210 research outputs found
Multiple-Resampling Receiver Design for OFDM Over Doppler-Distorted Underwater Acoustic Channels
Cataloged from PDF version of article.In this paper, we focus on orthogonal frequency-divisionmultiplexing
(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 scalingmay not be appropriatein 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
thatutilizemultiple-resampling (MR)branches,eachmatched 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 approachis 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
An Iterative Receiver for OFDM With Sparsity-Based Parametric Channel Estimation
In this work we design a receiver that iteratively passes soft information
between the channel estimation and data decoding stages. The receiver
incorporates sparsity-based parametric channel estimation. State-of-the-art
sparsity-based iterative receivers simplify the channel estimation problem by
restricting the multipath delays to a grid. Our receiver does not impose such a
restriction. As a result it does not suffer from the leakage effect, which
destroys sparsity. Communication at near capacity rates in high SNR requires a
large modulation order. Due to the close proximity of modulation symbols in
such systems, the grid-based approximation is of insufficient accuracy. We show
numerically that a state-of-the-art iterative receiver with grid-based sparse
channel estimation exhibits a bit-error-rate floor in the high SNR regime. On
the contrary, our receiver performs very close to the perfect channel state
information bound for all SNR values. We also demonstrate both theoretically
and numerically that parametric channel estimation works well in dense
channels, i.e., when the number of multipath components is large and each
individual component cannot be resolved.Comment: Major revision, accepted for IEEE Transactions on Signal Processin
Applying Spatial Diversity to Mitigate Partial Band Interference in Undersea Networks
Many acoustic channels suffer from interference which is neither narrowband nor impulsive. This relatively long duration partial band interference can be particularly detrimental to system performance. We survey recent work in interference mitigation and orthogonal frequency division multiplexing (OFDM) as background motivation to develop a spatial diversity receiver for use in underwater networks. The network consists of multiple distributed cabled hydrophones that receive data transmitted over a time-varying multipath channel in the presence of partial band interference produced by interfering active sonar signals as well as marine mammal vocalizations. In operational networks, many “dropped” messages are lost due to partial band interference which corrupts different portions of the received signal depending on the relative position of the interferers, information source and receivers due to the slow speed of propagation
Cost Function based Soft Feedback Iterative Channel Estimation in OFDM Underwater Acoustic Communication
Underwater Acoustic (UWA) communication is mainly characterized by bandwidth limited complex UWA channels. Orthogonal Frequency Division Multiplexing (OFDM) solves the bandwidth problem and an efficient channel estimation scheme estimates the channel parameters. Iterative channel estimation refines the channel estimation by reducing the number of pilots and coupling the channel estimator with channel decoder. This paper proposes an iterative receiver for OFDM UWA communication, based on a novel cost function threshold driven soft decision feedback iterative channel technique. The receiver exploits orthogonal matching pursuit (OMP) channel estimation and low density parity check (LDPC) coding techniques after comparing different channel estimation and coding schemes. The performance of the proposed receiver is verified by simulations as well as sea experiments. Furthermore, the proposed iterative receiver is compared with other non-iterative and soft decision feedback iterative receivers
Vector Approximate Message Passing based Channel Estimation for MIMO-OFDM Underwater Acoustic Communications
Accurate channel estimation is critical to the performance of orthogonal
frequency-division multiplexing (OFDM) underwater acoustic (UWA)
communications, especially under multiple-input multiple-output (MIMO)
scenarios. In this paper, we explore Vector Approximate Message Passing (VAMP)
coupled with Expected Maximum (EM) to obtain channel estimation (CE) for MIMO
OFDM UWA communications. The EM-VAMP-CE scheme is developed by employing a
Bernoulli-Gaussian (BG) prior distribution for the channel impulse response,
and hyperparameters of the BG prior distribution are learned via the EM
algorithm. Performance of the EM-VAMP-CE is evaluated through both synthesized
data and real data collected in two at-sea UWA communication experiments. It is
shown the EM-VAMP-CE achieves better performance-complexity tradeoff compared
with existing channel estimation methods.Comment: Journal:IEEE Journal of Oceanic Engineering(Date of
Submission:2022-06-25
Soft-Decision-Driven Sparse Channel Estimation and Turbo Equalization for MIMO Underwater Acoustic Communications
