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The problem of information transmission through water pipelines is addressed and a class of methods based on differentially encoded orthogonal frequency division multiplexing (OFDM) is proposed. Specifically, two methods are investigated; one based on conventional differential encoding with an estimation of the average time of arrival and another based on double encoding. Results show that the first approach improves performance in the low signal to noise ratio (SNR) region, while the second is better suited at high SNR. Adopting these techniques closes the performance gap between differential OFDM systems and coherent OFDM systems while retaining the benefits of computational simplicity.

OFDM systems are challenged by the time variability of mobile acoustic channels where the Doppler effect can be high enough that the received signal experiences non-negligible residual frequency offset, as well as channel time variability, which cause intercarrier interference (ICI). To mitigate these effects, we introduce an efficient yet computationally manageable two-stage algorithm that counteracts the frequency offset as well as the time selectivity of mobile acoustic channels. In the first stage, frequency offset is compensated using a practical approach based on differentially coherent detection which keeps the receiver complexity at a minimum and requires only a small pilot overhead. In the second stage, a method referred to as partial FFT demodulation is used to tone down the time variability of the broadband acoustic channel. Towards this goal, the time interval of one OFDM block is divided into several partial intervals, giving the channel less chance to change over each shorter interval, and demodulation is performed in each interval separately. The partial demodulator outputs are then combined before applying a coherent detection algorithm where refined channel estimation and data detection take place. Using the experimental data transmitted over a 3–7 km shallow water channel in the 10.515.5 kHz acoustic band, we study the receiver performance in terms of data detection mean squared error (MSE), and show that the proposed algorithm provides excellent performance, surpassing all our previously tested approaches.

This article addresses the problem of coherent detection of acoustic orthogonal frequency division multiplexing (OFDM) signals using a sparse channel estimation method based on a physical model of multipath propagation. Unlike the conventional sample-spaced and subsample-spaced methods, such as least squares and orthogonal matching pursuit (OMP), which target the taps of an equivalent discrete-delay channel response, the path identification (PI) method targets the physical propagation paths in a continuous-delay domain, and focuses on explicit estimation of delays and complex amplitudes of the channel paths in an iterative fashion. When multiple receive elements are available, two situations are possible: one in which the array elements see uncorrelated channel responses, and another in which the channel responses are correlated. In the first case, channel estimation must be accomplished element-by-element. This is done simply by applying the PI algorithm to each element individually. In the second case, correlation between the elements can be exploited. In doing so, our goal is to reduce the signal processing complexity without compromising the performance. Toward this goal, an adaptive precombining method is proposed. Without requiring any a priori knowledge about the spatial distribution of received signals, the method exploits spatial coherence between receive channels by linearly combining them into fewer output channels so as to reduce the number of subsequent channel estimators. The algorithm learns the spatial coherence pattern recursively over the carriers, thus effectively achieving broadband beamforming. The reduced-complexity precombining method relies on differential encoding that keeps the receiver complexity at a minimum and requires a very low pilot overhead. Using synthetic data as well as 210 experimental signals transmitted over a 3–7-km shallow-water channel in the 10.5–15.5-kHz acoustic band during a 3.5-h experiment, we study the system performance in terms of data detection mean-squared error (MSE), symbol error rate, and bit error rate (BER), and show that the PI algorithm achieves excellent MSE performance while its complexity is considerably lower than that of the OMP algorithm. We also demonstrate that the receiver equipped with the proposed reduced-complexity precombining scheme requires three times fewer channel estimators while achieving the same MSE and BER performance as the full-complexity receiver.

Fundamental understanding of the processes that affect the state and well being of the human body continues to be a challenging frontier. Recent technological developments point toward the possibility of implanting sensors inside the body, thus enabling in-situ data gathering and real-time actuation with the transmission of the sensed data to other implants as well as external computational clouds. This paper aims to survey and compare the existing methods for achieving intra-body communication (IBC) covering the methods of galvanic coupling (waveguide-based), capacitive coupling (electric field-based), ultrasound (acoustic-based) and magnetic resonant coupling (magnetic field-based). The performance of each method is evaluated in terms of its physical layer characteristics, including operating frequency range, attenuation effects within the body, channel modeling methods, power consumption, achievable data rates, communication distance, and safety limits under prolonged signal exposure. Based on this metric-driven study, we identify specific scenarios where one or more of these different IBC methods are better suited. For the specific case of galvanic coupling, we provide select system designs, experimental results from a custom-designed testbed and target applications that are more appropriate for this method of IBC. To the best of our knowledge, this is the first work that encapsulates the state of the art and current research trends for several different types of IBC solutions, a topic that promises to revolutionize the future of healthcare.

In this work we describe our investigation into the performance of coherent orthogonal frequency division multiplexing (OFDM) and differentially coherent OFDM communication systems in a wideband waveguide channel consisting of a steel pipe filled with static water. The channel transfer function was measured by a vector network analyzer, and the channel noise (found to be normally distributed above 10 kHz) was measured by a hydrophone connected to a data acquisition device. The measured steel-pipe water channel together with additive complex Gaussian noise is used as the communication channel. Bit error rate (BER) simulation results show that coherent OFDM outperforms differentially coherent OFDM because it takes advantage of accurate channel estimation. Nonetheless, differentially coherent OFDM detection performs well when the sub-carrier separation is less than the coherence bandwidth, offering the benefit of lower system complexity and increased throughput efficiency.

