889 resultados para Wireless power transmission


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In this letter, we consider wireless powered communication networks which could operate perpetually, as the base station (BS) broadcasts energy to the multiple energy harvesting (EH) information transmitters. These employ “harvest then transmit” mechanism, as they spend all of their energy harvested during the previous BS energy broadcast to transmit the information towards the BS. Assuming time division multiple access (TDMA), we propose a novel transmission scheme for jointly optimal allocation of the BS broadcasting power and time sharing among the wireless nodes, which maximizes the overall network throughput, under the constraint of average transmit power and maximum transmit power at the BS. The proposed scheme significantly outperforms “state of the art” schemes that employ only the optimal time allocation. If a single EH transmitter is considered, we generalize the optimal solutions for the case of fixed circuit power consumption, which refers to a much more practical scenario.

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Parallel combinatory orthogonal frequency division multiplexing (PC-OFDM yields lower maximum peak-to-average power ratio (PAR), high bandwidth efficiency and lower bit error rate (BER) on Gaussian channels compared to OFDM systems. However, PC-OFDM does not improve the statistics of PAR significantly. In this chapter, the use of a set of fixed permutations to improve the statistics of the PAR of a PC-OFDM signal is presented. For this technique, interleavers are used to produce K-1 permuted sequences from the same information sequence. The sequence with the lowest PAR, among K sequences is chosen for the transmission. The PAR of a PC-OFDM signal can be further reduced by 3-4 dB by this technique. Mathematical expressions for the complementary cumulative density function (CCDF)of PAR of PC-OFDM signal and interleaved PC-OFDM signal are also presented.

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A wireless sensor network system must have the ability to tolerate harsh environmental conditions and reduce communication failures. In a typical outdoor situation, the presence of wind can introduce movement in the foliage. This motion of vegetation structures causes large and rapid signal fading in the communication link and must be accounted for when deploying a wireless sensor network system in such conditions. This thesis examines the fading characteristics experienced by wireless sensor nodes due to the effect of varying wind speed in a foliage obstructed transmission path. It presents extensive measurement campaigns at two locations with the approach of a typical wireless sensor networks configuration. The significance of this research lies in the varied approaches of its different experiments, involving a variety of vegetation types, scenarios and the use of different polarisations (vertical and horizontal). Non–line of sight (NLoS) scenario conditions investigate the wind effect based on different vegetation densities including that of the Acacia tree, Dogbane tree and tall grass. Whereas the line of sight (LoS) scenario investigates the effect of wind when the grass is swaying and affecting the ground-reflected component of the signal. Vegetation type and scenarios are envisaged to simulate real life working conditions of wireless sensor network systems in outdoor foliated environments. The results from the measurements are presented in statistical models involving first and second order statistics. We found that in most of the cases, the fading amplitude could be approximated by both Lognormal and Nakagami distribution, whose m parameter was found to depend on received power fluctuations. Lognormal distribution is known as the result of slow fading characteristics due to shadowing. This study concludes that fading caused by variations in received power due to wind in wireless sensor networks systems are found to be insignificant. There is no notable difference in Nakagami m values for low, calm, and windy wind speed categories. It is also shown in the second order analysis, the duration of the deep fades are very short, 0.1 second for 10 dB attenuation below RMS level for vertical polarization and 0.01 second for 10 dB attenuation below RMS level for horizontal polarization. Another key finding is that the received signal strength for horizontal polarisation demonstrates more than 3 dB better performances than the vertical polarisation for LoS and near LoS (thin vegetation) conditions and up to 10 dB better for denser vegetation conditions.

