Journal articles: 'Doppler spread'

1

Benani, Abdelmoumen, Andre Carr, and Martin Quenneville. "Doppler spread technique." IEEE Vehicular Technology Magazine 4, no. 1 (March 2009): 78–86. http://dx.doi.org/10.1109/mvt.2008.931621.

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Dang, Qun, and Xiao Li Lei. "Doppler Frequency Shift Tolerance Extension in Burst Spread Spectrum Communication System." Advanced Materials Research 443-444 (January 2012): 237–40. http://dx.doi.org/10.4028/www.scientific.net/amr.443-444.237.

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A method to extend Doppler frequency discrimination tolerance is proposed for quick acquirement PN-code and Doppler frequency in TDMA burst spread spectrum communication system. According to Doppler’s different impacts on the correlation Peak and data demodulation, PN-code is acquired through single channel matched-filters, and parallel multi-channel correlators are used in the data demodulation branch channel. Thus, with using frame head prior information in data channel instead of traditional Cross-Product Automatic Frequency Control (CPAFC), the Doppler frequency shift discrimination tolerance is extended. Simulation and experiment show that frequency and PN-code can be acquired in several data periods, and synchronous time and the resources consumption are effectively reduced.

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Krasny, L., H. Arslan, D. Koilpillai, and S. Chennakeshu. "Doppler spread estimation in mobile radio systems." IEEE Communications Letters 5, no. 5 (May 2001): 197–99. http://dx.doi.org/10.1109/4234.922758.

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4

KO, Y. C. "Doppler Spread Estimation in Mobile Communication Systems." IEICE Transactions on Communications E88-B, no. 2 (February 1, 2005): 724–28. http://dx.doi.org/10.1093/ietcom/e88-b.2.724.

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5

Howard, S. J., and K. Pahlavan. "Doppler spread measurements of indoor radio channel." Electronics Letters 26, no. 2 (1990): 107. http://dx.doi.org/10.1049/el:19900074.

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Hines, Colin O. "The Doppler spread theory and parameterization revisited." Journal of Atmospheric and Solar-Terrestrial Physics 66, no. 11 (July 2004): 949–56. http://dx.doi.org/10.1016/j.jastp.2004.02.005.

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Baddour, K. E., and N. C. Beaulieu. "Robust Doppler spread estimation in nonisotropic fading channels." IEEE Transactions on Wireless Communications 4, no. 6 (November 2005): 2677–82. http://dx.doi.org/10.1109/twc.2005.858362.

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Frigyes, I., B. G. Molnár, R. Vallet, Z. Herczku, and Z. Bodnár. "Doppler spread characteristics of satellite personal communication channels." International Journal of Satellite Communications 19, no. 3 (May 2001): 251–62. http://dx.doi.org/10.1002/sat.685.

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Okada, Minoru, Hideaki Takayanagi, and Heiichi Yamamoto. "Array antenna assisted doppler spread compensator for OFDM." European Transactions on Telecommunications 13, no. 5 (September 2002): 507–12. http://dx.doi.org/10.1002/ett.4460130511.

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Huang, Pengda, Dinesh Rajan, and Joseph Camp. "An Autoregressive Doppler Spread Estimator for Fading Channels." IEEE Wireless Communications Letters 2, no. 6 (December 2013): 655–58. http://dx.doi.org/10.1109/wcl.2013.091113.130593.

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11

Rice, Joseph, Paul Baxley, Homer Bucker, Richard Shockley, Dale Green, John Proakis, and John Newton. "Doppler spread in an undersea acoustic transmission channel." Journal of the Acoustical Society of America 103, no. 5 (May 1998): 2782. http://dx.doi.org/10.1121/1.422266.

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12

Zhang, Yan, Zunwen He, Wancheng Zhang, Limin Xiao, and Shidong Zhou. "Measurement-Based Delay and Doppler Characterizations for High-Speed Railway Hilly Scenario." International Journal of Antennas and Propagation 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/875345.

