Energy-Efficient Communication over the Unsynchronized Gaussian Diamond Network

Communication networks are often designed and analyzed assuming tight synchronization among nodes. However, in applications that require communication in the energy-efficient regime of low signal-to-noise ratios, establishing tight synchronization among nodes in the network can result in a significant energy overhead. Motivated by a recent result showing that near-optimal energy efficiency can be achieved over the AWGN channel without requiring tight synchronization, we consider the question of whether the potential gains of cooperative communication can be achieved in the absence of synchronization. We focus on the symmetric Gaussian diamond network and establish that cooperative-communication gains are indeed feasible even with unsynchronized nodes. More precisely, we show that the capacity per unit energy of the unsynchronized symmetric Gaussian diamond network is within a constant factor of the capacity per unit energy of the corresponding synchronized network. To this end, we propose a distributed relaying scheme that does not require tight synchronization but nevertheless achieves most of the energy gains of coherent combining.Comment: 20 pages, 4 figures, submitted to IEEE Transactions on Information Theory, presented at IEEE ISIT 201

Ultra-Low-Power Uwb Impulse Radio Design: Architecture, Circuits, And Applications

Recent advances in home healthcare, environmental sensing, and low power computing have created a need for wireless communication at very low power for low data rate applications. Due to higher energy/bit requirements at lower data -rate, achieving power levels low enough to enable long battery lifetime (~10 years) or power-harvesting supplies have not been possible with traditional approaches. Dutycycled radios have often been proposed in literature as a solution for such applications due to their ability to shut off the static power consumption at low data rates. While earlier radio nodes for such systems have been proposed based on a type of sleepwake scheduling, such implementations are still power hungry due to large synchronization uncertainty (~1[MICRO SIGN]s). In this dissertation, we utilize impulsive signaling and a pulse-coupled oscillator (PCO) based synchronization scheme to facilitate a globally synchronized wireless network. We have modeled this network over a widely varying parameter space and found that it is capable of reducing system cost as well as providing scalability in wireless sensor networks. Based on this scheme, we implemented an FCC compliant, 3-5GHz, timemultiplexed, dual-band UWB impulse radio transceiver, measured to consume only 20[MICRO SIGN]W when the nodes are synchronized for peer-peer communication. At the system level the design was measured to consume 86[MICRO SIGN]W of power, while facilitating multi- hop communication. Simple pulse-shaping circuitry ensures spectral efficiency, FCC compliance and ~30dB band-isolation. Similarly, the band-switchable, ~2ns turn-on receiver implements a non-coherent pulse detection scheme that facilitates low power consumption with -87dBm sensitivity at 100Kbps. Once synchronized the nodes exchange information while duty-cycling, and can use any type of high level network protocols utilized in packet based communication. For robust network performance, a localized synchronization detection scheme based on relative timing and statistics of the PCO firing and the timing pulses ("sync") is reported. No active hand-shaking is required for nodes to detect synchronization. A self-reinforcement scheme also helps maintain synchronization even in the presence of miss-detections. Finally we discuss unique ways to exploit properties of pulse coupled oscillator networks to realize novel low power event communication, prioritization, localization and immediate neighborhood validation for low power wireless sensor applications

Performance and energy efficiency in wireless self-organized networks

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Application of advanced on-board processing concepts to future satellite communications systems

An initial definition of on-board processing requirements for an advanced satellite communications system to service domestic markets in the 1990's is presented. An exemplar system architecture with both RF on-board switching and demodulation/remodulation baseband processing was used to identify important issues related to system implementation, cost, and technology development