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The Midwest Independent Transmission System Operator (MISO) has experienced significant amounts of wind power development within the last decade. The MISO footprint spans the majority of the upper Midwest region of the country, from the Dakotas to Indiana and as far east as Michigan. These areas have a rich wind energy resource. States in the MISO footprint have passed laws or set goals that require load serving entities to supply a portion of their load using renewable energy. In order to meet these requirements, significant investments are needed to build the transmission infrastructure necessary to deliver the power from these often remote wind energy resources to the load centers. This paper presents some of the transmission planning related work done at MISO which was largely influenced by current and future needs for increased wind power generation in the footprint. Specifically, topics covered are generator interconnection, long-term planning coordination, and cost-allocation for new transmission lines.

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Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.

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A comparison of relay power minimisation subject to received signal-to-noise ratio (SNR) at the receiver and SNR maximisation subject to the total transmitted power of relays for a typical wireless network with distributed beamforming is presented. It is desirable to maximise receiver quality-of-service (QoS) and also to minimise the cost of transmission in terms of power. Hence, these two optimisation problems are very common and have been addressed separately in the literature. It is shown that SNR maximisation subject to power constraint and power minimisation subject to SNR constraint yield the same results for a typical wireless network. It proves that either one of the optimisation approaches is sufficient.

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Sensor networks for environmental monitoring present enormous benefits to the community and society as a whole. Currently there is a need for low cost, compact, solar powered sensors suitable for deployment in rural areas. The purpose of this research is to develop both a ground based wireless sensor network and data collection using unmanned aerial vehicles. The ground based sensor system is capable of measuring environmental data such as temperature or air quality using cost effective low power sensors. The sensor will be configured such that its data is stored on an ATMega16 microcontroller which will have the capability of communicating with a UAV flying overhead using UAV communication protocols. The data is then either sent to the ground in real time or stored on the UAV using a microcontroller until it lands or is close enough to enable the transmission of data to the ground station.

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Wireless adhoc networks transmit information from a source to a destination via multiple hops in order to save energy and, thus, increase the lifetime of battery-operated nodes. The energy savings can be especially significant in cooperative transmission schemes, where several nodes cooperate during one hop to forward the information to the next node along a route to the destination. Finding the best multi-hop transmission policy in such a network which determines nodes that are involved in each hop, is a very important problem, but also a very difficult one especially when the physical wireless channel behavior is to be accounted for and exploited. We model the above optimization problem for randomly fading channels as a decentralized control problem - the channel observations available at each node define the information structure, while the control policy is defined by the power and phase of the signal transmitted by each node. In particular, we consider the problem of computing an energy-optimal cooperative transmission scheme in a wireless network for two different channel fading models: (i) slow fading channels, where the channel gains of the links remain the same for a large number of transmissions, and (ii) fast fading channels, where the channel gains of the links change quickly from one transmission to another. For slow fading, we consider a factored class of policies (corresponding to local cooperation between nodes), and show that the computation of an optimal policy in this class is equivalent to a shortest path computation on an induced graph, whose edge costs can be computed in a decentralized manner using only locally available channel state information (CSI). For fast fading, both CSI acquisition and data transmission consume energy. Hence, we need to jointly optimize over both these; we cast this optimization problem as a large stochastic optimization problem. We then jointly optimize over a set of CSI functions of the local channel states, and a c- - orresponding factored class of control poli.

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Many wireless applications demand a fast mechanism to detect the packet from a node with the highest priority ("best node") only, while packets from nodes with lower priority are irrelevant. In this paper, we introduce an extremely fast contention-based multiple access algorithm that selects the best node and requires only local information of the priorities of the nodes. The algorithm, which we call Variable Power Multiple Access Selection (VP-MAS), uses the local channel state information from the accessing nodes to the receiver, and maps the priorities onto the receive power. It is based on a key result that shows that mapping onto a set of discrete receive power levels is optimal, when the power levels are chosen to exploit packet capture that inherently occurs in a wireless physical layer. The VP-MAS algorithm adjusts the expected number of users that contend in each step and their respective transmission powers, depending on whether previous transmission attempts resulted in capture, idle channel, or collision. We also show how reliable information regarding the total received power at the receiver can be used to improve the algorithm by enhancing the feedback mechanism. The algorithm detects the packet from the best node in 1.5 to 2.1 slots, which is considerably lower than the 2.43 slot average achieved by the best algorithm known to date.