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This paper presents results for delay and Doppler spread characterization in high-speed railway (HSR) hilly scenario. To investigate the propagation characteristics in this specific terrain, a measurement campaign is conducted along the “Guangzhou-Shenzhen” HSR in China. A wideband channel sounder with 40 MHz bandwidth is used to collect raw data at 2.4 GHz band. The delay spread and Doppler frequency features are analyzed based on measured data. It is found that there are abundant multipath components (MPCs) in this scenario. We present the relationship between the delay spreads and the transceiver distances. The measured route can be divided into four areas with different delay and Doppler characteristics. Finally, a tapped delay line (TDL) model is proposed to parameterize the channel responses in the HSR hilly environment, which is supposed to provide criterions for evaluations of the radio interface and development of wireless communication system.

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TAO, X., C. ZHANG, and J. LU. "Doppler Diversity in MC-CDMA Systems with T-ZCZ Sequences for Doppler Spread Cancelation." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E90-A, no. 11 (November 1, 2007): 2361–68. http://dx.doi.org/10.1093/ietfec/e90-a.11.2361.

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14

Yanovsky, F. J., C. M. H. Unal, H. W. J. Russchenberg, and L. P. Ligthart. "Doppler-Polarimetric Weather Radar: Returns from Wide Spread Precipitation." Telecommunications and Radio Engineering 66, no. 8 (2007): 715–27. http://dx.doi.org/10.1615/telecomradeng.v66.i8.20.

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15

SHENG, Bin, Pengcheng ZHU, and Xiaohu YOU. "An Enhanced Doppler Spread Estimation Method for OFDM Systems." IEICE Transactions on Communications E95.B, no. 12 (2012): 3911–14. http://dx.doi.org/10.1587/transcom.e95.b.3911.

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16

Reyes, Hector, Naima Kaabouch, and Wen-Chen Hu. "Spectrum Channel Characterization Using Delay and Doppler Spread Parameters." Journal of Communications 9, no. 3 (2014): 234–40. http://dx.doi.org/10.12720/jcm.9.3.234-240.

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17

Capoglu, I. R., Ye Li, and A. Swami. "Effect of Doppler spread in OFDM-based UWB systems." IEEE Transactions on Wireless Communications 4, no. 5 (September 2005): 2559–67. http://dx.doi.org/10.1109/twc.2005.853978.

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18

ZHANG, P., X. XU, G. BI, X. CAO, and J. ZHAO. "Iterative Joint Correlation Interval Selection and Doppler Spread Estimation." IEICE Transactions on Communications E89-B, no. 11 (November 1, 2006): 3156–59. http://dx.doi.org/10.1093/ietcom/e89-b.11.3156.

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19

Mohammadkarimi, Mostafa, Ebrahim Karami, Octavia A. Dobre, and Moe Z. Win. "Doppler Spread Estimation in MIMO Frequency-Selective Fading Channels." IEEE Transactions on Wireless Communications 17, no. 3 (March 2018): 1951–65. http://dx.doi.org/10.1109/twc.2017.2787539.

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20

Robertson, Patrick, and Stefan Kaiser. "Analysis of Doppler Spread Perturbations in OFDM(A) Systems." European Transactions on Telecommunications 11, no. 6 (November 2000): 585–92. http://dx.doi.org/10.1002/ett.4460110609.

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21

Eller, Anthony I., and Ellen M. Daley. "Effects of scattering‐induced frequency spread on Doppler performance." Journal of the Acoustical Society of America 98, no. 5 (November 1995): 2912. http://dx.doi.org/10.1121/1.414197.

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22

Hong Zhang and A. Abdi. "Cyclostationarity-based doppler spread estimation in mobile fading channels." IEEE Transactions on Communications 57, no. 4 (April 2009): 1061–67. http://dx.doi.org/10.1109/tcomm.2009.04.070255.

