ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada / An acoustic modem employing direct-sequence spread-spectrum (DSSS) signaling is considered with LDPC coding. The underwater acoustic channel is tracked using a Kalman filter which requires accurate data decisions. To improve KF performance and reduce the overall error rate, joint iterative LDPC decoding and channel estimation is proposed based on a factor graph and sum-product algorithm approximation. In this scheme, the decoder posterior log likelihood ratios (LLRs) provide data decisions for the KF. Decoder extrinsic LLRs are similarly incorporated into the detector LLRs to yield improved priors for decoding. Error rate simulations of the overall modem are provided for a shallow-water channel model with Ricean/Rayleigh fading.

A transponder for underwater acoustic data communications is prototyped. The mobile transponder emits a data sequence whenever it detects a ping from a base station. The data sequence includes GPS coordinates and UTC time sent over a conservative and brief 12 kbps turbo-coded BPSK link, and a 6 kB JPEG image sent over an ambitious 67 kbps turbo-coded 16-QAM link. The range of the transponder from the base station can also be accurately derived. Several challenges exist in decoding the underwater signals at the base station receiver, including Doppler distortion and multipath. While experimental results show that the ranges for decoding the 16-QAM signals with a single hydrophone are limited to less than 25 m, the BPSK signals prove to be much more robust, decoding at ranges of up to 625 m. Experiments with delays and transducer tether length indicate methods for improving reliability in the presence of reverberation and thermocline. This transponder uses mostly off-the-shelf parts and is anticipated to be improved when paired with advanced sonar array devices. / text

In this dissertation, we propose decentralized and scalable algorithms for Gaussian process (GP) training and prediction in multi-agent systems. The first challenge is to compute a spatial field that represents underwater acoustic communication performance from a set of measurements. We compare kriging to cokriging with vehicle range as a secondary variable using a simple approximate linear-log model of the communication performance. Next, we propose a model-based learning methodology for the prediction of underwater acoustic performance using a realistic propagation model. The methodology consists of two steps: i) estimation of the covariance matrix by evaluating candidate functions with estimated parameters; and ii) prediction of communication performance. Covariance estimation is addressed with a multi-stage iterative training method that produces unbiased and robust results with nested models. The efficiency of the framework is validated with simulations and experimental data from field trials. The second challenge is to perform predictions at unvisited locations with a team of agents and limited inter-agent information exchange. To decentralize the implementation of GP training, we employ the alternating direction method of multipliers (ADMM). A closed-form solution of the decentralized proximal ADMM is provided for the case of GP hyper-parameter training with maximum likelihood estimation. Multiple aggregation techniques for GP prediction are decentralized with the use of iterative and consensus methods. In addition, we propose a covariance-based nearest neighbor selection strategy that enables a subset of agents to perform predictions. Empirical evaluations illustrate the efficiency of the proposed methods / Doctor of Philosophy / In this dissertation, we propose decentralized and scalable algorithms for collaborative multiagent learning. Mobile robots, such as autonomous underwater vehicles (AUVs), can use predictions of communication performance to anticipate where they are likely to be connected to the communication network. The first challenge is to predict the acoustic communication performance of AUVs from a set of measurements. We compare two methodologies using a simple model of communication performance. Next, we propose a model-based learning methodology for the prediction of underwater acoustic performance using a realistic model. The methodology first estimates the covariance matrix and then predicts the communication performance. The efficiency of the framework is validated with simulations and experimental data from field trials. The second challenge regards the efficient execution of Gaussian processes using multiple agents and communicating as little as possible. We propose decentralized algorithms that facilitate local computations at the expense of inter-agent communications. Moreover, we propose a nearest neighbor selection strategy that enables a subset of agents to participate in the prediction. Illustrative examples with real world data are provided to validate the efficiency of the algorithms.