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We consider an optimal power and rate scheduling problem for a multiaccess fading wireless channel with the objective of minimising a weighted sum of mean packet transmission delay subject to a peak power constraint. The base station acts as a controller which, depending upon the buffer lengths and the channel state of each user, allocates transmission rate and power to individual users. We assume perfect channel state information at the transmitter and the receiver. We also assume a Markov model for the fading and packet arrival processes. The policy obtained represents a form of Indexability.

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This paper describes an approach for the analysis and design of 765kV/400kV EHV transmission system which is a typical expansion in Indian power grid system, based on the analysis of steady state and transient over voltages. The approach for transmission system design is iterative in nature. The first step involves exhaustive power flow analysis, based on constraints such as right of way, power to be transmitted, power transfer capabilities of lines, existing interconnecting transformer capabilities etc. Acceptable bus voltage profiles and satisfactory equipment loadings during all foreseeable operating conditions for normal and contingency operation are the guiding criteria. Critical operating strategies are also evolved in this initial design phase. With the steady state over voltages obtained, comprehensive dynamic and transient studies are to be carried out including switching over voltages studies. This paper presents steady state and switching transient studies for alternative two typical configurations of 765kV/400 kV systems and the results are compared. Transient studies are carried out to obtain the peak values of 765 kV transmission systems and are compared with the alternative configurations of existing 400 kV systems.

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A common and practical paradigm in cooperative communication systems is the use of a dynamically selected `best' relay to decode and forward information from a source to a destination. Such systems use two phases - a relay selection phase, in which the system uses transmission time and energy to select the best relay, and a data transmission phase, in which it uses the spatial diversity benefits of selection to transmit data. In this paper, we derive closed-form expressions for the overall throughput and energy consumption, and study the time and energy trade-off between the selection and data transmission phases. To this end, we analyze a baseline non-adaptive system and several adaptive systems that adapt the selection phase, relay transmission power, or transmission time. Our results show that while selection yields significant benefits, the selection phase's time and energy overhead can be significant. In fact, at the optimal point, the selection can be far from perfect, and depends on the number of relays and the mode of adaptation. The results also provide guidelines about the optimal system operating point for different modes of adaptation. The analysis also sheds new insights on the fast splitting-based algorithm considered in this paper for relay selection.

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The use of energy harvesting (EH) nodes as cooperative relays is a promising and emerging solution in wireless systems such as wireless sensor networks. It harnesses the spatial diversity of a multi-relay network and addresses the vexing problem of a relay's batteries getting drained in forwarding information to the destination. We consider a cooperative system in which EH nodes volunteer to serve as amplify-and-forward relays whenever they have sufficient energy for transmission. For a general class of stationary and ergodic EH processes, we introduce the notion of energy constrained and energy unconstrained relays and analytically characterize the symbol error rate of the system. Further insight is gained by an asymptotic analysis that considers the cases where the signal-to-noise-ratio or the number of relays is large. Our analysis quantifies how the energy usage at an EH relay and, consequently, its availability for relaying, depends not only on the relay's energy harvesting process, but also on its transmit power setting and the other relays in the system. The optimal static transmit power setting at the EH relays is also determined. Altogether, our results demonstrate how a system that uses EH relays differs in significant ways from one that uses conventional cooperative relays.

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This paper is concerned with the influence of different levels of complexity in modelling various constituent subsystems on the dynamic stability of power systems compensated by static var systems (SVS) operating on pure voltage control. The system components investigated include thyristor controlled reactor (TCR) transients, SVS delays, network transients, the synchronous generator and automatic voltage regulator (AVR). An overall model is proposed which adequately describes the system performance for small signal perturbations. The SVS performance is validated through detailed nonlinear simulation on a physical simulator.