3,070 research outputs found
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EcoBlock: Grid Impacts, Scaling, and Resilience
Widespread deployment of EcoBlocks has the potential to transform today's electricity system into one that is more resilient, flexible, efficient and sustainable. In this vision, the system will consist of self- su cient, renewable-powered, block-scale entities that can deliberately adjust their net power exchange and can optimize performance, maintain stability, support each other, or disconnect entirely from the grid as needed. This report is intended as an independent analysis of the potential relationships, both constructive and adverse, between EcoBlocks and the grid
Distribution automation applications of fiber optics
Motivations for interest and research in distribution automation are discussed. The communication requirements of distribution automation are examined and shown to exceed the capabilities of power line carrier, radio, and telephone systems. A fiber optic based communication system is described that is co-located with the distribution system and that could satisfy the data rate and reliability requirements. A cost comparison shows that it could be constructed at a cost that is similar to that of a power line carrier system. The requirements for fiber optic sensors for distribution automation are discussed. The design of a data link suitable for optically-powered electronic sensing is presented. Empirical results are given. A modeling technique that was used to understand the reflections of guided light from a variety of surfaces is described. An optical position-indicator design is discussed. Systems aspects of distribution automation are discussed, in particular, the lack of interface, communications, and data standards. The economics of distribution automation are examined
Simultaneous wireless information and power transfer (SWIPT) in cooperative networks
2019 Spring.Includes bibliographical references.In recent years, the capacity and charging speed of batteries have become the bottleneck of mobile communications systems. Energy harvesting (EH) is regarded as a promising technology to significantly extend the lifetime of battery-powered devices. Among many EH technologies, simultaneous wireless information and power transfer (SWIPT) proposes to harvest part of the energy carried by the wireless communication signals. In particular, SWIPT has been successfully applied to energy-constrained relays that are mainly or exclusively powered by the energy harvested from the received signals. These relays are known as EH relays, which attract significant attention in both the academia and the industry. In this research, we investigate the performance of SWIPT-based EH cooperative networks and the optimization problems therein. Due to hardware limitations, the energy harvesting circuit cannot decode the signal directly. Power splitting (PS) is a popular and effective solution to this problem. Therefore, we focus on PS based SWIPT in this research. First, different from existing work that employs time-switching (TS) based SWIPT, we propose to employ PS based SWIPT for a truly full-duplex (FD) EH relay network, where the information reception and transmission take place simultaneously at the relay all the time. This more thorough exploitation of the FD feature consequently leads to a significant capacity improvement compared with existing alternatives in the literature. Secondly, when multiple relays are available in the network, we explore the relay selection (RS) and network beamforming techniques in EH relay networks. Assuming orthogonal bandwidth allocation, both single relay selection (SRS) and general relay selection (GRS) without the limit on the number of cooperating relays are investigated and the corresponding RS methods are proposed. We will show that our proposed heuristic GRS methods outperform the SRS methods and achieve very similar performance compared with the optimal RS method achieved by exhaustive search but with dramatically reduced complexity. Under the shared bandwidth assumption, network beamforming among EH relays is investigated. We propose a joint PS factor optimization method based on semidefinite relaxation. Simulations show that network beamforming achieves the best performance among all other cooperative techniques. Finally, we study the problem of power allocation and PS factor optimization for SWIPT over doubly-selective wireless channels. In contrast to existing work in the literature, we take the channel variation in both time and frequency domains into consideration and jointly optimize the power allocation and the PS factors. The objective is to maximize the achievable data rate with constraints on the delivered energy in a time window. Since the problem is difficult to solve directly due to its nonconvexity, we proposed a two-step approach, named joint power allocation and splitting (JoPAS), to solve the problem along the time and frequency dimensions sequentially. Simulations show significantly improved performance compared with the existing dynamic power splitting scheme. A suboptimal heuristic algorithm, named decoupled power allocation and splitting (DePAS), is also proposed with significantly reduced computational complexity and simulations demonstrate its near-optimum performance
Public and private roles in road infrastructure: an exploration of market failure, public instruments and government failure
Starting with a 'greenfield' situation, we discuss reasons for market failure in road infrastructure provision. We show why it may not be optimal from a welfare perspective to leave road provision fully to the market and government intervention in this sector can improve welfare. Government intervention comes in different forms, such as financial intervention (taxation, subsidies), regulation (price, quality, environmental), and public provision of roads or road services. The analysis of the literature regarding government instruments allows us to establish a correspondence between different forms of market failure and instruments. Several case studies of particular road infrastructure projects are included to illustrate the use of government instruments.