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23

Zhang, Wei, Huiyong Li, Guohao Sun, and Zishu He. "Enhanced Detection of Doppler-Spread Targets for FMCW Radar." IEEE Transactions on Aerospace and Electronic Systems 55, no. 4 (August 2019): 2066–78. http://dx.doi.org/10.1109/taes.2019.2925433.

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24

Reddi, C. R., M. S. S. R. K. N. Sarma, and K. Niranjan. "HF Doppler radar observations of low-latitude spread F." Radio Science 44, no. 3 (May 9, 2009): n/a. http://dx.doi.org/10.1029/2007rs003777.

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25

Yang, Guang, Feng Zhou, Gang Qiao, Yunjiang Zhao, Yufei Liu, Yinheng Lu, and Yuanan He. "Optimized Doppler Estimation and Symbol Synchronization for Mobile M-ary Spread Spectrum Underwater Acoustic Communication." Journal of Marine Science and Engineering 9, no. 9 (September 13, 2021): 1001. http://dx.doi.org/10.3390/jmse9091001.

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In mobile underwater acoustic (UWA) communications, the Doppler effect causes severe signal distortion, which leads to carrier frequency shift and compresses/broadens the signal length. This situation has a more severe impact on communication performance in the case of low signal-to-noise ratio and variable-speed movement. This paper proposes a non-data-aided Doppler estimation method for M-ary spread spectrum UWA communication systems in mobile scenarios. The receiver uses the spread spectrum codes dedicated to transmitting signals with different frequency offsets as local reference signals. Correlation operations are performed symbol by symbol with the received signal. The decoding and Doppler estimation of the present symbol are achieved by searching the correlation maximum in the code domain and frequency domain. The length of the current symbol is corrected for the next symbol synchronization using the estimated Doppler coefficient. To optimize the process of Doppler estimation and symbol synchronization, a heuristic search method is used. By adjusting the Doppler factor search step size, setting the threshold value, and using the Doppler factor estimation of the previous symbol, the search range can be significantly reduced and the computational complexity decreased. The Fisher-Yates shuffle algorithm is used to traverse the search range to ensure reliability of the results. Simulation results show that enlarging the frequency-domain search step size in some degree does not affect the decoding accuracy. On 15 May 2021, a shallow-water mobile UWA spread spectrum communication experiment was conducted in Weihai, China. The horizontal distance between the transmitter and the receiver is 3.7–4.0 km, and the communication rate is 41.96 bits per second. The transmitting ship moves at a speed of 0–3 m/s, and the bit error rate (BER) is lower than 1e−3, which is better than that of the sliding correlation despreading method with average Doppler compensation.

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26

Yoon, Eunchul, Soonbum Kwon, Unil Yun, and Sun-Yong Kim. "Doppler Spread Estimation Based on Machine Learning for an OFDM System." Wireless Communications and Mobile Computing 2021 (September 21, 2021): 1–15. http://dx.doi.org/10.1155/2021/5586029.

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In this paper, we propose a Doppler spread estimation approach based on machine learning for an OFDM system. We present a carefully designed neural network architecture to achieve good performance in a mixed-channel scenario in which channel characteristic variables such as Rician K factor, azimuth angle of arrival (AOA) width, mean direction of azimuth AOA, and channel estimation errors are randomly generated. When preprocessing the channel state information (CSI) collected under the mixed-channel scenario, we propose averaged power spectral density (PSD) sequence as high-quality training data in machine learning for Doppler spread estimation. We detail intermediate mathematical derivatives of the machine learning process, making it easy to graft the derived results into other wireless communication technologies. Through simulation, we show that the machine learning approach using the averaged PSD sequence as training data outperforms the other machine learning approach using the channel frequency response (CFR) sequence as training data and two other existing Doppler estimation approaches.

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27

Wu, Xing Cun, Ping Gong, Hai Jun Song, and Hui Zhi Zou. "An FFT-Based Approach for Carrier Frequency Domain Acquisition in Spread Spectrum TT&C System." Applied Mechanics and Materials 135-136 (October 2011): 211–16. http://dx.doi.org/10.4028/www.scientific.net/amm.135-136.211.