We address the design of a multi-user system where each user employs multi-carrier modulation in the form of orthogonal frequency division multiplexing (OFDM). We present a transmission and detection method that combines OFDM with direct-sequence spread spectrum. Coding is employed across carriers in a manner that provides multi-user interference suppression along with subsequent channel estimation and data detection. We consider both coherent and differentially coherent data detection, each integrated with a custom-designed technique for Doppler frequency shift compensation. Using the recordings from the Mobile Acoustic Communication Experiment (MACE'10), where signals were transmitted in the 10.5 kHz – 15.5 kHz acoustic band over a shallow-water channel, we demonstrate the performance of the system in terms of the mean squared error for a varying number of users. We conclude that the proposed system is able to operate in the multi-user interference scenario while maintaining low computational complexity.

Motivated by recent experimental observations, where differentially coherent detection outperforms coherent detection on certain underwater acoustic channels, we revisit the performance of these two methods with respect to the achievable rate in orthogonal frequency-division multiplexing systems. Our comparison is based on a class of time-varying channels, where coherent quadrature phase shift keying (QPSK) detection requires channel estimation through a set of designated pilot symbols, while differentially coherent QPSK (DQPSK) enjoys an almost pilot-free detection. We show that given the cost of pilot overhead and channel estimation errors, the average rate achievable with DQPSK can be higher than that of QPSK. We use analytical results to identify channels for which this is the case, and expand the results to larger constellation sizes such as 8PSK, 16PSK, and 16QAM. In addition to acoustic channels, wireless radio channels with unusually long delay spread or high Doppler spread, such as those found in unmanned aerial systems and high-speed trains, may also benefit from using differentially coherent detection. In general, differentially coherent detection is favored in rapidly time-varying channels which require large pilot overhead and/or whose bit error rate performance is dominated by channel estimation errors. Our analysis includes the results for array receivers and soft detectors, showing that the favorable parameter range for differentially coherent detection expands significantly in both cases.

We consider random linear packet coding for fading channels with long propagation delays, such as underwater acoustic channels. We propose a scheme in which the number of coded packets to transmit is determined to achieve a prespecified outage/reliability criterion and investigate joint power and rate control with constrained resources. Using the channel state information that is obtained via feedback from the receiver, the transmitter adjusts its power and the number of coded packets so that the average energy per successfully transmitted bit of information is minimized. Two optimization constraints are imposed: 1) the transmit power should not exceed a maximum level; and 2) the number of coded packets should not exceed a maximum value dictated by the desired throughput and delay. We further extend the results to take into account the effect of inevitable channel estimation errors, and consider the case in which the transmitter has only an estimate of the channel gain. We design adaptation policies for such a case based on minimum mean square error (MMSE) channel estimation, taking into account the effect of channel estimation errors in an optimal manner to satisfy the required outage/reliability criterion. Finally, we compare the proposed technique to standard automatic repeat request (ARQ) protocols for underwater communications in terms of the throughput efficiency. Analytical results show that substantial energy savings and improvements in throughput efficiency are available from adaptive power/rate control. We also present experimental results obtained using channel gains measured during the Surface Process Acoustic Communication Experiment (SPACE-08), an at-sea underwater experiment conducted off the coast of Martha's Vineyard in fall 2008.

High data rate coherent communication in acoustic channels are difficult due to the compound effects of motion-induced Doppler and long multipath. To account for these effects, we consider a coherent receiver based on orthogonal frequency division multiplexing (OFDM) which performs an iterative frequency offset compensation and sparse channel estimation. In mobile acoustic systems, Doppler effect can be severe enough that the OFDM signals experiences non-negligible frequency offsets even after initial resampling. To compensate for these offsets, a practical method based on stochastic gradient is employed. The method relies on differential encoding which keeps the receiver complexity at a minimum and requires only a small pilot overhead. Differential encoding is applied across carriers, promoting the use of a large number of closely spaced carriers within a given bandwidth. This approach simultaneously supports frequency domain coherence and efficient use of bandwidth for achieving high bit rates. After compensating for the frequency offset, a sparse channel estimation method based on a physical model of multipath propagation is used to obtain channel state information for coherent detection. The channel estimation method, referred to as path identification (PI), targets the physical propagation paths in a continuous-delay domain, and focuses on explicit estimation of delays and complex amplitudes of the channel paths in an iterative fashion. Using the experimental data transmitted over a 3–7 km shallow water channel in the 10.5-15.5 kHz acoustic band, we study the receiver performance in terms of data detection mean squared error (MSE) and bit error rate (BER), and show that the proposed receiver provides excellent performance at low computational cost.

We consider energy harvesting communications over an intersymbol interference (ISI) channel corrupted by additive white Gaussian noise. We assume that the energy arrivals at the transmitter, which is equipped with a finite battery, are independent and identically distributed, and provide a method of computing achievable information rates with channel inputs selected from a finite alphabet. We illustrate the methodology via a set of examples quantifying the effects of energy arrival rates as well as battery capacity on the achievable information rates.

