A. James Clark School of Engineering
Permanent URI for this communityhttp://hdl.handle.net/1903/1654
The collections in this community comprise faculty research works, as well as graduate theses and dissertations.
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Item Design of a Quasi-Adiabatic Current-Mode Neurostimulator Integrated Circuit for Deep Brain Stimulation(2018) Mandal, Arindam; Newcomb, Robert W; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Electrical stimulation of neural tissues is a valuable tool in the retinal prosthesis, cardiac pacemakers, and Deep Brain Stimulation (DBS). DBS is being to treat a growing number of neurological disorders, such as movement disorder, epilepsy, and Parkinson’s disease. The role of the electronic stimulator is paramount in such application, and significant design challenges are to be met to enhance safety and reliability. A current-source based stimulator can accurately deliver a charge-balanced stimulus maintaining patient safety. In this thesis, a general-purpose current-mode neurostimulator (CMS) based upon a new quasi-adiabatic driving technique is proposed which can theoretically achieve more than 80% efficiency with the help of a dynamic high voltage supply (DHVS) as opposed to most conventional general-purpose CMS having less than 25% efficiency. The high-voltage supply is required to withstand the voltage seen across the electrodes (>10V) due to the time-varying impedance presented by the electrode-tissue interface. The overall efficiency of the designed CMS is limited by the efficiency of the DHVS. A HVDD of 15V is created by the DHVS from an input voltage (VDD) of 3V. The DHVS circuit is made by cascading five charge pump circuits using the AMI 0.5µm CMOS process. It can maintain more than 60% efficiency for a wide range of load current from 25µA to 1.4mA, with peak efficiency at 67% and this is comparable with existing specific-purpose state-of-the-art high-voltage supplies used in a current stimulator. The stimulator designed in this thesis employs a new efficient charge recycling mechanism to enhance the overall efficiency, compared to the existing state-of-the-art CMSs. Thus, the overall CMS efficiency is improved by 20% to 25%. A current source, programmable by 8-bit digital input, is also designed which has an output impedance greater than 2MΩ with a dropout voltage of only 120mV. Measurements show voltage compliance exceeding +/-15V when driving a biphasic current stimulus of 10µA to 2.5mA through a simplified R-C model of the electrode-tissue interface. The voltage compliance is defined as the maximum voltage a stimulator can apply across the electrodes to achieve neural stimulation.Item Energy Efficiency and Privacy Protection in Cellular Networks(2014) Ta, Tuan Minh; Baras, John S; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Smartphones have become an essential part of our society. The benefits of having an always present, highly capable device cannot be overstated. As more aspects of our life depend on our smartphones, it is more important than ever to ensure the availability of those devices. However, their big advantages also come with big risks. The fact that we have our smartphones with us all the time means that it is easier than ever to collect our information, sometimes without our consent. In this dissertation, we study the two pressing concerns in cellular communications: energy efficiency and privacy protection. We focus on LTE networks, the current most advanced global standard for cellular communications. In the first part of the dissertation, we study the energy efficiency problem from both device and network perspectives. From the device point of view, we introduce a new angle to address the battery life concern. We recognize that the value of battery for the users is not always the same, and that it depends on the user usage. We also identify, and show in real network, diversity of usage, the phenomenon that at any instant, there is a diverse distribution of smartphone usage among cellular users. We propose ``Battery Deposit Service'' (BDS), a cooperative system which makes use of device-to-device (D2D) communications underlaying cellular networks to provide energy sharing in the form of load sharing. We design BDS to take advantage of diversity of usage to maximize the utility of smartphone battery. We show that our system increases battery life of cellular users, at almost no cost to the rest of the network. BDS is designed to be compatible to LTE architecture. From the network point of view, we design an energy efficient D2D relay system underlaying LTE networks. We minimize transmission power of smartphones by considering relay selection, resource allocation and power control. The overall problem is prohibited due to its exponential search space. We develop a divide-and-conquer strategy which splits the overall problem into small sub-problems. We relate these sub-problems to well-studied graph theoretic problems, and take advantage of existing fast algorithms. We show that our algorithms meet the runtime requirement of real-time LTE operations. In the second part of the dissertation, we address a privacy concern in LTE networks. In particular, we show that user location can be leaked in current LTE paging architecture. We propose a mechanism