investigates the application of EQ scalable design to serial interconnects, which are the de facto standard for data exchanges between processing hardware and sensors. In this context, two novel bus encodings are proposed, called Approximate Differential Encoding and Serial-T0, that exploit the statistical characteristics of data produced by sensors to reduce the energy consumption on the bus at the cost of controlled data approximations. The two techniques achieve different results for data of different origins, but share the common features of allowing runtime reconfiguration of the allowed error and being compatible with standard serial bus protocols. Finally, the last part of the manuscript is devoted to the application of EQ scalable design principles to displays, which are often among the most energy- hungry components in mobile systems. The two proposals in this context leverage the emissive nature of Organic Light-Emitting Diode (OLED) displays to save energy by altering the displayed image, thus inducing an output quality reduction that depends on the amount of such alteration. The first technique implements an image-adaptive form of brightness scaling, whose outputs are optimized in terms of balance between power consumption and similarity with the input. The second approach achieves concurrent power reduction and image enhancement, by means of an adaptive polynomial transformation. Both solutions focus on minimizing the overheads associated with a real-time implementation of the transformations in software or hardware, so that these do not offset the savings in the display. For each of these three topics, results show that the aforementioned goal of building EQ scalable systems compatible with existing best practices and mature for being integrated in commercial devices can be effectively achieved. Moreover, they also show that very simple and similar principles can be applied to design EQ scalable versions of different system components (processing, peripherals and I/O), and to equip these components with knobs for the runtime reconfiguration of the energy versus quality tradeoff

    On Regularity and Integrated DFM Metrics

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    Transistor geometries are well into the nanometer regime, keeping with Moore's Law. With this scaling in geometry, problems not significant in the larger geometries have come to the fore. These problems, collectively termed variability, stem from second-order effects due to the small geometries themselves and engineering limitations in creating the small geometries. The engineering obstacles have a few solutions which are yet to be widely adopted due to cost limitations in deploying them. Addressing and mitigating variability due to second-order effects comes largely under the purview of device engineers and to a smaller extent, design practices. Passive layout measures that ease these manufacturing limitations by regularizing the different layout pitches have been explored in the past. However, the question of the best design practice to combat systematic variations is still open. In this work we explore considerations for the regular layout of the exclusive-OR gate, the half-adder and full-adder cells implemented with varying degrees of regularity. Tradeoffs like complete interconnect unidirectionality, and the inevitable introduction of vias are qualitatively analyzed and some factors affecting the analysis are presented. Finally, results from the Calibre Critical Feature Analysis (CFA) of the cells are used to evaluate the qualitative analysis

    Gallium-Nitride Efficacy for High-Reliability Forward Converters in Spacecraft

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    Gallium Nitride (GaN) devices show particular promise for space-rated power conversion applications that rely on MOSFET technology whose performance is severely limited by the radiation hardening processes. Though GaN failure mode classification and radiation hardened device variety is limited, the current space-rated selection pool can still yield significant efficiency and power density improvements. However, the context of GaN research is often future oriented such that the application of GaN to common, proven, space-rated converter designs is rare. The presented work quantifies the performance benefits of market available, space-rated GaN HEMTs over radiation hardened MOSFETs for a synchronous forward converter, which remains an extremely popular topology for isolated, medium power, DC-DC conversion on NASA satellite systems. Two 75-Watt, space-rated forward converters were designed, implemented, and benchmarked, with the power switch technology being the single variable of change. By forming pareto-optimal fronts of the key device metrics, optimal Rad-hard MOSFETs were chosen so that the baseline converter performance was considered best-case. The frequency limitations of common, available, Rad-hard PWM controllers limited power density in the GaN and Si converter alike, however, efficiency gains proved sizeable. The GaN based converter saw a peak efficiency of 86%, which was a 4.54% improvement over the Si baseline. Detailed efficiency and loss differential plots are presented which show the GaN converter’s reduced sensitivity to input voltage. Extreme similarity between the waveforms and functional characteristics of the two converters verified the design of the experiment. Furthermore, the performance of the baseline Si converter proved very similar to that of a large sampling of space-rated forward converters, making the experimental results have a high degree of utility for manufacturers

    Hierarchical Agent-based Adaptation for Self-Aware Embedded Computing Systems

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    Siirretty Doriast

    SRAM Cells for Embedded Systems

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