Showing papers by "Milica Stojanovic published in 2013"

Statistical Characterization and Computationally Efficient Modeling of a Class of Underwater Acoustic Communication Channels

Abstract: Underwater acoustic channel models provide a tool for predicting the performance of communication systems before deployment, and are thus essential for system design. In this paper, we offer a statistical channel model which incorporates physical laws of acoustic propagation (frequency-dependent attenuation, bottom/surface reflections), as well as the effects of inevitable random local displacements. Specifically, we focus on random displacements on two scales: those that involve distances on the order of a few wavelengths, to which we refer as small-scale effects, and those that involve many wavelengths, to which we refer as large-scale effects. Small-scale effects include scattering and motion-induced Doppler shifting, and are responsible for fast variations of the instantaneous channel response, while large-scale effects describe the location uncertainty and changing environmental conditions, and affect the locally averaged received power. We model each propagation path by a large-scale gain and micromultipath components that cumulatively result in a complex Gaussian distortion. Time- and frequency-correlation properties of the path coefficients are assessed analytically, leading to a computationally efficient model for numerical channel simulation. Random motion of the surface and transmitter/receiver displacements introduce additional variation whose temporal correlation is described by Bessel-type functions. The total energy, or the gain contained in the channel, averaged over small scale, is modeled as log-normally distributed. The models are validated using real data obtained from four experiments. Specifically, experimental data are used to assess the distribution and the autocorrelation functions of the large-scale transmission loss and the short-term path gains. While the former indicates a log-normal distribution with an exponentially decaying autocorrelation, the latter indicates a conditional Ricean distribution with Bessel-type autocorrelation.

Multiple-Resampling Receiver Design for OFDM Over Doppler-Distorted Underwater Acoustic Channels

Abstract: In this paper, we focus on orthogonal frequency-division multiplexing (OFDM) receiver designs for underwater acoustic (UWA) channels with user- and/or path-specific Doppler scaling distortions. The scenario is motivated by the cooperative communications framework, where distributed transmitter/receiver pairs may experience significantly different Doppler distortions, as well as by the single-user scenarios, where distinct Doppler scaling factors may exist among different propagation paths. The conventional approach of front-end resampling that corrects for common Doppler scaling may not be appropriate in such scenarios, rendering a post-fast-Fourier-transform (FFT) signal that is contaminated by user- and/or path-specific intercarrier interference. To counteract this problem, we propose a family of front-end receiver structures that utilize multiple-resampling (MR) branches, each matched to the Doppler scaling factor of a particular user and/or path. Following resampling, FFT modules transform the Doppler-compensated signals into the frequency domain for further processing through linear or nonlinear detection schemes. As part of the overall receiver structure, a gradient-descent approach is also proposed to refine the channel estimates obtained by standard sparse channel estimators. The effectiveness and robustness of the proposed receivers are demonstrated via simulations, as well as emulations based on real data collected during the 2010 Mobile Acoustic Communications Experiment (MACE10, Martha's Vineyard, MA) and the 2008 Kauai Acomms MURI (KAM08, Kauai, HI) experiment.

Random Access Compressed Sensing over Fading and Noisy Communication Channels

Abstract: Random Access Compressed Sensing (RACS) is an efficient method for data gathering from a network of distributed sensors with limited resources. RACS relies on integrating random sensing with the communication architecture, and achieves overall efficiency in terms of the energy per bit of information successfully delivered. To address realistic deployment conditions, we consider data gathering over a fading and noisy communication channel. We provide a framework for system design under various fading conditions, and quantify the bandwidth and energy requirements of RACS in fading. We show that for most practical values of the signal to noise ratio, energy utilization is higher in a fading channel than it is in a non-fading channel, while the minimum required bandwidth is lower. Finally, we demonstrate the savings in the overall energy and the bandwidth requirements of RACS compared to a conventional TDMA scheme. We show that considerable gains in energy -on the order of 10 dB- are achievable, as well as a reduction in the required bandwidth, e.g., 2.5-fold decrease in the bandwidth for a network of 4000 nodes.

Recent trends in underwater acoustic communications

Abstract: Advances in underwater acoustic communications technology are being enabled by more access to in-water data and an infusion of new techniques, researchers, and students. In-water data collection is being made possible by robust funding in the United States, the European Union, and other countries, typically to multiorganization consortia working on both physical and network layer research. At the physical layer, single and multicarrier modulation methods continue to be refined, with a focus on both low signal-to-noise ratio, low-rate and high signal-to-noise ratio, high-rate data links. Establishment of performance metrics for adaptive equalizers and other parts of the physical layer continue, and recent work on high-fidelity channel models that mimic the effects of small-scale ocean processes indicates that progress is being made. Research in undersea acoustic networks continues to gain momentum as well, with multiple options available for integrating acoustic propagation models with network simulation, providing common frameworks for basing network design. The combination of these recent advances, plus continued interest by maritime science and industry in wireless communications, means that the field is poised to make new commercial breakthroughs in the next several years.