We address the use of orthogonal frequency division multiplexing (OFDM) for high-rate communication over a mobile acoustic channel. To counteract the frequency offset and time-variability of the broadband mobile channel, we employ a dedicated method for synchronization and partial FFT (P-FFT) demodulation, cast into the framework of multichannel diversity combining. Unlike conventional receivers, where the signal is demodulated using a single FFT operating over the full OFDM block interval, P-FFT employs multiple FFT operations to demodulate the signal over several partial intervals. The partial demodulator outputs are subsequently combined, and the combined signal is fed to a second stage, where refined channel estimation and data detection take place. We investigate both coherent and differentially coherent detection, and test refined channel estimation with least squares (LS) and matching pursuit (MP) algorithms. Partial interval demodulation offers an additional degree of freedom by allowing for suppression of time-variation before inter-carrier interference has been created in the process of demodulation. The result is an improved quality of data detection, which we demonstrate using real data recorded during the 2010 Mobile Acoustic Communications Experiment MACE’10. Results of experimental data processing show excellent performance with up to 2048 QPSK-modulated carriers operating in the 10.5 kHz -15.5 kHz acoustic band over varying distance (3-7 km) and speeds up to 1.5 m/s.

In this paper, we consider a class of single-input–multiple-output (SIMO) underwater acoustic communication channels, where each propagation path can be characterized by a complex-valued Gaussian block-fading model. The capacity of such channels is computed and analyzed using three power allocation strategies: waterfilling, uniform, and on–off uniform power allocation across the signal bandwidth. Our analysis considers the effects of imperfect channel estimation, delayed feedback, and pilot overhead, which are found to contribute to about 1 (b/s)/Hz loss from 4 (b/s)/Hz at 20-dB signal-to-noise ratio (SNR) for the experimental channel. We find that given the long feedback delays associated with acoustic channels, all-on uniform power allocation, which does not require feedback and is simple to implement, emerges as a justified practical solution that outperforms the other strategies. Furthermore, when considering acoustic-specific propagation effects, such as frequency-dependent attenuation and colored noise, considerable gain can be achieved by selecting the frequency band according to the attenuation pattern and the available transmit power, e.g., at least 6-dB gain for a 10-km link when compared to transmission over a preselected frequency band of 10–15 kHz.

In this paper, Alamouti space-frequency block coding, applied over the carriers of an orthogonal frequency-division multiplexing (OFDM) system, is considered for obtaining transmit diversity in an underwater acoustic channel. This technique relies on the assumptions that there is sufficient spatial diversity between the channels of the two transmitters, and that each channel changes slowly over the carriers, thus satisfying the basic Alamouti coherence requirement and allowing simple data detection. We propose an adaptive channel estimation method based on Doppler prediction and time smoothing, whose decision-directed operation allows for reduction in the pilot overhead. System performance is demonstrated using real data transmitted in the 10-15-kHz acoustic band from a vehicle moving at 0.5-2 m/s and received over a shallow-water channel, using quadrature phase-shift keying (QPSK) and a varying number of carriers ranging from 64 to 1024. Results demonstrate an average mean squared error gain of about 2 dB as compared to the single-transmitter case and an order of magnitude decrease in the bit error rate when the number of carriers is chosen optimally. This work was supported in part by the ONR under grants N00014-07-1-0738, N00014-09-1-0700, and the NSF grant CNS-1212999.

We address detection of acoustic OFDM signals using a channel estimation method based on a physical model of multipath propagation rather than an equivalent sample-spaced model. The path identification (PI) algorithm focuses on explicit estimation of delays and complex amplitudes of the channel paths. We apply this algorithm, along with the conventional least squares (LS) and orthogonal matching pursuit (OMP) to a set of signals recorded over a mobile acoustic channel. We demonstrate excellent performance of the PI algorithm and show that its complexity is considerably lower than that of the OMP algorithm. The PI algorithm consistently outperforms the conventional LS and compares favorably with the OMP algorithm in terms of the mean-squared data detection error observed for a varying number of OFDM carriers and receiver array configurations.

Cataloged from PDF version of article. In this paper, we explore design aspects of adaptive modulation based on orthogonal frequency-division multiplexing (OFDM) for underwater acoustic (UWA) communications, and study its performance using real-time at-sea experiments. Our design criterion is to maximize the system throughput under a target average bit error rate (BER). We consider two different schemes based on the level of adaptivity: in the first scheme, only the modulation levels are adjusted while the power is allocated uniformly across the subcarriers, whereas in the second scheme, both the modulation levels and the power are adjusted adaptively. For both schemes we linearly predict the channel one travel time ahead so as to improve the performance in the presence of a long propagation delay. The system design assumes a feedback link from the receiver that is exploited in two forms: one that conveys the modulation alphabet and quantized power levels to be used for each subcarrier, and the other that conveys a quantized estimate of the sparse channel impulse response. The second approach is shown to be advantageous, as it requires significantly fewer feedback bits for the same system throughput. The effectiveness of the proposed adaptive schemes is demonstrated using computer simulations, real channel measurements recorded in shallow water off the western coast of Kauai, HI, USA, in June 2008, and real-time at-sea experiments conducted at the same location in July 2011. We note that this is the first paper that presents adaptive modulation results for UWA links with real-time at-sea experiments. © 2013 IEEE.

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.

We compare the achievable rate for QPSK and DQPSK modulations while considering the effect of channel estimation errors and pilot overhead. DQPSK is generally regarded in the literature as the low complexity alternative to QPSK, and is considered to sacrifice the performance as a trade-off. This argument is valid when the channel is perfectly known to the receiver. Here, we show that when the cost of pilot overhead and channel estimation errors are considered, there exist cases where DQPSK modulation delivers higher data rates as compared to QPSK modulation, even if optimal ratio of symbols are assigned as pilots. We classify these cases, and show through simulations that they occur frequently in underwater acoustic channels as the long delay spread requires a considerable pilot overhead for estimating the channel. Our results are supported by analysis, as well as simulation.