based on signal processing to remedy this vulnerability. Our method makes use of physical layer identification, which are low-power tags embedded on the wireless waveform, to signal paging messages to user devices. We show that our method is stealthy and robust, and that it mitigates the aforementioned privacy issue.Item GUARANTEE DESIGN ON ENERGY PERFORMANCE CONTRACTS UNDER UNCERTAINTY(2011) Deng, Qianli; Cui, Qingbin; Jiang, Xianglin; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Due to the growing concerns with climate change and energy supply, Energy Performance Contracting (EPC), which uses the guaranteed future utility savings to repay the initial renovation investments, becomes increasingly popular. However, most Energy Service Companies (ESCOs) set the savings guarantee roughly based on their previous experience, which leads to inaccurate estimates in practice. This paper has built the stochastic models for the savings risks both from the energy price volatility and the facility performance instability, which follow the Geometric Brownian Motions (GBM) and Ito's lemma. Then, a flexible guarantee designing method for ESCOs is developed to minimize the financial risks and a case study has been conducted to show the application. Finally, suggestions have been made for how ESCOs set the guarantee and the extra profit sharing proportion in contracts based on the existing information. This method will help them appropriately allocate risks with successful contract negotiation.Item DELAY MINIMIZATION IN ENERGY CONSTRAINED WIRELESS COMMUNICATIONS(2010) Yang, Jing; Ulukus, Sennur; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In wireless communications and networks, especially for many real-time applications, the average delay packets experience is an important quality of service criterion. Therefore, it is imperative to design advanced transmission schemes to jointly address the goals of reliability, high rates and low delay. Achieving these objectives often requires careful allocation of given resources, such as energy, power, rate, among users. It also requires a close collaboration between physical layer, medium access control layer, and upper layers, and yields cross-layer solutions. We first investigate the problem of minimizing the overall transmission delay of packets in a multiple access wireless communication system, where the transmitters have average power constraints. We formulate the problem as a constrained optimization problem, and then transform it into a linear programming problem. We show that the optimal policy has a threshold structure: when the sum of the queue lengths is larger than a threshold, both users should transmit a packet during the current slot; when the sum of the queue lengths is smaller than a threshold, only one of the users, the one with the longer queue, should transmit a packet during the current slot. Then, we study the delay-optimal rate allocation in a multiple access wireless communication system. Our goal is to allocate rates to users, from the multiple access capacity region, based on their current queue lengths, in order to minimize the average delay of the system. We formulate the problem as a Markov decision problem (MDP) with an average cost criterion. We first show that the value function is increasing, symmetric and convex in the queue length vector. Taking advantage of these properties, we show that the optimal rate allocation policy is one which tries to equalize the queue lengths as much as possible in each slot, while working on the dominant face of the capacity region. Next, we extend the delay-optimal rate allocation problem to a communication channel with two transmitters and one receiver, where the underlying rate region is approximated as a general pentagon. We show that the delay-optimal policy has a switch curve structure. For the discounted-cost problem, we prove that the switch curve has a limit along one of the dimensions. The existence of a limit in the switch curve along one of the dimensions implies that, once the queue state is beyond the limit, the system always operates at one of the corner points, implying that the queues can be operated partially distributedly. Next, we shift our focus from the average delay minimization problem to transmission completion time minimization problem in energy harvesting communication systems. We first consider the optimal packet scheduling problem in a single-user energy harvesting wireless communication system. In this system, both the data packets and the harvested energy are modeled to arrive at the source node randomly. Our goal is to adaptively change the transmission rate according to the traffic load and available energy, such that the time by which all packets are delivered is minimized. Under a deterministic system setting, we develop an optimal off-line scheduling policy which minimizes the transmission completion time, under causality constraints on both data and energy arrivals. Then, we investigate the transmission completion time minimization problem in a two-user additive white Gaussian noise (AWGN) broadcast channel, where the transmitter is able to harvest energy from the nature. We first analyze the structural properties of the optimal transmission policy. We prove that the optimal total transmit power has the