abstract: The widespread adoption of mobile devices gives rise to new opportunities and challenges for authentication mechanisms. Many traditional authentication mechanisms become unsuitable for smart devices. For example, while password is widely used on computers as user identity authentication, inputting password on small smartphone screen is error-prone and not convenient. In the meantime, there are emerging demands for new types of authentication. Proximity authentication is an example, which is not needed for computers but quite necessary for smart devices. These challenges motivate me to study and develop novel authentication mechanisms specific for smart devices. In this dissertation, I am interested in the special authentication demands of smart devices and about to satisfy the demands. First, I study how the features of smart devices affect user identity authentications. For identity authentication domain, I aim to design a continuous, forge-resistant authentication mechanism that does not interrupt user-device interactions. I propose a mechanism that authenticates user identity based on the user's finger movement patterns. Next, I study a smart-device-specific authentication, proximity authentication, which authenticates whether two devices are in close proximity. For prox- imity authentication domain, I aim to design a user-friendly authentication mechanism that can defend against relay attacks. In addition, I restrict the authenticated distance to the scale of near field, i.e., a few centimeters. My first design utilizes a user's coherent two-finger movement on smart device screen to restrict the distance. To achieve a fully-automated system, I explore acoustic communications and propose a novel near field authentication system. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2014

Approved for public release, distribution is unlimited / A recent improvement to the Seaweb underwater wireless network was the implementation of a Selective Automatic Repeat Request (SRQ) mechanism. SRQ is a protocol implemented in the Seaweb link layer as a measure for mitigating unreliability inherent in the telesonar physical layer. In January 2004, an experiment was performed in St. Andrew's Bay, Panama City, Florida. The goal was to transmit large data files through the network, in accordance with a Naval Special Warfare need for imagery file telemetry. For three point-to-point test geometries, SRQ was tested with a noisy and variable physical layer. Through the incorporation of SRQ, the unreliability was overcome. A link-budget model calibrated with the sound channel data collected from the experiment establishes the benefit of a "SRQ gain." / Ensign, United States Navy

Traditionally, noise in communication systems has been modeled as an additive, white Gaussian noise process with independent, identically distributed samples. Although this model accurately reflects thermal noise present in communication system electronics, it fails to capture the statistics of interference and other sources of noise, e.g. in unlicensed communication bands. Modern communication system designers must take into account interference and non-Gaussian noise to maximize efficiencies and capacities of current and future communication networks. In this work, I develop new multi-dimensional signal processing methods to improve performance of communication systems in three applications areas: (i) underwater acoustic, (ii) powerline, and (iii) multi-antenna cellular. In underwater acoustic communications, I address impairments caused by strong, time-varying and Doppler-spread reverberations (self-interference) using adaptive space-time signal processing methods. I apply these methods to array receivers with a large number of elements. In powerline communications, I address impairments caused by non-Gaussian noise arising from devices sharing the powerline. I develop and apply a cyclic adaptive modulation and coding scheme and a factor-graph-based impulsive noise mitigation method to improve signal quality and boost link throughput and robustness. In cellular communications, I develop a low-latency, high-throughput space-time-frequency processing framework used for large scale (up to 128 antenna) MIMO. This framework is used in the world's first 100-antenna MIMO system and processes up to 492 Gbps raw baseband samples in the uplink and downlink directions. My methods prove that multi-dimensional processing methods can be applied to increase communication system performance without sacrificing real-time requirements. / text

