Improvement of Time-Reversal Communications Using Adaptive Channel Equalizers

Song, H. C.; Hodgkiss, William S.; Kuperman, W. A.; Stevenson, Mark; Akal, T.

doi:10.1109/joe.2006.876139

Cited by 136 publications

(93 citation statements)

References 20 publications

(45 reference statements)

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“…An equalizer is thus generally preferred to time-reversal. Attempts have been made to include both time-reversal and equalization into one communication system [17,18,98].…”

Section: Stojanovic Et Al Pioneered the Analysis And Application Of mentioning

confidence: 99%

Analysis of and techniques for adaptive equalization for underwater acoustic communication

Blair¹

2011

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Underwater wireless communication is quickly becoming a necessity for applications in ocean science, defense, and homeland security. Acoustics remains the only practical means of accomplishing long-range communication in the ocean. The acoustic communication channel is fraught with difficulties including limited available bandwidth, long delay-spread, time-variability, and Doppler spreading. These difficulties reduce the reliability of the communication system and make high data-rate communication challenging. Adaptive decision feedback equalization is a common method to compensate for distortions introduced by the underwater acoustic channel. Limited work has been done thus far to introduce the physics of the underwater channel into improving and better understanding the operation of a decision feedback equalizer. This thesis examines how to use physical models to improve the reliability and reduce the computational complexity of the decision feedback equalizer. The specific topics covered by this work are: how to handle channel estimation errors for the time varying channel, how to use angular constraints imposed by the environment into an array receiver, what happens when there is a mismatch between the true channel order and the estimated channel order, and why there is a performance difference between the direct adaptation and channel estimation based methods for computing the equalizer coefficients. For each of these topics, algorithms are provided that help create a more robust equalizer with lower computational complexity for the underwater channel.

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“…An equalizer is thus generally preferred to time-reversal. Attempts have been made to include both time-reversal and equalization into one communication system [17,18,98].…”

Section: Stojanovic Et Al Pioneered the Analysis And Application Of mentioning

confidence: 99%

Analysis of and techniques for adaptive equalization for underwater acoustic communication

Blair¹

2011

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“…Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. We have shown that the time reversal approach provides nearly optimal performance in conjunction with channel equalization [2][3][4][5][6]. The benefit of the time reversal approach is lower computational complexity for two reasons.…”

Section: Form Approved Omb No 0704-0188mentioning

confidence: 99%

Shallow Water Fluctuations and Communications

Song

Kuperman

2008

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LONG TERM GOALSThe central effort of this research will be the development of robust algorithms for reliable, high data rate, acoustic communications in a dynamic ocean environment and demonstration of their use with data collected in a shallow water environment. OBJECTIVEWe will study shallow water fluctuation physics and the enhancement of performance of broad area acoustic communications in shallow water by building on developments in adaptive channel equalizers in conjunction with the time reversal approach. APPROACHTime reversal communications exploits spatial diversity to achieve spatial and temporal focusing in complex ocean environments. Spatial diversity easily can be provided by a vertical array in a waveguide. Alternatively, spatial diversity can be obtained from a virtual horizontal array generated by two elements, a transmitter and a receiver, due to relative motion between them, referred to as a synthetic aperture. In this case, the same data is transmitted periodically. The cost is a reduction in the overall data rate by the number of transmissions accumulated in generation of synthetic aperture. In addition, Doppler compensation is required involving Doppler shift estimation and re-sampling of the broadband communication signal.Recently we have investigated the feasibility of synthetic aperture communications (SAC) in shallow water [1]. In that work, simple on/off keying modulation was employed to minimize the complexity and not require coherent demodulation. Furthermore, the motion was almost transversal resulting in a small Doppler shift. In this case diversity appears to come from the data being collected in an azimuthally inhomogeneous environment coupled with temporal channel variation between transmissions.

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“…Although the time reversal technique also employs an array of spatially separated receivers, it is relatively simple, effectively reduces the ISI in a multipath environment, and restores the original communication signal, thereby increasing the signal-to-noise ratio (SNR). Recently, passive time reversal processes have been widely used in underwater communication due to the simplicity of the system, in which an array is required only at the receiver [17][18][19]. Passive time reversal is related to the reciprocity of the active time reversal.…”

Section: Introductionmentioning

confidence: 99%

“…In general, the q-function depends on the complexity of the communication channel, the number of receivers in the array, and their spacing [19]. In an ideal case in which the estimated CIR has infinite bandwidth and no multipath, the q-function becomes a delta function, and the time reversal process recovers the exact original communication signal [14][15][16][17][18][19]. However, in a real ocean waveguide, the q-function is no longer the delta function, but has a main lobe and side lobes, producing a residual ISI of time compressed signal.…”

Section: Introductionmentioning

confidence: 99%

Estimate of Passive Time Reversal Communication Performance in Shallow Water

et al. 2017

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Time reversal processes have been used to improve communication performance in the severe underwater communication environment characterized by significant multipath channels by reducing inter-symbol interference and increasing signal-to-noise ratio. In general, the performance of the time reversal is strongly related to the behavior of the q-function, which is estimated by a sum of the autocorrelation of the channel impulse response for each channel in the receiver array. The q-function depends on the complexity of the communication channel, the number of channel elements and their spacing. A q-function with a high side-lobe level and a main-lobe width wider than the symbol duration creates a residual ISI (inter-symbol interference), which makes communication difficult even after time reversal is applied. In this paper, we propose a new parameter, E q , to describe the performance of time reversal communication. E q is an estimate of how much of the q-function lies within one symbol duration. The values of E q were estimated using communication data acquired at two different sites: one in which the sound speed ratio of sediment to water was less than unity and one where the ratio was higher than unity. Finally, the parameter E q was compared to the bit error rate and the output signal-to-noise ratio obtained after the time reversal operation. The results show that these parameters are strongly correlated to the parameter E q .

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Improvement of Time-Reversal Communications Using Adaptive Channel Equalizers

Cited by 136 publications

References 20 publications

Analysis of and techniques for adaptive equalization for underwater acoustic communication

Analysis of and techniques for adaptive equalization for underwater acoustic communication

Shallow Water Fluctuations and Communications

Estimate of Passive Time Reversal Communication Performance in Shallow Water

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