Testing the wide-sense stationarity of bandpass signals for underwater acoustic communications

Kochańska, Iwona

doi:10.1109/inista.2017.8001208

Cited by 2 publications

(6 citation statements)

References 10 publications

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“…Moreover, the complex envelope y(t) should be a zero-mean process. According to [6], the similarity of autocorrelation functions R I I (∆t, τ) and R QQ (∆t, τ) can be expressed as the cross-correlation coefficient:…”

Section: Testing Wide-sense Stationary Assumption Fulfilmentmentioning

confidence: 99%

“…, defined similarly as in Equations (6) and 7for in-phase h I (t, τ) and quadrature h Q (t, τ) components of the impulse response h(t, τ). The cross-correlation coefficients c h IQ and c h IQQI are calculated as functions of delay τ:…”

Section: Testing Wide-sense Stationary Assumption Fulfilmentmentioning

confidence: 99%

“…Moreover, within this time interval, the signal received by the UAC system receiver represents a WSS process, and its power spectrum can be defined via a Fourier transform, according to the Wiener-Khinchin Theorem. This is especially important for signal detection performed in the frequency domain, as is the case with communication systems using the Orthogonal Frequency-Division Multiplexing (OFDM), and the Frequency Hopping Spread Spectrum (FHSS) techniques [4,6,7].…”

Section: Introductionmentioning

confidence: 99%

“…Statistical properties of the real and imaginary parts of the impulse response, measured using the correlation method, are exploited to test the WSS assumption fulfilment. In [6] a similar method is proposed to assess whether the channel is WSS/non-WSS on the basis of the complex envelope of a received probe signal. However, the method was tested only in simulation conditions.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, both methods are compared using the results of simulations and the inland water experiment. The values of correlation coefficients, which are the basis of the WSS indicator proposed in [6], are presented. These coefficients express the similarity of the autocorrelation and cross-correlation functions of the in-phase and quadrature components of the received signal and the impulse response estimated using this signal.…”

Section: Introductionmentioning

confidence: 99%

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Assessment of Wide-Sense Stationarity of an Underwater Acoustic Channel Based on a Pseudo-Random Binary Sequence Probe Signal

Kochańska

2020

Applied Sciences

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The performances of Underwater Acoustic Communication (UAC) systems are strongly related to the specific propagation conditions of the underwater channel. Designing the physical layer of a reliable data transmission system requires a knowledge of channel characteristics in terms of the specific parameters of the stochastic model. The Wide-Sense Stationary Uncorrelated Scattering (WSSUS) assumption simplifies the stochastic description of the channel, and thus the estimation of its transmission parameters. However, shallow underwater channels may not meet the WSSUS assumption. This paper proposes a method for testing the Wide-Sense Stationary (WSS) part of the WSSUS feature of a UAC channel on the basis of the complex envelope of a received probe Pseudo-Random Binary Sequence (PRBS) signal. Two correlation coefficients are calculated that can be interpreted, together, as a measure that determines whether the channel is WSS or not. A similar wide-sense stationarity assessment can be performed on the basis of the Time-Varying Impulse Response (TVIR) of a UAC channel. However, the method proposed in this paper requires fewer computational operations in the receiver of a UAC system. PRBS signal transmission tests were conducted in the UAC channel simulator and in real conditions during an inland water experiment. The correlation coefficient values obtained using the method based on the envelope of a probe signal and the method of analysing the TVIR estimates are compared. The results are similar, and thus, it is possible to assess if the UAC channel can be modelled as a WSS stochastic process without the need for TVIR estimation.

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Section: Testing Wide-sense Stationary Assumption Fulfilmentmentioning

confidence: 99%

Section: Testing Wide-sense Stationary Assumption Fulfilmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Assessment of Wide-Sense Stationarity of an Underwater Acoustic Channel Based on a Pseudo-Random Binary Sequence Probe Signal

Kochańska

2020

Applied Sciences

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Investigating Validity of Wide-Sense Stationary Assumption in Millimeter Wave Radio Channels

et al. 2019

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In this paper, impact of antenna directivity and bandwidth on the small scale fading statistics have been analyzed for millimeter-wave (mmWave) radio channels. For this purpose, small-scale fading measurements at the mmWave frequency band (58-62 GHz) are carried out using transmit and receive antennas with different antenna directivities (emulated beamforming gains). Measurements emulate a non line-of-sight scenario when the communication between transmit and receive antennas is possible only through a single multipath cluster. In order to compare results, measurements in a line-of-sight scenario with omni-directional antennas are also carried out for reference purpose. Considering two main mmWave system features i.e., high antenna directivity and higher system bandwidth, we report the following results: 1) Randomness/fading in the received signal magnitude vanishes with an increase in bandwidth. 2) The channel impulse response h (t, τ ) does not remain a wide-sense stationary (WSS) random process in the slow-time domain i.e., along t, where, the fast-time domain refers to the dimension along τ . 3) Measured channels are WSS in the frequency domain and the coherence bandwidth increases when propagation channels are illuminated with high gain antennas.INDEX TERMS Small-scale fading, channel measurements, channel models, multipath clusters, beamforming, ultra-wide band (UWB) channels, millimeter wave (mmWave) communications, MIMO, 5G.

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Testing the wide-sense stationarity of bandpass signals for underwater acoustic communications

Cited by 2 publications

References 10 publications

Assessment of Wide-Sense Stationarity of an Underwater Acoustic Channel Based on a Pseudo-Random Binary Sequence Probe Signal

Assessment of Wide-Sense Stationarity of an Underwater Acoustic Channel Based on a Pseudo-Random Binary Sequence Probe Signal

Investigating Validity of Wide-Sense Stationary Assumption in Millimeter Wave Radio Channels

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