Employing Orthogonal Frequency Division Multiplexing (OFDM) signaling over time-varying channels results in inter-carrier interference (ICI) and degraded detection error probability due to the loss of orthogonality among the subcarriers. This problem is particularly exacerbated for systems operating in highly mobile scenarios such as underwater acoustic (UWA) communications, digital video broadcasting (DVB) for mobile devices and vehicle-to-vehicle (V2V) networks. To address the problem of data detection in such scenarios, we propose a novel demodulation strategy using several partial interval Fast Fourier Transforms (FFTs) instead of a conventional, single full interval FFT. Algorithms for computing the weights used to combine the outputs of the partial FFT are presented for three scenarios: full, partial and no knowledge of the time varying channel. Numerical simulations and an approximate theoretical analysis show that significant performance gains can be obtained over traditional equalizers at a very moderate complexity.

In this paper we propose new bounds on the achievable information rate for discrete-time Gaussian channels with intersymbol interference (ISI) and independent and uniformly distributed (i.u.d.) channel input symbols drawn from finite-order modulation alphabets. Specifically, we are interested in developing new bounds on the achievable rates for sparse channels with long memory. We obtain a lower bound which can be achieved by practical receivers, based on MMSE channel shortening and suboptimal symbol detection for a reduced-state channel. An upper bound is given in the form of a semi-analytical solution derived using basic information theoretic inequalities, by a grouping of the channel taps into several clusters resulting in a newly defined single-input multiple-output (SIMO) channel. We show that the so obtained time-dispersive SIMO channel can be represented by an equivalent single-input single-output (SISO) channel with a significantly shorter channel memory. The reduced computational complexity allows the use of the BCJR algorithm for the newly defined channel. The proposed bounds are illustrated through several sparse channel examples and i.u.d. input symbols, showing that the upper bound significantly outperforms existing bounds. Performance of our lower bound strongly depends on the channel structure, showing best results for minimum-phase and maximum-phase systems.

We analyze the performance of underwater acoustic ad-hoc networks in the presence of interference. We assume a uniform distribution of nodes over a finite area, and focus for simplicity on a two-dimensional network. The node-to-node channel is modeled using frequency dependent path loss and Ricean fading. We adopt a communication theoretic approach and study the sustainable number of hops through the network as an indicator of the network connectivity, as well as power and bandwidth requirements. The network operation is highly dependent on the node density with two distinct regions of limited performance: the coverage-limited region, where the number of nodes in the network is small, and the interference-limited region, where the number of nodes is large. We show that a desired level of connectivity can be achieved through a judicious selection of the operating frequency, power and bandwidth. Numerical examples illustrate the results of the analysis. These results motivate us to propose a hierarchical underwater acoustic sensor network architecture in which the sensors and the collector stations operate in distinct layers. The hierarchical architecture is supported by the property of the acoustic underwater transmission medium that for each transmission distance there exists an operating frequency for which the narrow-band signal-to-noise ratio is maximized. The sensors and the collector stations are consequently allocated different operating frequencies. We assume a uniform distribution of both sensors and collector stations over the finite area of the sensing field, and model the channel accordingly. The analysis is performed under the assumption that there is interference from other nodes within the same layer of the hierarchy. Numerical examples illustrate the network performance and demonstrate that the preferred operating frequencies ensure network operation without any cross-interference between the collector network and the sensor network.

Inspired by the theory of compressed sensing and employing random channel access, we propose a distributed energy-efficient sensor network scheme denoted by Random Access Compressed Sensing (RACS). The proposed scheme is suitable for long-term deployment of large underwater networks, in which saving energy and bandwidth is of crucial importance. During each frame, a randomly chosen subset of nodes participate in the sensing process, then share the channel using random access. Due to the nature of random access, packets may collide at the fusion center. To account for the packet loss that occurs due to collisions, the network design employs the concept of sufficient sensing probability. With this probability, sufficiently many data packets - as required for field reconstruction based on compressed sensing - are to be received. The RACS scheme prolongs network life-time while employing a simple and distributed scheme which eliminates the need for scheduling.

Orthogonal frequency division multiplexing (OFDM) has emerged as a promising modulation scheme for underwater acoustic (UWA) communications, thanks to its robustness to channels with severe time dispersion. Compared to conventional single-carrier systems, for which complicated equalization schemes are usually required, OFDM systems are in general much simpler to implement as detection can be carried out symbol-by-symbol over time-dispersive channels. In this paper, we focus on cyclic-prefixed OFDM over time-varying UWA channels. To cope with the intercarrier interference (ICI) that arises at the receiver side because of the time variations in the channel, we consider two ICI-mitigation techniques. In the first scheme, the ICI coefficients are explicitly estimated, and minimum mean square error linear equalization based on such estimates is performed. In the second approach, no explicit ICI estimation is performed, and detection is based on an adaptive decision-feedback equalizer applied in the frequency domain across adjacent subcarriers. To cope with the phase variations of the ICI coefficients, phase-tracking loops are introduced in both ICI-mitigation schemes. The effectiveness of the presented schemes is demonstrated through simulation results, as well as real data collected in a recent experiment conducted in shallow water off the western coast of Kauai, HI, in June 2008.