same structure as the optimal single-user transmit power. We also prove that there exists a cut-off power level for the stronger user. If the optimal total transmit power is lower than this level, all transmit power is allocated to the stronger user, and when the optimal total transmit power is larger than this level, all transmit power above this level is allocated to the weaker user. Based on these structural properties of the optimal policy, we propose an algorithm that yields the globally optimal off-line scheduling policy. Next, we investigate the transmission completion time minimization problem in a two-user AWGN multiple access channel. We first develop a generalized iterative backward waterfilling algorithm to characterize the maximum departure region of the transmitters for any given deadline. Then, based on the sequence of maximum departure regions at energy arrival epochs, we decompose the transmission completion time minimization problem into a convex optimization problem and solve it efficiently. Finally, we investigate the average delay minimization problem in a single-user communication channel with an energy harvesting transmitter. We consider three different cases. In the first case, both the data packets and the energy to be used to transmit them are assumed to be available at the transmitter at the beginning. In the second case, while the energy is available at the transmitter at the beginning, packets arrive during the transmissions. In the third case, the packets are available at the transmitter at the beginning and the energy arrives during the transmissions, as a result of energy harvesting. In each scenario, we find the structural properties of the optimal solution, and develop iterative algorithms to obtain the solution.Item Design Space Exploration for Energy-Efficient Secure Sensor Network(IEEE, 2002-07) Yuan, Lin; Qu, GangWe consider two of the most important design issues for distributed sensor networks in the battlefield: security for communication in such hostile terrain; and energy efficiency because of battery’s limited capacity and the impracticality of recharging. Communication security is normally provided by encryption, i.e., data are encrypted before transmission and will be decrypted first on reception. We exploit the secure sensor network design space for energy efficiency by investigating different microprocessors coupled with various public key algorithms. We propose a power control mechanism for sensors to operate at an energy-efficient fashion using the newly developed dynamical voltage scaling (DVS) technique. In particular, we consider multiple voltage processors and insert additional information into the communication channel to guide the selection of proper voltages for data decryption/encryption and processing in order to reduce the total computational energy consumption. We experiment several encryption standards on a broad range of embedded processors and simulate the behavior of the sensor network to show that the sensor’s lifetime can be extended substantially.Item SELF ORGANIZING WIRELESS SENSOR NETWORKS(2007-10-26) Kordari, Kamiar; Blankenship, Gilmer L; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation is concerned with the properties of self-organizing network systems, where a large number of distributed sensor nodes with limited sensing, processing and communication capability organize themselves into a cooperative network without any centralized control or management. Due to the distributed nature of the management and lack of global information for in-node decision making, sensor management in such networks is a complicated task. The dynamics of such networks are characterized by constraints and uncertainty, and the presence of disturbances that significantly affect aggregate system behavior. In this dissertation we examine several important topics in the management of self-organizing wireless sensor networks. The first topic is a statistical analysis to determine the minimum requirements for the deployment phase of a random sensor network to achieve a desired degree of coverage and connectivity. The second topic focuses on the development of a viable online sensor management methodology in the absence of global information. We consider consensus based sensor data fusion as a motivating problem to demonstrate the capability of the sensor management algorithms. The approach that has been widely investigated in the literature for this problem is the fusion of information from all the sensors. It does not involve active control of the sensors as part of the algorithm. Our approach is to control the operations of the nodes involved in the consensus process by associating costs with each node to emphasize those with highest payoff. This approach provides a practical, low complexity algorithm that allows the nodes to optimize their operations despite the lack of global information. In the third topic we have studied sensor networks that include "leaders," "followers," and "disrupters." The diffusion of information in a network where there are conflicting strategies is investigated through simulations. These results can be used to develop algorithms to manage the roles in the network in order to optimize the diffusion of information as well as protect the network against disruption.