Simultaneous Positioning and Communications: Hybrid Radio Architecture, Estimation Techniques, and Experimental Validation

abstract: Limited spectral access motivates technologies that adapt to diminishing resources and increasingly cluttered environments. A joint positioning-communications system is designed and implemented on \acf{COTS} hardware. This system enables simultaneous positioning of, and communications between, nodes in a distributed network of base-stations and unmanned aerial systems (UASs). This technology offers extreme ranging precision ($<$ 5 cm) with minimal bandwidth (10 MHz), a secure communications link to protect against cyberattacks, a small form factor that enables integration into numerous platforms, and minimal resource consumption which supports high-density networks. The positioning and communications tasks are performed simultaneously with a single, co-use waveform, which efficiently utilizes limited resources and supports higher user densities. The positioning task uses a cooperative, point-to-point synchronization protocol to estimate the relative position and orientation of all users within the network. The communications task distributes positioning information between users and secures the positioning task against cyberattacks. This high-performance system is enabled by advanced time-of-arrival estimation techniques and a modern phase-accurate distributed coherence synchronization algorithm. This technology may be installed in ground-stations, ground vehicles, unmanned aerial systems, and airborne vehicles, enabling a highly-mobile, re-configurable network with numerous applications.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Brain at work : time, sparseness and superposition principles

Abstract : Many studies explored mechanisms through which the brain encodes sensory inputs allowing a coherent behavior. The brain could identify stimuli via a hierarchical stream of activity leading to a cardinal neuron responsive to one particular object. The opportunity to record from numerous neurons offered investigators the capability of examining simultaneously the functioning of many cells. These approaches suggested encoding processes that are parallel rather than serial. Binding the many features of a stimulus may be accomplished through an induced synchronization of cell’s action potentials. These interpretations are supported by experimental data and offer many advantages but also several shortcomings. We argue for a coding mechanism based on a sparse synchronization paradigm. We show that synchronization of spikes is a fast and efficient mode to encode the representation of objects based on feature bindings. We introduce the view that sparse synchronization coding presents an interesting venue in probing brain encoding mechanisms as it allows the functional establishment of multilayered and time-conditioned neuronal networks or multislice networks. We propose a model based on integrate-and-fire spiking neurons

Mapping and Merging Using Sound and Vision : Automatic Calibration and Map Fusion with Statistical Deformations

Over the last couple of years both cameras, audio and radio sensors have become cheaper and more common in our everyday lives. Such sensors can be used to create maps of where the sensors are positioned and the appearance of the surroundings. For sound and radio, the process of estimating the sender and receiver positions from time of arrival (TOA) or time-difference of arrival (TDOA) measurements is referred to as automatic calibration. The corresponding process for images is to estimate the camera positions as well as the positions of the objects captured in the images. This is called structure from motion (SfM) or visual simultaneous localisation and mapping (SLAM). In this thesis we present studies on how to create such maps, divided into three parts: to find accurate measurements; robust mapping; and merging of maps.The first part is treated in Paper I and involves finding precise – on a subsample level – TDOA measurements. These types of subsample refinements give a high precision, but are sensitive to noise. We present an explicit expression for the variance of the TDOA estimate and study the impact that noise in the signals has. Exact measurements is an important foundation for creating accurate maps. The second part of this thesis includes Papers II–V and covers the topic of robust self-calibration using one-dimensional signals, such as sound or radio. We estimate both sender and receiver positions using TOA and TDOA measurements. The estimation process is divided in two parts, where the first is specific for TOA or TDOA and involves solving a relaxed version of the problem. The second step is common for different types of problems and involves an upgrade from the relaxed solution to the sought parameters. In this thesis we present numerically stable minimal solvers for both these steps for some different setups with senders and receivers. We also suggest frameworks for how to use these solvers together with RANSAC to achieve systems that are robust to outliers, noise and missing data. Additionally, in the last paper we focus on extending self-calibration results, especially for the sound source path, which often cannot be fully reconstructed immediately. The third part of the thesis, Papers VI–VIII, is concerned with the merging of already estimated maps. We mainly focus on maps created from image data, but the methods are applicable to sparse 3D maps coming from different sensor modalities. Merging of maps can be advantageous if there are several map representations of the same environment, or if there is a need for adding new information to an already existing map. We suggest a compact map representation with a small memory footprint, which we then use to fuse maps efficiently. We suggest one method for fusion of maps that are pre-aligned, and one where we additionally estimate the coordinate system. The merging utilises a compact approximation of the residuals and allows for deformations in the original maps. Furthermore, we present minimal solvers for 3D point matching with statistical deformations – which increases the number of inliers when the original maps contain errors