Minimal doubly resolving sets of prism graphs

Abstract: In this paper, we consider the problem of determining the minimal cardinality of double resolving sets for prism graphs . It is proved that the minimal cardinality is equal to four if is even and equal to three if is odd.

Capacity Scaling Laws for Underwater Networks

Abstract: The underwater acoustic channel is characterized by a path loss that depends not only on the transmission distance, but also on signal frequency. Signals transmitted from one user to another over a distance l are subject to a power loss of l −α a(f)−l . Although a terrestrial radio channel can be modeled similarly, the underwater acoustic channel has different characteristics. The spreading factor α, related to the geometry of propagation, has values in the range 1⩽α⩽2. The absorption coefficient a(f) is a rapidly increasing function of frequency: it is three orders of magnitude greater at 100 kHz than at a few hertz. Existing results for capacity of radio wireless networks correspond to scenarios for which a(f)=1, or a constant greater than one, and α⩾2. These results cannot be applied to underwater acoustic networks in which the attenuation varies over the system bandwidth. We use a water-filling argument to assess the minimal transmission power and optimal transmission band as functions of the link dis...

A node discovery protocol for ad hoc underwater acoustic networks

Abstract: Motivated by the advances in acoustic modem technology and the growing number of applications that call for ad hoc deployable autonomous underwater systems (floating sensors, crawlers, vehicles), we address the problem of network initialization upon deployment. A neighbor discovery protocol is proposed, whose goal is to establish communication links over a large area, with a finite power budget that mandates multi-hopping to provide full coverage. The protocol uses random access to eliminate the need for scheduling (i.e., enable system operation without a global clock reference) and power control to ensure that full connectivity is provided using shortest links (i.e., to conserve batteries and prolong the system's lifetime). Transmit power allocation takes into account the acoustic propagation loss, while additional large-scale variation in the average received power is modeled via log-normal fading which is confirmed by experimental observations. System performance is assessed through simulation, by measuring the energy consumption, time to completion, and reliability in the presence of fading. Fading is shown to have a degrading effect on the system reliability, and protocol adjustments are proposed to recover the performance under the constraint on maximum power. The key features of the protocol are simplicity of implementation and efficient use of power.Copyright © 2012 John Wiley & Sons, Ltd.

On the Effects of Frequency Scaling Over Capacity Scaling in Underwater Networks--Part II: Dense Network Model

Abstract: This is the second in a two-part series of papers on information-theoretic capacity scaling laws for an underwater acoustic network. Part II focuses on a dense network scenario, where nodes are deployed in a unit area. By deriving a cut-set upper bound on the capacity scaling, we first show that there exists either a bandwidth or power limitation, or both, according to the operating regimes (i.e., path-loss attenuation regimes), thus yielding the upper bound that follows three fundamentally different information transfer arguments. In addition, an achievability result based on the multi-hop (MH) transmission is presented for dense networks. MH is shown to guarantee the order optimality under certain operating regimes. More specifically, it turns out that scaling the carrier frequency faster than or as $$n^{1/4}$$ is instrumental towards achieving the order optimality of the MH protocol.

Exploiting temporal and spatial correlation in wireless sensor networks

Abstract: Motivated by applications of wireless sensor networks to seismic field monitoring, we propose a method that integrates in-situ lightweight temporal compression with random access communication and compressive sensing for recovery of spatially-sparse phenomena. This method of spatio-temporal compression offers savings in terms of energy consumption and bandwidth usage, does not require sensors to be synchronized, and requires minimal feedback from the fusion center. Furthermore, the method is robust to node failures and packet losses. Performance is quantified using both simulation and real data, showing significant improvements in energy and bandwidth efficiency over more conventional techniques.

Energy optimization with delay constraints in Underwater Acoustic Networks

Abstract: Underwater Acoustic Sensor Networks find use in critical time-sensitive applications such as disaster prevention and coastline protection. The sensor nodes used in such networks are powered by batteries that are difficult to recharge or replace. Hence it is imperative that routing algorithms used in such networks be very energy efficient while also satisfying necessary delay constraints for time-sensitive applications. Unlike the radio frequency medium, underwater acoustic channels have low bandwidth, large propagation delays and long multipath delay spreads. While energy-efficient routing is an actively researched area for terrestrial radio frequency networks, results from those studies generally do not apply to underwater acoustic networks due to vast differences in channel characteristics. In this paper we explore delay-constrained energy optimization for routing in underwater acoustic sensor networks. Specifically, we propose an offline Mixed Integer Linear Programming based routing algorithm that enables computation of delay constrained energy efficient routes.