abstract: Underwater acoustic communications face significant challenges unprecedented in radio terrestrial communications including long multipath delay spreads, strong Doppler effects, and stringent bandwidth requirements. Recently, multi-carrier communications based on orthogonal frequency division multiplexing (OFDM) have seen significant growth in underwater acoustic (UWA) communications, thanks to their well well-known robustness against severely time-dispersive channels. However, the performance of OFDM systems over UWA channels significantly deteriorates due to severe intercarrier interference (ICI) resulting from rapid time variations of the channel. With the motivation of developing enabling techniques for OFDM over UWA channels, the major contributions of this thesis include (1) two effective frequencydomain equalizers that provide general means to counteract the ICI; (2) a family of multiple-resampling receiver designs dealing with distortions caused by user and/or path specific Doppler scaling effects; (3) proposal of using orthogonal frequency division multiple access (OFDMA) as an effective multiple access scheme for UWA communications; (4) the capacity evaluation for single-resampling versus multiple-resampling receiver designs. All of the proposed receiver designs have been verified both through simulations and emulations based on data collected in real-life UWA communications experiments. Particularly, the frequency domain equalizers are shown to be effective with significantly reduced pilot overhead and offer robustness against Doppler and timing estimation errors. The multiple-resampling designs, where each branch is tasked with the Doppler distortion of different paths and/or users, overcome the disadvantages of the commonly-used single-resampling receivers and yield significant performance gains. Multiple-resampling receivers are also demonstrated to be necessary for UWA OFDMA systems. The unique design effectively mitigates interuser interference (IUI), opening up the possibility to exploit advanced user subcarrier assignment schemes. Finally, the benefits of the multiple-resampling receivers are further demonstrated through channel capacity evaluation results. / Dissertation/Thesis / Ph.D. Electrical Engineering 2011

Communication underwater is challenging because of the inherent characteristics of the media. First, common radio frequency (RF) signals utilized in wireless communications cannot be used under water. RF signals are attenuated in such as way that RF communication underwater is restricted to very few meters. As a result, acoustic-based communication is utilized for underwater communications; however, acoustic communication has its own limitations. For example, the speed of sound is five orders of magnitude lower than the speed of light, meaning that communications under water experience long propagation delays, even in short distances. Long propagation delays impose strong challenges in the design of Data Link Layer (DLL) protocols. The underwater communication channel is noisy, too. The bit error rate (BER) can also change depending on depth and other factors, and the errors are correlated, like in wireless communications. As in wireless communications, transducers for acoustic communication are half duplex, limiting the application of well-known detection mechanisms in Medium Access Control (MAC) layer protocols. Further, known problems like the hidden and exposed terminal problem also occur here. All these aspects together make the underwater communication channel to have the worst characteristics of all other known channels. Because of these reasons, underwater scenarios are complicated to implement, especially when they have underwater autonomous vehicles exchanging information among them. This dissertation proposes data link layer protocols in support of swarming of underwater autonomous vehicles that deal with the problems mentioned before. At the MAC sublayer, a MAC protocol called 2MAC is introduced. 2MAC improves the throughput of the network using the multichannel capabilities of OFDM at the physical layer. At the logical link control sublayer, a protocol named SW-MER is proposed. SW-MER improves the throughput and the reliability combining the well-known stop and wait protocol with the sliding window strategy, and using an exponential retransmission strategy to deal with errors. 2MAC and SW-MER are evaluated and compared with other protocols using analytical means and simulations. The results show that by using 2MAC, packet collisions are considerably reduced and the throughput improved. In addition, the use of SW-MER improves the packet delivery ratio over existing mechanisms. In general, the evaluations indicate that the proposed data link layer protocols offer a better communication alternative for underwater autonomous vehicles (UAV) than traditional protocols.

Approved for public release, distribution is unlimited / Direct-Sequence Spread Spectrum (DSSS) modulation is being advanced as the physical-layer basis for Seaweb undersea acoustic networking. DSSS meets the need for channel tolerance, transmission security, and multi-user access. This thesis investigates the performance of subspace-decomposition blind-equalization algorithms as alternatives to RAKE processing of DSSS signals. This approach is tailored for superior performance in time-dispersive and frequency-dispersive channels characteristic of ocean acoustic propagation. Transmitter and receiver structures are implemented in Matlab and evaluated with a statistics-based model of a doubly spread channel with additive noise. Receiver performance is examined using Monte Carlo simulation. Biterror rates versus signal-to-noise ratio are presented for various multipath assumptions, noise assumptions, and receiver synchronization assumptions. / Lieutenant, Hellenic Navy