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Acquisition time of precision ranging code is long under the conditions of large Doppler shift, the carrier frequency domain FFT-based fast acquisition theory was analyzed, and the method of carrier Doppler compensation estimates to complete the PN code Doppler compensation was directly used in spread spectrum ranging signal acquisition. Comparing with the traditional parallel acquisition approach, the Doppler frequency estimation accuracy and acquisition speed is greatly improved, the acquisition time is shorter than long code segment with the traditional parallel acquisition method. Comparing with the method of short code supporting for long code, the channel energy is saved.

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28

Liu, Bei Jia, Xiao Wang, Xue Zhi Tan, and Yang Yu. "An Adaptive Channel Estimation Based on Polynomial Fitting for LTE Uplink in High Doppler Spread Scenario." Advanced Materials Research 756-759 (September 2013): 3522–26. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.3522.

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Channel estimation plays a crucial role in improving the overall system performance in long term evolution (LTE) systems. However, it is demonstrated that conventional channel estimation algorithms have poor performance in the presence of a large Doppler frequency shift. To mitigate the adverse effect of Doppler frequency shift on transmission signals, an adaptive anti-Doppler shift method based on polynomial fitting for LTE uplink is proposed in this paper. Furthermore, an adaptive strategy is exploited to improve estimation accuracy and reduce estimation mean square error (MSE), achieving better system performance. Simulations results validate the effectiveness of anti-Doppler algorithm.

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29

Li, Jie, Fangjiong Chen, Songzuo Liu, Hua Yu, and Fei Ji. "Estimation of Overspread Underwater Acoustic Channel Based on Low-Rank Matrix Recovery." Sensors 19, no. 22 (November 15, 2019): 4976. http://dx.doi.org/10.3390/s19224976.

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In this paper, the estimation of overspread, i.e., doubly spread underwater acoustic (UWA) channels of strong dispersion is considered. We show that although the UWA channel dispersion causes the degeneration of channel sparsity, it leads to a low-rank structure especially when the channel delay-Doppler-spread function is separable in delay and Doppler domain. Therefore, we introduce the low-rank criterion to estimate the UWA channels, which can help to improve the estimation performance in the case of strong dispersion. The estimator is based on the discrete delay-Doppler-spread function representation of channel, and is formulated as a low-rank matrix recovery problem which can be solved by the singular value projection technique. Simulation examples are carried out to demonstrate the effectiveness of the proposed low-rank-based channel estimator.

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30

Marsden, R. F., and R. G. Ingram. "Correcting for Beam Spread in Acoustic Doppler Current Profiler Measurements." Journal of Atmospheric and Oceanic Technology 21, no. 9 (September 2004): 1491–98. http://dx.doi.org/10.1175/1520-0426(2004)021<1491:cfbsia>2.0.co;2.

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31

Po-Ying Chen and Hsueh-Jyh Li. "An iterative algorithm for Doppler spread estimation in LOS environments." IEEE Transactions on Wireless Communications 5, no. 6 (June 2006): 1223–28. http://dx.doi.org/10.1109/twc.2006.1638638.

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32

Ghogho, M., A. Swami, and T. S. Durrani. "Frequency estimation in the presence of Doppler spread: performance analysis." IEEE Transactions on Signal Processing 49, no. 4 (April 2001): 777–89. http://dx.doi.org/10.1109/78.912922.

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33

Hagfors, T., and E. Tereshchenko. "Two-dimensional chirp mapping of delay and Doppler spread targets." Radio Science 26, no. 5 (September 1991): 1199–203. http://dx.doi.org/10.1029/91rs01414.