In this paper, a multihop underwater acoustic line network, which consists of a series of equal-distance hops connected by relay transceivers in a tandem, is considered. Messages are originated as coded packets from a source node at one end, relayed sequentially hop by hop (decoded and re-encoded), and finally received by a destination node at the other end of the network. Several key characteristics of underwater acoustic channels, namely, frequency-dependent signal attenuation and noise, interhop interference, half-duplex modem constraint, and large propagation delay, are taken into account in the analysis. Simple transmission protocols with spatial reuse and periodic transmit/receive schedule are considered. Performance bounds and scheduling design are developed to satisfy the half-duplex constraint on relay transceivers in the presence of long propagation delay. To efficiently cope with frequency-dependent channel characteristic and interhop interference, the power spectral density (PSD) of the signaling is analytically optimized in a way analogous to water filling. Furthermore, the problem of determining the minimum number of hops to support a prespecified rate and reliability with and without a maximum coded packet length constraint is examined. Finally, numerical results are presented to illustrate the analysis.

Path loss in an underwater acoustic channel depends not only on the transmission distance, but also on the signal frequency. As a result, the useful bandwidth decreases with distance, a feature not normally present in terrestrial radio networks. This fact motivates the use of multihop communications in an acoustic network, and strongly influences its design, since the same set of protocols will exhibit different performance when operating in a different frequency range. Multihop transmission is considered for large area coverage in acoustic networks, with an eye towards efficient power and bandwidth allocation. Power control is used as a practical means of optimizing the overall performance across the physical, medium access control (MAC) and routing layers. A geographic routing technique, called the focused beam routing (FBR), which requires each node to know only its own location and that of the final destination, is coupled with the distance aware collision avoidance protocol, which regulates the channel access. Results show that the average energy per bit consumption is reduced by adjusting the power, center frequency, and bandwidth in accordance with the network node density. Specifically, as the density increases, greater bandwidths offer per-hop energy reduction as well as a reduced packet collision rate.

In this paper, frequency and time correlation of the underwater channel are exploited to obtain a low-complexity adaptive channel estimation algorithm for multiple-input-multiple-output (MIMO) spatial multiplexing of independent data streams. The algorithm is coupled with nonuniform Doppler prediction and tracking, which enable decision-directed operation and reduces the overhead. Performance is demonstrated on experimental data recorded in several shallow-water channels over distances on the order of 1 km. Nearly error-free performance is observed for two and four transmitters with BCH(64,10) encoded quadrature phase-shift keying (QPSK) signals. With a 24-kHz bandwidth, overall data rates of up to 23 kb/s after coding were achieved with 2048 carriers. Good results have also been observed in two other experiments with varying MIMO-OFDM (orthogonal frequency-division multiplexing) configurations.

Acoustic propagation is characterized by three major factors: attenuation that increases with signal frequency, time-varying multipath propagation, and low speed of sound (1500 m/s). The background noise, although often characterized as Gaussian, is not white, but has a decaying power spectral density. The channel capacity depends on the distance, and may be extremely limited. Because acoustic propagation is best supported at low frequencies, although the total available bandwidth may be low, an acoustic communication system is inherently wideband in the sense that the bandwidth is not negligible with respect to its center frequency. The channel can have a sparse impulse response, where each physical path acts as a time-varying low-pass filter, and motion introduces additional Doppler spreading and shifting. Surface waves, internal turbulence, fluctuations in the sound speed, and other small-scale phenomena contribute to random signal variations. At this time, there are no standardized models for the acoustic channel fading, and experimental measurements are often made to assess the statistical properties of the channel in particular deployment sites.

Motivated by finding reduced complexity versions of the maximum-likelihood (ML) detector for highly distorted underwater channels, a multiuser detection (MUD) algorithm for joint data detection and channel estimation based on the cyclic coordinate descent method is proposed. Assuming that the data symbols are available, they are used to estimate the channel responses, which, in turn, are used to refine the symbol estimates. Adaptive estimation is performed using minimum mean square error as the overall optimization criterion. The receiver is implemented in a multichannel configuration, which provides the array processing gain necessary for many of the underwater acoustic channels. The complexity of the detection algorithm is linear in the number of receive elements and it does not depend on the modulation level of the transmitted signals. The algorithm has been tested using real data obtained over a 2-km shallow-water channel in a 20-kHz band, demonstrating good results.

For underwater acoustic channels where multipath spread is measured in tens of symbol intervals at high transmission rates, multichannel equalization required for bandwidth-efficient communications may become prohibitively complex for real-time implementation. To reduce computational complexity of signal processing and improve performance of data detection, receiver structures that are matched to the physical channel characteristics are investigated. A decision-feedback equalizer is designed which relies on an adaptive channel estimator to compute its parameters. The channel estimate is reduced in size by selecting only the significant components, whose delay span is often much shorter than the multipath spread of the channel. Optimal coefficient selection (sparsing) is performed by truncation in magnitude. This estimate is used to cancel the post-cursor ISI prior to linear equalization. Spatial diversity gain is achieved by a reduced-complexity pre-combining method which eliminates the need for a separate channel estimator/equalizer for each array element. The advantages of this approach are reduction in the number of receiver parameters, optimal implementation of sparse feedback, and efficient parallel implementation of adaptive algorithms for the pre-combiner, the fractionally-spaced channel estimators and the short feedforward equalizer filters. Receiver algorithm is applied to real data transmitted at 10 kbps over 3 km in shallow water, showing excellent results.