Random linear packet coding for fading channels

Abstract: Random linear packet coding is considered for use over underwater acoustic channels where long delays challenge the efficiency of standard ARQ. Adaptive power control and rate control are explored to overcome the effect of fading, while minimizing the average energy per successfully transmitted bit of information. Two extreme scenarios are considered: independent fading where the channel varies independently from one data packet to the next, and block fading where the channel stays fixed over a block of packets. For the case of block fading, we design a power (rate) adaptation strategy under an outage criterion. We show that there exists an optimal transmission power (number of coded packets) for which the average energy per bit is minimized. Finally, we quantify the benefits of adaptive power (rate) control using real channel data recorded over a mobile link in the 10kHz acoustic band. These results show that energy savings are available from adaptive power (rate) control strategies.

Partial FFT demodulation for coherent detection of OFDM signals over underwater acoustic channels

Abstract: We propose an algorithm for coherent detection of OFDM signals over underwater acoustic channels in the presence of Doppler distortions. The algorithm uses multiple FFT demodulators, each operating on a different (partial) segment of the incoming OFDM block. The segments corresponding to several adjacent carriers and multiple receiving elements are adaptively combined to reduce the inter-carrier interference. The combiner weights are computed recursively across carriers, using a stochastic gradient algorithm. The information contained in the combiner weights is also used to predict the Doppler shifts for the next incoming block, thus enhancing the accuracy of adaptive channel tracking. Synthetic and experimental data from a recent experiment conducted over a mobile acoustic channel in the 10 - 15 kHz band, show that partial FFT demodulation with enhanced channel tracking provides a significant gain in performance over a conventional coherent detector, and increases the bandwidth efficiency.

Target localization and tracking in a random access sensor network

Abstract: We consider tracking of multiple objects using a wireless sensor network where distributed nodes transmit to a fusion center using random access. During an initialization phase, targets are identified on a discrete set of locations using a sparse identification method. Tracking then proceeds to update the target locations and amplitudes explicitly, using a gradient algorithm to solve the underlying non-linear optimization problem. Updating continues at the pace dictated by the average sensing/transmission rate, which can be adjusted to suit an expected target velocity. By focusing explicitly on the target locations, as opposed to continuing with sparse identification over a quantized space whose size may be much greater than the number of targets, the goal is to reduce the computational complexity, improve the performance, and eliminate the spatial quantization effects.

Supergroups for six series of hyperbolic simplex groups

Abstract: There are investigated supergroups of some hyperbolic space groups with simplicial fundamental domain. Six simplices considered here from [9] are collected in families F9 (T23, T64), F10 (T21, T49, T61), F29 (T34). All of them have the same symmetry by half-turn h, with axis through the midpoints of edges A0A1 and A2A3. Since that isometry identifies pairs of points, if a supergroup with such smaller fundamental domain exists, it is of index 2. At the side pairings of T34 this half-turn implies additional reflections, equal parameters 2a = 6b, and leads to Family 2, considered in [9]. Other possibility to find supergroups is when the simplices have vertices out of the absolute. In that case we can truncate them by polar planes of the vertices and the new polyhedra are fundamental domains of richer groups.

On the Effects of Frequency Scaling Over Capacity Scaling in Underwater Networks—Part II: Dense Network Model

Abstract: This is the second in a two-part series of papers on information-theoretic capacity scaling laws for an underwater acoustic network. Part II focuses on a dense network scenario, where nodes are deployed in a unit area. By deriving a cut-set upper bound on the capacity scaling, we first show that there exists either a bandwidth or power limitation, or both, according to the operating regimes (i.e., path-loss attenuation regimes), thus yielding the upper bound that follows three fundamentally different information transfer arguments. In addition, an achievability result based on the multi-hop (MH) transmission is presented for dense networks. MH is shown to guarantee the order optimality under certain operating regimes. More specifically, it turns out that scaling the carrier frequency faster than or as $$n^{1/4}$$ is instrumental towards achieving the order optimality of the MH protocol.

Computationally efficient simulation of underwater acoustic communication systems

Abstract: We propose a statistical model for underwater acoustic channel simulation which addresses acoustic propagation laws as well as fading. The fading effects are studied on small-scale (involving distances on the order of the wavelength) and large-scale (due to location uncertainty). These effects are caused by various phenomena such as scattering, system motion and changing environmental conditions, and result in the variation of the instantaneous channel response as well as the average signal to noise ratio. We compare the simulator with real underwater acoustic data obtained during the Kauai Acomms MURI (KAM'11) experiment which was held in July 2011. Simulated and experimental channels exhibit complex Gaussian path fading with a Bessel-type time-correlation on the small scale, and log-normal distribution with an exponentially decaying time-correlation on the large scale. MSE performance is compared for coherent and differentially coherent detection of experimental and simulated data.

Resource allocation for hierarchical underwater sensor networks

Abstract: We investigate data collection over an underwater acoustic communication network, where sensor nodes are deployed to measure an environmental process. To enhance the energy-efficiency, the network is organized into a hierarchical structure, in which multiple local fusion centers collect the information and convey it to a master fusion center. The master fusion center then recovers the map of the sensing field. We exploit the unique properties of the underwater signal propagation to allocate resources efficiently across the network, resulting in overall savings in the energy and a reduction in the minimum necessary bandwidth.