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34

Ramakrishnan, D., and J. Krolik. "Adaptive Radar Detection in Doubly Nonstationary Autoregressive Doppler Spread Clutter." IEEE Transactions on Aerospace and Electronic Systems 45, no. 2 (April 2009): 484–501. http://dx.doi.org/10.1109/taes.2009.5089536.

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35

Roy, Sébastien, Huu Tuê Huynh, and Paul Fortier. "Compound Doppler Spread Effects of Subscriber Motion and Scatterer Motion." AEU - International Journal of Electronics and Communications 57, no. 4 (January 2003): 237–46. http://dx.doi.org/10.1078/1434-8411-54100166.

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36

Yuh-Ren Tsai and Kai-Jie Yang. "Approximate ML Doppler Spread Estimation Over Flat Rayleigh Fading Channels." IEEE Signal Processing Letters 16, no. 11 (November 2009): 1007–10. http://dx.doi.org/10.1109/lsp.2009.2028458.

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37

Luo, T., Z. Wen, J. Li, and H. H. Chen. "Saturation throughput analysis of WAVE networks in Doppler spread scenarios." IET Communications 4, no. 7 (2010): 817. http://dx.doi.org/10.1049/iet-com.2009.0071.

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38

Castrellon, Mario, David Muñoz, Cesar Vargas, Claudio Lopez, and David Covarrubias. "Doppler spread for Gaussian scatter density environments employing smart antennas." AEU - International Journal of Electronics and Communications 61, no. 9 (October 2007): 631–36. http://dx.doi.org/10.1016/j.aeue.2006.12.010.

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39

Zhao, Feng, and Xihong Sun. "Method of Doppler Frequency Spread Estimation for High-Mobility OFDM Systems." International Journal of Distributed Sensor Networks 2015 (2015): 1–6. http://dx.doi.org/10.1155/2015/461017.

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A method of Doppler frequency spread (DFS) estimation algorithm is discussed which is suitable for high-mobility Orthogonal Frequency Division Multiplexing (OFDM) systems. DFS is a main factor which may mitigate the performance of system. The proposed method is based on autocorrelation function algorithm of received signal which utilizes cyclic prefix (CP) to estimate Doppler spread. The estimation algorithm uses least square (LS) method between the autocorrelation function of received signal and the zero-order Bessel function which is approximated by the expansion of power series. Then the estimation bias is analyzed and using polynomial fitting method can effectively correct estimation error at different DFS, respectively. Compared with the previously proposed method, the estimation performance of DFS in the proposed method has better performance. Simulation results show that when sufficient elements are used, the proposed scheme can effectively estimate DFS and can be applied into high-mobility OFDM systems.

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40

Becker, Erich, and Charles McLandress. "Consistent Scale Interaction of Gravity Waves in the Doppler Spread Parameterization." Journal of the Atmospheric Sciences 66, no. 5 (May 1, 2009): 1434–49. http://dx.doi.org/10.1175/2008jas2810.1.

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Abstract The standard Doppler spread parameterization of gravity waves, which was proposed by C.-O. Hines and has been applied in a number of middle atmosphere general circulation models, is extended by the inclusion of all effects associated with vertical diffusion. Here the Wentzel–Kramers–Brillouin (WKB) approximation is employed to calculate the vertical propagation of the wave spectrum in the presence of wave damping. According to the scale interaction between quasi-stationary turbulence and the larger nonturbulent flow, all vertical diffusion applied to the resolved flow should damp the parameterized gravity waves as well. Hence, the unobliterated part of the gravity wave spectrum is subject to diffusive damping by the following processes: 1) the background diffusion derived from the model’s boundary layer vertical diffusion scheme, which may extend into the middle atmosphere, 2) molecular diffusion, and 3) the turbulent diffusion resulting from the truncation of the gravity wave spectrum by Doppler spreading, which thus feeds back on the unobliterated gravity waves. The extended Doppler spread parameterization is examined using perpetual July simulations performed with a mechanistic general circulation model. For reasonable parameter settings, the convergence of the potential temperature flux cannot be neglected in the sensible heat budget, especially in the thermosphere. Less gravity wave flux enters the model thermosphere when vertical diffusion is included, thus avoiding the need for artificial means to control the parameterized gravity waves in the upper atmosphere. The zonal wind in the tropical middle and upper atmosphere is found to be especially sensitive to gravity wave damping by diffusion.

