Roee Diamant

Bio: Roee Diamant is an academic researcher from University of Haifa. The author has contributed to research in topics: Underwater acoustic communication & Network topology. The author has an hindex of 20, co-authored 95 publications receiving 1458 citations. Previous affiliations of Roee Diamant include University of Padua & University of British Columbia.

Underwater Localization with Time-Synchronization and Propagation Speed Uncertainties

Abstract: Underwater acoustic localization (UWAL) is a key element in most underwater communication applications. The absence of GPS as well as the signal propagation environment makes UWAL similar to indoor localization. However, UWAL poses additional challenges. The propagation speed varies with depth, temperature, and salinity, anchor and unlocalized (UL) nodes cannot be assumed time-synchronized, and nodes are constantly moving due to ocean currents or self-motion. Taking these specific features of UWAL into account, in this paper, we describe a new sequential algorithm for joint time-synchronization and localization for underwater networks. The algorithm is based on packet exchanges between anchor and UL nodes, makes use of directional navigation systems employed in nodes to obtain accurate short-term motion estimates, and exploits the permanent motion of nodes. Our solution also allows self-evaluation of the localization accuracy. Using simulations, we compare our algorithm to two benchmark localization methods as well as to the Cramer-Rao bound (CBR). The results demonstrate that our algorithm achieves accurate localization using only two anchor nodes and outperforms the benchmark schemes when node synchronization and knowledge of propagation speed are not available. Moreover, we report results of a sea trial where we validated our algorithm in open sea.

Spatial Reuse Time-Division Multiple Access for Broadcast Ad Hoc Underwater Acoustic Communication Networks

Abstract: Underwater acoustic communication (UWAC) is often the only viable solution to establish an ad hoc underwater communication network. The specific features of UWAC, arising from the physics of underwater acoustics, make the design of resource-efficient media access control (MAC) protocols important as well as challenging. In this paper, we tackle this task considering ad hoc UWAC networks that support high-traffic broadcast communication. To this end, we propose the application of the spatial reuse concept and the exploitation of direct sequence spread spectrum used at the UWAC physical layer to obtain a new hybrid spatial reuse time-division multiple-access (HSR-TDMA) protocol. By tracking the time-varying network topology, our protocol adaptively optimizes the set of active communication nodes and overcomes problems of UWAC networks such as the near-far problem, flickering, and formation of islands. Pertinent performance parameters, namely network availability, message reliability, and transmission rate, are analyzed for the proposed protocol. Evaluation of these analytical performance expressions demonstrates the significant advantages of HSR-TDMA over commonly used conventional TDMA for broadcast UWAC networks. We also report performance results for both the HSR-TDMA and the conventional TDMA protocol from a sea trial at the Haifa harbor, which corroborate the results obtained from the analysis.

Low Probability of Detection for Underwater Acoustic Communication: A Review

Abstract: Low probability of detection (LPD) is an extremely important characteristic of an underwater acoustic communication (UWAC) system when used for military-related applications, since the detection of a communication signal in the channel may reveal the presence of the transmitter or receiver. Furthermore, the recent advances in the understanding of the environmental effects of sound transmission in the ocean have led to a growing interest in LPD for UWAC also for civilian use. This is because systems that are designed for reliable communication at low signal power have a reduced environmental impact. In this paper, we identify the main challenges for the design of UWAC LPD systems. We describe and classify common approaches for transmission, reception, and interception of LPD signals, and we discuss their advantages and weaknesses. We also present several methods to determine the LPD capability of a system and suggest to adopt the range ratio test as a performance measure that captures the effects of signal propagation through the UWAC channel and the capabilities of the communication receiver and a signal interceptor. In light of the environmental benefits of LPD transmission and ongoing discussions about limiting the power spectral density of UWAC signals through regulations, we believe that LPD transmission is an area of growing importance for UWAC research and development. We hope that this paper serves as a motivation and a starting point for further research in this field.

LOS and NLOS Classification for Underwater Acoustic Localization

Abstract: The low sound speed in water makes propagation delay (PD)-based range estimation attractive for underwater acoustic localization (UWAL). However, due to the long channel impulse response and the existence of reflectors, PD-based UWAL suffers from significant degradation when PD measurements of nonline-of-sight (NLOS) communication links are falsely identified as line-of-sight (LOS). In this paper, we utilize expected variation of PD measurements due to mobility of nodes and present an algorithm to classify the former into LOS and NLOS links. First, by comparing signal strength-based and PD-based range measurements, we identify object-related NLOS (ONLOS) links, where signals are reflected from objects with high reflection loss, for example, ships hull, docks, rocks and so on. In the second step, excluding PD measurements related to ONLOS links, we use a constrained expectation-maximization algorithm to classify PD measurements into two classes: LOS and sea-related NLOS (SNLOS), and to estimate the statistical parameters of each class. Since our classifier relies on models for the underwater acoustic channel, which are often simplified, alongside simulation results, we validate the performance of our classifier based on measurements from three sea trials. Both our simulation and sea trial results demonstrate a high detection rate of ONLOS links, and accurate classification of PD measurements into LOS and SNLOS.

Random graphs

Abstract: We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

A Survey of Underwater Optical Wireless Communications

Abstract: Underwater wireless communications refer to data transmission in unguided water environment through wireless carriers, i.e., radio-frequency (RF) wave, acoustic wave, and optical wave. In comparison to RF and acoustic counterparts, underwater optical wireless communication (UOWC) can provide a much higher transmission bandwidth and much higher data rate. Therefore, we focus, in this paper, on the UOWC that employs optical wave as the transmission carrier. In recent years, many potential applications of UOWC systems have been proposed for environmental monitoring, offshore exploration, disaster precaution, and military operations. However, UOWC systems also suffer from severe absorption and scattering introduced by underwater channels. In order to overcome these technical barriers, several new system design approaches, which are different from the conventional terrestrial free-space optical communication, have been explored in recent years. We provide a comprehensive and exhaustive survey of the state-of-the-art UOWC research in three aspects: 1) channel characterization; 2) modulation; and 3) coding techniques, together with the practical implementations of UOWC.

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Abstract: Wireless sensor networks (WSNs) monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002–2013 of machine learning methods that were used to address common issues in WSNs. The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.

Detection, Estimation, and Modulation Theory

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