Random linear packet coding combined with adaptive power and rate control is being considered as an alternative to traditional ARQ techniques for the underwater acoustic channel. We first analyze a scheme where the number of coded packets to transmit is determined so as to achieve a pre-determined reliability at the receiver, and hence eliminate the need for explicit feedback. We next investigate joint power and rate control with constrained resources. Using the channel gain information which is obtained via feedback from the receiver, the transmitter adjusts its transmit power and the number of coded packets such that the average energy per bit is minimized. We impose two main constraints for the optimization: (a) the transmit power should be within a maximum available power, and (b) the number of coded packets should not exceed a maximum value. Under these constraints, we define adaptation policies to minimize the average energy per bit and show analytical results for average energy savings available from the adaptation policies. We also show experimental results obtained using the measured channel gains from the SPACE-08 experiment, an at-sea experiment conducted off the coast of Martha's Vineyard in Massachusetts.

Air-to-Ground (A-G) communication networks play an important role providing wireless access to areas that lack cellular or satellite infrastructure. The use of Multiple-Input Multiple-Output (MIMO) technology has been considered to increase the data rate and range of these systems, and over-the-air experiments have shown promising results, however, they lack a detailed characterization of the A-G channel. In this paper an extension to the Geometric Air-to- Ground Ellipsoidal (GAGE) radio channel model is proposed to predict the performance of MIMO for low- altitude A-G systems. The geometry and propagation loss characteristics of the model are defined, and example results for a hilly rural environment are shown for 2x2 Spatial Multiplexing (SMX) and Space-Time Block Coding (STBC). The results predict that an uncoded multi-carrier system can use STBC for gains up to 16 dB or use SMX to increase the throughput by a factor of two.

We propose a spatial combining technique for detection of multicarrier underwater acoustic communication signals using a vertical array of receivers. Instead of estimating the channel for each receiver independently and ignoring the angles of arrival of each of the channel paths, the suggested technique is based on spatially filtering each of the channel paths by steering a multi-frequency beamformer to their angles of arrival. As the number of channel paths is usually smaller than the number of the receivers, this process reduces the dimensionality of the model and involves a lower computational load. The signals at the output of the beamformer are then decoded in a coherent or differentially-coherent form. Simulation results show that angle-of-arrival-based detection outperforms the traditional angle-of-arrival-ignorant spatial combining methods for low signal to noise ratio and moderate range.

The recent surge of implantable and wearable medical devices have paved the way for realizing intra-body networks (IBNs). Traditional RF-based techniques fall short in wirelessly connecting such devices owing to absorption within body tissues. A different approach is known as galvanic coupling, which employs weak electrical current within naturally conducting tissues to enable intra-body communication. This work is focused on channel characterization of the human body tissues considering the propagation of such electrical signals through it that carry data. Experiments were conducted using porcine tissue (in lieu of actual human tissue) with skin, fat and muscle layers in the frequency range of 100 kHz to 1 MHz. By utilizing single-carrier BPSK modulated Pseudorandom Noise Sequences, a correlative channel sounding system was implemented, leading to the following contributions: (1) measurements of the channel impulse and frequency response, (2) a noise analysis and capacity estimation, and (3) the comparison of results with existing models.

High rate underwater communications have traditionally relied on equalization methods to overcome the intersymbol interference (ISI) caused by multipath propagation. An alternative technique has emerged in the form of time-reversal, which comes at virtually no cost in computational complexity, but sacrifices the data rate and relies on the use of large arrays to reduce ISI. In this paper, spatiotemporal processing for optimal multipath suppression is addressed analytically. A communication link between a single element and an array is considered in several scenarios: uplink and downlink transmission, with and without channel state information and varying implementation complexity. Transmit/receive techniques are designed which simultaneously maximize the data detection signal-to-noise ratio and minimize the residual ISI, while maintaining maximal data rate in a given bandwidth and satisfying a constraint on transmitted energy. The performance of so-obtained focusing techniques is compared to the standard ones on a shallow water channel operating in a 5 kHz bandwidth around a 15 kHz center frequency. Results demonstrate benefits of focusing techniques whose performance is not conditioned on the array size. Optimal configurations are intended as a basis for adaptive system implementation in which channel estimates will replace the actual values.

Multicarrier code-division multiple access (MC-CDMA) combines multicarrier transmission with direct sequence spread spectrum. Different approaches have been adopted which do not assume a perfectly known channel. We examine the forward-link performance of decision-directed adaptive detection schemes, with and without explicit channel estimation, for MC-CDMA systems operating in fast fading channels. We analyze theoretically the impact of channel estimation errors by first considering a simpler system employing a threshold orthogonality restoring combining (TORC) detector with a Kalman channel estimator. We show that the performance deteriorates significantly as the channel fading rate increases and that the fading rate affects the selection of system parameters. We examine the performance of more realistic schemes based on the minimum mean square error (MMSE) criterion using least mean square (LMS) and recursive least square (RLS) adaptation. We present a discussion which compares the decision-directed and pilot-aided approaches and explores the tradeoffs between channel estimation overhead and performance. We find that there is a fading rate range where each method provides a good tradeoff between performance and overhead. We conclude that the MMSE per carrier decision-directed detector with RLS estimation combines good performance in low to moderate fading rates, robustness in parameter variations, and relatively low complexity and overhead. For higher fading rates, however, only pilot-symbol-aided detectors are appropriate.

Random linear packet coding is considered for channels that experience fading and have long propagation delay, such as the underwater acoustic channels. Previously, we employed power control (adjusting the transmission power according to the channel gain) and rate control (adjusting the number of coded packets according to the channel gain) to counteract the effects of fading. For such policies, it was shown that there exists an optimal number of coded packets (when employing power control) or optimal transmission power (when employing rate control) for which the energy required per bit of information transmitted is minimized. In this paper, we present a strategy to jointly optimize the transmission power and the number of coded packets. We present two optimization criteria, i.e., (a) minimizing the average energy per bit for transmission and (b) maximizing the throughput. Given the statistics of the channel, we compute the average energy per bit and the average throughput under each criterion, to make a choice based on the desired tradeoff. In applications with limited power, minimizing the average energy per bit will be the guiding principle, while in time-critical applications maximizing the average throughput will dictate the choice.