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41

Shome, Subhankar, Rabindra Nath Bera, Samarendra Nath Sur, and Rabi Adhikary. "Moving Target Detection and Doppler Extraction Using Digital Spread Spectrum Radar." International Journal of Intelligent Systems and Applications 6, no. 10 (September 8, 2014): 47–54. http://dx.doi.org/10.5815/ijisa.2014.10.07.

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42

Ziemer, R. E., and T. B. Welch. "Equal-gain combining of multichannel DPSK in Doppler-spread Ricean fading." IEEE Transactions on Vehicular Technology 49, no. 5 (2000): 1846–55. http://dx.doi.org/10.1109/25.892588.

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43

Wang, Jian, Camillo Gentile, Peter B. Papazian, Jae-Kark Choi, and Jelena Senic. "Quasi-Deterministic Model for Doppler Spread in Millimeter-Wave Communication Systems." IEEE Antennas and Wireless Propagation Letters 16 (2017): 2195–98. http://dx.doi.org/10.1109/lawp.2017.2705578.

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44

Eggen, T. H., A. B. Baggeroer, and J. C. Preisig. "Communication over Doppler spread channels. Part I: Channel and receiver presentation." IEEE Journal of Oceanic Engineering 25, no. 1 (January 2000): 62–71. http://dx.doi.org/10.1109/48.820737.

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45

Eggen, T. H., J. C. Preisig, and A. B. Baggeroer. "Communication over Doppler spread channels. II. Receiver characterization and practical results." IEEE Journal of Oceanic Engineering 26, no. 4 (2001): 612–21. http://dx.doi.org/10.1109/48.972101.

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46

Jueping Cai, Wentao Song, and Zan Li. "Doppler spread estimation for mobile OFDM systems in Rayleigh fading channels." IEEE Transactions on Consumer Electronics 49, no. 4 (November 2003): 973–77. http://dx.doi.org/10.1109/tce.2003.1261183.

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47

Arnaut, Luk R. "Pulse Jitter, Delay Spread, and Doppler Shift in Mode-Stirred Reverberation." IEEE Transactions on Electromagnetic Compatibility 58, no. 6 (December 2016): 1717–27. http://dx.doi.org/10.1109/temc.2016.2585546.

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48

Mar, Jeich, and Hung-Ta Lin. "Doppler estimator operating with matched filter for vehicular spread spectrum radar." Electronics Letters 38, no. 16 (2002): 911. http://dx.doi.org/10.1049/el:20020588.

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49

Vierinen, J., M. S. Lehtinen, and I. I. Virtanen. "Amplitude domain analysis of strong range and Doppler spread radar echos." Annales Geophysicae 26, no. 8 (August 6, 2008): 2419–26. http://dx.doi.org/10.5194/angeo-26-2419-2008.

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Abstract. We present a novel method for analyzing range and Doppler spread targets in the amplitude domain using linear statistical inversion. The result of the analysis is an estimate of the range dependent amplitude behaviour of the target backscatter during the time that the transmission passes the target. A meteor head echo and strong backscatter from artificially heated regions of the ionosphere are used to demonstrate this novel analysis method. Plans to apply amplitude-domain radar target estimation methods to more complicated noisy underdetermined targets are also briefly discussed.

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50

Hysell, D. L., and J. L. Chau. "Interpreting the Doppler spectrum of coherent scatter from topside equatorial spread." Journal of Atmospheric and Solar-Terrestrial Physics 66, no. 17 (November 2004): 1549–57. http://dx.doi.org/10.1016/j.jastp.2004.07.003.

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Journal articles on the topic 'Doppler spread'

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