Multi-input multi-output (MIMO) detection based on turbo principle has been shown to provide a great enhancement in the throughput and reliability of underwater acoustic (UWA) communication systems. Benefits of the iterative detection in MIMO systems, however, can be obtained only when a high quality channel estimation is ensured. In this paper, we develop a new soft-decision-driven sparse channel estimation and turbo equalization scheme in the triply selective MIMO UWA. First, the Homotopy recursive least square dichotomous coordinate descent (Homotopy RLS-DCD) adaptive algorithm, recently proposed for sparse single-input single-output system identification, is extended to adaptively estimate rapid time-varying MIMO sparse channels. Next, the more reliable a posteriori soft-decision symbols, instead of the hard decision symbols or the a priori soft-decision symbols, at the equalizer output, are not only feedback to the Homotopy RLS-DCD-based channel estimator but also to the minimum mean-square-error (MMSE) equalizer. As the turbo iterations progress, the accuracy of channel estimation and the quality of the MMSE equalizer are improved gradually, leading to the enhancement in the turbo equalization performance. This also allows the reduction in pilot overhead. The proposed receiver has been tested by using the data collected from the SHLake2013 experiment. The performance of the receiver is evaluated for various modulation schemes, channel estimators, and MIMO sizes. Experimental results demonstrate that the proposed a posteriori soft-decision-driven sparse channel estimation based on the Homotopy RLS-DCD algorithm and turbo equalization offer considerable improvement in system performance over other turbo equalization schemes
Fifty Years of Noise Modeling and Mitigation in Power-Line Communications.
Building on the ubiquity of electric power infrastructure, power line communications (PLC) has been successfully used in diverse application scenarios, including the smart grid and in-home broadband communications systems as well as industrial and home automation. However, the power line channel exhibits deleterious properties, one of which is its hostile noise environment. This article aims for providing a review of noise modeling and mitigation techniques in PLC. Specifically, a comprehensive review of representative noise models developed over the past fifty years is presented, including both the empirical models based on measurement campaigns and simplified mathematical models. Following this, we provide an extensive survey of the suite of noise mitigation schemes, categorizing them into mitigation at the transmitter as well as parametric and non-parametric techniques employed at the receiver. Furthermore, since the accuracy of channel estimation in PLC is affected by noise, we review the literature of joint noise mitigation and channel estimation solutions. Finally, a number of directions are outlined for future research on both noise modeling and mitigation in PLC
Doctor of Philosophy
dissertationThe demand for high speed communication has been increasing in the past two decades. Multicarrier communication technology has been suggested to address this demand. Orthogonal frequency-division multiplexing (OFDM) is the most widely used multicarrier technique. However, OFDM has a number of disadvantages in time-varying channels, multiple access, and cognitive radios. On the other hand, filterbank multicarrier (FBMC) communication has been suggested as an alternative to OFDM that can overcome the disadvantages of OFDM. In this dissertation, we investigate the application of filtered multitone (FMT), a subset of FBMC modulation methods, to slow fading and fast fading channels. We investigate the FMT transmitter and receiver in continuous and discrete time domains. An efficient implementation of FMT systems is derived and the conditions for perfect reconstruction in an FBMC communication system are presented. We derive equations for FMT in slow fading channels that allow evaluation of FMT when applied to mobile wireless communication systems. We consider using fractionally spaced per tone channel equalizers with different number of taps. The numerical results are presented to investigate the performance of these equalizers. The numerical results show that single-tap equalizers suffice for typical wireless channels. The equalizer design study is advanced by introducing adaptive equalizers which use channel estimation. We derive equations for a minimum mean square error (MMSE) channel estimator and improve the channel estimation by considering the finite duration of channel impulse response. The results of optimum equalizers (when channel is known perfectly) are compared with those of the adaptive equalizers, and it is found that a loss of 1 dB or less incurs. We also introduce a new form of FMT which is specially designed to handle doubly dispersive channels. This method is called FMT-dd (FMT for doubly dispersive channels). The proposed FMT-dd is applied to two common methods of data symbol orientation in the time-frequency space grid; namely, rectangular and hexagonal lattices. The performance of these methods along with OFDM and the conventional FMT are compared and a significant improvement in performance is observed. The FMT-dd design is applied to real-world underwater acoustic (UWA) communication channels. The experimental results from an at-sea experiment (ACOMM10) show that this new design provides a significant gain over OFDM. The feasibility of implementing a MIMO system for multicarrier UWA communication channels is studied through computer simulations. Our study emphasizes the bandwidth efficiency of multicarrier MIMO communications .We show that the value of MIMO to UWA communication is very limited
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