We use a per-path Rician fading model to analyze the capacity of acoustic channels, and provide experimental data to confirm the practicality of simulation results. Three power allocation policies are considered: water-filling, uniform power allocation across selected, channel-favored frequencies (“on-off” carriers in an OFDM system), and uniform power allocation across all carriers irrespective of the channel (“all-on”). The impact of channel estimation errors and feedback delay is taken into account. The three policies are found to differ little in terms of the achievable rate, and to suffer similar loss from imperfect channel knowledge at the receiver (about 1 bps/Hz loss from 4 bps/Hz at 20 dB for the experimental channel). Unlike water-filling and on-off power allocation, which are additionally sensitive to outdated channel feedback, all-on uniform power allocation does not require feedback and is simple to implement, thus emerging as a justified practical solution.

We propose a method for channel estimation in orthogonal frequency division multiplexing (OFDM) systems. Unlike the conventional sample-spaced and sub-sample-spaced methods, which target the taps of an equivalent discrete-delay channel response, this method targets the physical propagation paths in a continuous-delay domain. Numerical results quantify its benefits over the conventional least-squares, orthogonal matching pursuit, and mixed-norm methods. Assuming that channel is slowly varying from one OFDM block to another, we also develop an adaptive algorithm for channel tracking. Performance is illustrated through simulation.

Random linear packet coding is considered for efficient broadcasting in networks with large propagation delays, such as underwater acoustic networks. To additionally overcome the effects of fading, we combine packet coding with adaptive power control, whereby the transmitter adjusts its power upon receiving feedback from the receiver on the current state of the channel (locally-averaged, large-scale gain). We investigate two power adjustment rules: the worst link rule and the average link rule. In the first case, the transmit power is adjusted in accordance with the link that has the lowest channel gain, while in the second case, the power is adjusted in accordance with the average of the gains on all links. System performance is evaluated based on the average energy per bit of successfully transmitted bit of information, using (i) simulated channels, (ii) experimentally recorded gain values from the MISSION 2012 experiment, and (iii) actual network deployment from the MISSION 2013 experiment conducted off the coast of Singapore. Results indicate energy savings on the order of several dB compared to systems that do not use power control.

We investigate the use of differential space fre- quency block codes (SFBCs) with orthogonal frequency division multiplexing (OFDM) over underwater acoustic channels. While SFBC efficiently exploits spatial transmit diversity, differentially coherent detection eliminates the need for extensive signal pro- cessing required for channel tracking. System performance is demonstrated using real data transmitted in the 12 !26 kHz acoustic band from a vehicle moving at 0.5 !2 m/s and received over a 100 m shallow water channel, using 4-QAM and a varying number of carriers ranging from 128 to 2048. Performance results demonstrate the advantage of the differentially coherent SFBC detection over the conventional, coherent SFBC detection which suffers from imperfect channel estimation.

With the advances in acoustic modem technology that enabled high-rate reliable communications, current research focuses on communication between various remote instruments within a network environment. Underwater acoustic (UWA) networks are generally formed by acoustically connected ocean-bottom sensors, autonomous underwater vehicles, and a surface station, which provides a link to an on-shore control center. While many applications require long-term monitoring of the deployment area, the battery-powered network nodes limit the lifetime of UWA networks. In addition, shallow-water acoustic channel characteristics, such as low available bandwidth, highly varying multipath, and large propagation delays, restrict the efficiency of UWA networks. Within such an environment, designing an UWA network that maximizes throughput and reliability while minimizing the power consumption becomes a very difficult task. The goal of this paper is to survey the existing network technology and its applicability to underwater acoustic channels. In addition, we present a shallow-water acoustic network example and outline some future research directions.

Error probability of an adaptive multiuser diversity receiver is evaluated in terms of channel fading rate and the number of code-division multiple access users. Fading-induced performance loss, which leads to the error probability floor, is established for the proposed coherent combining scheme and compared to that of the differentially coherent receiver with equal-gain combining.

An adaptive decorrelating multiuser detector is considered for application in Rayleigh fading multipath channels with significant fading rate (Doppler spread). A suboptimal receiver structure, in which decorrelation is decoupled from multipath recombining, allows efficient implementation of adaptive channel estimation, e.g. via LMS algorithm. The channel estimates are used to perform maximum ratio combining. Bit error rate is evaluated analytically as a function of fading statistics and receiver tracking parameters. Results demonstrate performance sensitivity to the choice of the LMS step size when the channel is modeled as a second-order AR process. Performance degradation increases with fading rate, leading to the saturation of the error probability at a level determined by the fading rate of the channel and the deviation of the step size from the optimal value. The receiver is near-far resistant regardless of the fading rate of the channel.

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.

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.

Multipath propagation in underwater acoustic channels causes intersymbol interference in the transmission of digital communication signals. An increase of the transmission rate on a multipath channel results in longer intersymbol interference, which ultimately limits the performance of a phase‐coherent digital communication system. Recent experimental results, however, show a seemingly surprising result: an increase in transmission rate resulted in improved system performance. An explanation for this phenomenon is found in the time variation of the ocean multipath. In strongly fluctuating shallow water channels, higher transmission rates allow for more frequent sampling of the rapidly varying channel, thus resulting in a better tracking capability of the receiver. Experimental results obtained in shallow water show a substantial improvement in performance of QPSK coherent detection over a 1‐mile range, as the data rate is increased from 5 to 20 kilobits per second. A theoretical analysis based on stochast...