Interference mitigation using group decoding in multiantenna systems
fi=vertaisarvioitu|en=peerReviewed
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Leveraging Backscatter for Ultra-low Power Wireless Sensing Systems
The past few years have seen a dramatic growth in wireless sensing systems, with millions of wirelessly connected sensors becoming first-class citizens of the Internet. The number of wireless sensing devices is expected to surpass 6.75 billion by 2017, more than the world\u27s population as well as the combined market of smartphones, tablets, and PCs. However, its growth faces two pressing challenges: battery energy density and wireless radio power consumption. Battery energy density looms as a fundamental limiting factor due to slow improvements over the past several decades (3x over 22 years). Wireless radio power consumption is another key challenge because high-speed wireless communication is often far more expensive energy-wise than computation, storage and sensing. To make matters worse, wireless sensing devices are generating an increasing amount of data. These challenges raise a fundamental question --- how should we power and communicate with wireless sensing devices. More specifically, instead of using batteries, can we leverage other energy sources to reduce, if not eliminate, the dependence on batteries? Similarly, instead of optimizing existing wireless radios, can we fundamentally change how radios transmit wireless signals to achieve lower power consumption? A promising technique to address these questions is backscatter --- a primitive that enables RF energy harvesting and ultra-low-power wireless communication. Backscatter has the potential to reduce dependence on batteries because it can obtain energy by rectifying the wireless signals transmitted by a backscatter reader. Backscatter can also work by reflecting existing wireless signals (WiFi, BLE) when these are available nearby. Because signal reflection only consumes uWs of power, backscatter can enable ultra-low-power wireless communication. However, the use of backscatter for communicating with wireless sensing devices presents several challenges. First, decreasing RF power across distance limits the operational range of micro-powered backscatter devices. This raises the question of how to maintain a communication link with a backscatter device despite tiny amount of harvested power. Second, even though the backscatter RF front-end is extremely power-efficient, the computational and sensing overhead on backscatter sensors limit its ability to operate with a few micro-Watts of power. Such overhead is a negligible factor of overall power consumption for platforms where radio power consumption is high (e.g. WiFi or Bluetooth based devices). However, it becomes the bottleneck for backscatter based platforms. Third, backscatter readers are not currently deployed in existing indoor environments to provide a continuous carrier for carrying backscattered information. As a result, backscatter deployment is not yet widespread. This thesis addresses these challenges by making the following contributions. First, we design a network stack that enables continuous operation despite decreasing harvested power across distance by employing an OS abstraction --- task fragmentation. We show that such a network stack enables packet transfer even when the whole system is powered by a 3cmx3cm solar panel under natural indoor light condition. Second, we design a hardware architecture that minimizes the computational overhead of backscatter to enable over 1Mbps backscatter transmission while consuming less than 100uWs of power, a two order of magnitude improvement over the state-of-the-art. Finally, we design a system that can leverage both ambient WiFi and BLE signals for backscatter. Our empirical evaluation shows that we can backscatter 500bps data on top of a WiFi stream and 50kbps data on top of a Bluetooth stream when the backscatter device is 3m away from the commercial WiFi and Bluetooth receivers
Efficient DSP and Circuit Architectures for Massive MIMO: State-of-the-Art and Future Directions
Massive MIMO is a compelling wireless access concept that relies on the use
of an excess number of base-station antennas, relative to the number of active
terminals. This technology is a main component of 5G New Radio (NR) and
addresses all important requirements of future wireless standards: a great
capacity increase, the support of many simultaneous users, and improvement in
energy efficiency. Massive MIMO requires the simultaneous processing of signals
from many antenna chains, and computational operations on large matrices. The
complexity of the digital processing has been viewed as a fundamental obstacle
to the feasibility of Massive MIMO in the past. Recent advances on
system-algorithm-hardware co-design have led to extremely energy-efficient
implementations. These exploit opportunities in deeply-scaled silicon
technologies and perform partly distributed processing to cope with the
bottlenecks encountered in the interconnection of many signals. For example,
prototype ASIC implementations have demonstrated zero-forcing precoding in real
time at a 55 mW power consumption (20 MHz bandwidth, 128 antennas, multiplexing
of 8 terminals). Coarse and even error-prone digital processing in the antenna
paths permits a reduction of consumption with a factor of 2 to 5. This article
summarizes the fundamental technical contributions to efficient digital signal
processing for Massive MIMO. The opportunities and constraints on operating on
low-complexity RF and analog hardware chains are clarified. It illustrates how
terminals can benefit from improved energy efficiency. The status of technology
and real-life prototypes discussed. Open challenges and directions for future
research are suggested.Comment: submitted to IEEE transactions on signal processin
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