John A. Flynn

Multichannel equalization by decision-directed passive phase conjugation: experimental results

An adaptive technique for underwater acoustic communication using passive phase conjugation (PPC) is developed. Multipath channel-parameter identification is accomplished by decision-directed model building and finite-window block-updated least squares computed by LSQR (an iterative linear systems solver). The resulting channel estimates are then used by the PPC processor to generate decisions for use in the next processing block. This architecture effectively accomplishes array equalization with low computation cost in shallow-water environments that exhibit rapidly fluctuating multipath scattering. The performance on shallow-water acoustic communications channels is demonstrated at ranges of 0.9-4.6 km under windy surface conditions and shipping noise, using measured wide-band telemetry data with binary phase-shift keying signaling. The algorithm is evaluated with sparse receiver apertures using subsets of a 14-element array.

Performance of reduced-complexity multi-channel equalizers for underwater acoustic communications

Underwater acoustic telemetry in shallow water environments is difficult due to large delay spreads, rapid fading, and reverberation clutter. Development of usable array equalizers remains an ongoing effort in the community. We evaluate three block-adaptive multichannel equalizer architectures that are effective for the underwater channel. These use a finite-window least squares (LS) approach for estimating both channel and equalizer. The channel identification model is constructed by decision-direction. The three equalizer designs are based on criteria of MMSE, zero-forcing, and space-time matched filtering justified by passive phase conjugation (PPC, or time-reversal mirror) theory. This architecture avoids committing to temporal parameter correlation models inherent in standard RLS adaptation methods. Robust numerical linear algebra technology (algorithm LSQR) iteratively solves the large linear systems involved. The performance evaluation compares MSE of the three equalizers in context of the adaptive architecture under channel estimation errors. We show an exact MSE expression for PPC equalization that includes channel identification error. The evaluations are based on data from underwater acoustic telemetry experiments made in Puget Sound, Seattle.

Acoustic Communication Using Time‐Reversal Signal Processing: Spatial and Frequency Diversity

Time‐reversal signal processing can be viewed as a form of matched filtering that operates both in time and in space. Acoustic communication represents a promising potential application of the processing. In designing a communications system, constraints are imposed by the available bandwidth and by the geometry of the time‐reversal array. In the present paper, the interplay between bandwidth and array geometry is examined. If the bandwidth is large relative to the symbol rate, time‐reversal processing can be successful with sparse arrays. If the array is well populated, the required bandwidth can be reduced. Results from experiments and data‐driven simulations are presented.

Turbo array receiver for underwater telemetry

We describe a novel, turbo-based array receiver architecture for underwater channels with large delay-Doppler spreading. We demonstrate performance on data from an underwater BPSK telemetry experiment with rapid fading, and on simulated data extended to MPSK. Compared to a classical decision-directed LS-MMSE receiver of comparable observation and filter sizes, our proposed algorithm shows dramatically improved performance. The architecture is built around a block-based multi-channel linear model that considers deterministic time-invariant (TIV) multipath and random fading. Symbol estimates are decomposed by approximated conditional mean and variance components to reflect varying degrees of uncertainty. By approximating TIV coefficients with previous estimates, observation components due to symbol uncertainty conform to a linear model. The turbo cycle refines estimates for both predicted symbols and multipath parameters, effectively mitigating decision delay in rapidly time-varying channels with large delay spread. Our presentation includes a practical and robust computation approach, essential for problems of this size.

Decision-directed passive phase conjugation for underwater acoustic communications with results from a shallow-water trial

We describe a novel decision-directed structure that extends the passive phase conjugation (PPC) array demodulation method of Rouseff et al.. The PPC transmission scheme is a single source and multiple receive sensors. Our algorithm uses an initial training period with known data, followed by block-update LS channel estimation via LSQR (Paige and Saunders1982) iterations, and subsequent memoryless decisions. Decisions are circulated back into the LS model for the next estimation block. Performance on a shallow-water acoustic channel is shown at ranges up to 4.6 km under windy surface conditions and shipping noise. The algorithm demonstrates good bit error rates, and robustly tracks time-varying channels. Its unquantized output can be further processed by conventional equalizers.

Decision-directed Passive Phase Conjugation for underwater acoustic communication: experimental results

Passive Phase Conjugation is a method for coherent underwater acoustic communication that uses multiple receive-only hydrophones. The technique is essentially a space-time matched filter. Previous results from a field experiment demonstrating the method were reported by Rouseff et al. [IEEE J. Oceanic Eng. 26, pp. 821-831, 2001]. In this paper, performance results are presented for Decision-Directed Passive Phase Conjugation, an adaptive extension to the basic technique. Using decision directed estimates for the channel impulse response, the method requires training overhead of less than 2% for the 10000-symbol packets used in the experiment. Mean-Square-Error and Bit-Error-Rates are reported for various array configurations including a three-element horizontal array.

Decision‐directed passive phase conjugation: A robust and simple architecture for array receivers in the underwater communications channel

A decision‐directed extension to the passive phase conjugation (PPC) technique of array demodulation for underwater communications channels is presented. The PPC method utilizes a probe signal from the transmitter to exploit the time‐reversal concept in a one‐way fashion at the receiver on subsequent unknown data signals [D. R. Jackson et al., Conf. Rec. 34th Asilomar Conf. on Signals, Syst., and Comp., Vol. 1, 680–683 (2000)]. PPC demonstrated excellent equalization of communication bursts in shallow water with sparse array reception. The decision‐directed extension to PPC presented here virtually eliminates the need for repeated channel probing, while improving channel estimation in rapidly varying, noisy environments. The technique utilizes decision‐directed channel modeling in a fixed‐window linear statistical framework, a deterministic least squares optimization criteria, and robust conjugate‐gradient numerical methods driving the PPC demodulator. The resulting architecture scales linearly with the n...