In recent years, underwater acoustic (UWA) communications have received much attention as their applications have begun to shift from military toward commercial. Digital communications through UWA channels differ substantially from those in other media, such as radio channels, due to severe signal degradations caused by multipath propagation and high temporal and spatial variability of the channel conditions. The design of underwater acoustic communication systems has until recently relied on the use of noncoherent modulation techniques. However, to achieve high data rates on the severely band-limited UWA channels, bandwidth-efficient modulation techniques must be considered, together with array processing for exploitation of spatial multipath diversity. The new generation of underwater communication systems, employing phase-coherent modulation techniques, has a potential of achieving at least an order of magnitude increase in data throughput. The emerging communication scenario in which the modern underwater acoustic systems mill operate is that of an underwater network consisting of stationary and mobile nodes. Current research focuses on the development of efficient signal processing algorithms, multiuser communications in the presence of interference, and design of efficient modulation and coding schemes. This paper presents a review of recent results and research problems in high-speed underwater acoustic communications, focusing on the bandwidth-efficient phase-coherent methods. Experimental results are included to illustrate the state-of-the-art coherent detection of digital signals transmitted at 30 and 40 kb/s through a rapidly varying one-mile shallow water channel.

High-throughout multiple-access communication networks are being considered for use in underwater acoustic channels. Bandwidth limitations of underwater acoustic channels require receivers to process broad-band communications signals in the presence of several active users. To deal with the resulting multiple-access interference in addition to high intersymbol interference, the spatial variability of ocean multipath is exploited in a multichannel multiuser receiver. Two configurations of such a receiver, a centralized and a decentralized one, are presented in fully adaptive modes of operations. While greatly reducing intersymbol and multiple-access interference, spatial diversity implies high increase in adaptive multiuser receiver complexity. To reduce the complexity of the optimal multichannel combiner, spatial structure of multipath is exploited. The complexity of resulting adaptive decentralized multichannel multiuser receiver is reduced at almost no cost in performance. Comparison of proposed multichannel receivers in an experimental shallow water channel demonstrates superior performance of spatial signal combining. The use of multiple input channels is shown to provide high level of tolerance for the near-far effect in both centralized and decentralized receivers. Decentralized receiver with reduced-complexity combining is found to satisfy the performance/complexity trade-off required for practical receiver realization in shallow water networks.

The performance of antenna diversity coherent and differentially coherent linear multiuser receivers is analyzed in frequency-nonselective Rayleigh fading CDMA channels with memory. The estimates of the complex fading processes are utilized for maximal-ratio combining and carrier recovery of the coherent multiuser receiver. To analyze the impact of channel estimation errors on the receiver performance, error probability is assessed directly in terms of the fading rate and the number of active users, showing the penalty imposed by imperfect channel estimation as well as the fading-induced error probability floor. The impact of fading dynamics on the differentially coherent decorrelating receiver with equal-gain combining is quantified. While performance of multiuser receivers at lower SNR is determined by both the fading dynamics and the number of active CDMA users, performance at higher SNR is given by an error probability floor which is due to fading only and has the same value as in a single-user case. The comparison of the two receiver structures indicates that the coherent decorrelating receiver with diversity reception may be preferable to the differentially coherent one in nonselective fading CDMA channels with memory.

Multichannel processing of high‐speed underwater acoustic communication signals requires computationally intensive receiver algorithms. The size of adaptive filters, determined by the extent of ocean multipath, increases with signaling rate and limits system performance through large noise enhancement and increased sensitivity of computationally efficient algorithms to numerical errors. To overcome these limitations, reduction in receiver complexity is achieved by exploiting the relationship between optimal diversity combining and beamforming. Under relatively simple conditions, two adaptive receivers, one based on diversity combining which does not rely on any spatial signal distribution, and the other based on optimal beamforming, are shown to achieve the same performance. The beamforming approach, however, leads to a receiver of lower complexity. Carrying these observations over to a general case of broadband transmission through an unknown channel, a fully adaptive receiver is developed which incorporates a multi‐input multi‐output, many‐to‐few combiner, and a reduced‐complexity multichannel equalizer. Receiver operations are optimized jointly to ensure minimum mean‐squared error performance of data detection. Results of processing experimental shallow water data demonstrate the capability to fully exploit spatial diversity of underwater multipath while keeping the complexity at an acceptable level.

A coherent receiver with a decision-feedback equalizer (DFE) operating on a Rayleigh fading channel under a suitable adaptive algorithm is considered. In the analysis of a DFE, a common assumption is that the receiver has perfect knowledge of the channel impulse response. However, this is not the case in practice, and for a rapidly fading channel, errors in channel tracking can become significant. We analyze theoretically the impact of these errors on the performance of a multichannel DFE. The expressions obtained for the achievable average MPSK bit error probabilities depend on the estimation error covariance. In order to specify this matrix, we focus on a special case when a Kalman filter is used as an optimal channel estimator. In this case, the probability of bit error can be assessed directly in terms of channel fading model parameters, the most interesting of which is the fading rate. Our results show the penalty imposed by imperfect channel estimation, as well as the fading-induced irreducible error rates. >