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MINISTRY OF EDUCATION AND TRAINING HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY DO VIET HA MÔ HÌNH ĐẶC TÍNH KÊNH TRUYỀN CHO THÔNG TIN THỦY ÂM VÙNG NƯỚC NÔNG CHANNEL MODELING FOR SHALLOW UNDERWATER ACOUSTIC COMMUNICATIONS DOCTORAL THESIS OF TELECOMMUNICATIONS ENGINEERING HA NOI - 2017 MINISTRY OF EDUCATION AND TRAINING HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY DO VIET HA MÔ HÌNH ĐẶC TÍNH KÊNH TRUYỀN CHO THÔNG TIN THỦY ÂM VÙNG NƯỚC NÔNG CHANNEL MODELING FOR SHALLOW UNDERWATER ACOUSTIC COMMUNICATIONS Specialization: Telecommunications Engineering Code No: 62520208 DOCTORAL THESIS OF TELECOMMUNICATIONS ENGINEERING SUPERVISORS: Assoc.Prof Van Duc Nguyen Dr Van Tien Pham Hanoi - 2017 DECLARATION OF AUTHORSHIP I hereby declare that this dissertation titled, "Channel Modeling for Shallow Underwater Acoustic Communications”, and the work presented in it are entirely my own original work under the guidance of my supervisors I confirm that: • This work was done wholly or mainly while in candidature for a PhD research degree at Hanoi University of Science and Technology • Where any part of this dissertation has previously been submitted for a degree of any other qualification at Hanoi University of Science and Technology or any other institution, this has been clearly stated • Where I have consult the published work or others, this is always given With the exception of such quotations, this dissertation is entirely my own work • I have acknowledged all main source of help • Where the thesis is based on work done by myself jointly with others, I have made exactly what was done by others and what I have contributed myself SUPERVISORS Hanoi, August 27, 2017 PhD STUDENT Assoc.Prof Van Duc Nguyen Dr Van Tien Pham Do Viet Ha ACKNOWLEDGEMENTS First and foremost, I would like to thank my advisor Associate Prof Dr Nguyen Van Duc for for providing an excellent atmosphere for doing research, for his valuable comments, constant support and motivation His guidance helped me in all the time of research and writing of this dissertation I could not have imagined having a better advisor and mentor for my PhD I would also like to thank Dr Pham Van Tien for their advice and feedback, also for many educational and inspiring discussions My sincere gratitude goes to the members in the Wireless Communication Lab, School of Electronics and Telecommunications, Hanoi University of Science and Technology, Hanoi, Vietnam Without their support and friendship it would have been difficult to complete my PhD studies I am also thankful to Dr Nguyen Tien Hoa for his invaluable instructions in presenting my dissertation I would also like to express my deepest gratitude to my parents, my husband, my son, and my daughter They were always supporting me and encouraging me with their best wishes, they were standing by me throughout my life Hanoi, August 27, 2017 PhD STUDENT Do Viet Ha Contents TABLE OF CONTENTS ABBREVIATIONS iv LIST OF FIGURES vi LIST OF TABLES ix INTRODUCTION Chapter DESIGN OF SHALLOW UWA CHANNEL SIMULATORS 15 1.1 Introduction 16 1.2 Overview of Simulation Models for UWA Channels 1.2.1 Rayleigh and Rice channels 1.2.2 Deterministic SOS Channel Models 1.2.3 Deterministic SOC Channel Models 19 19 20 21 1.3 The Geometry-based UWA Channel Simulator 21 1.3.1 Developing the Reference Model from the Geometrical Channel Model 22 1.3.2 The Simulation Model 27 1.3.3 The Estimated Parameters of the Simulation Model 27 1.3.4 Simulation Results 28 1.4 The Measurement-based UWA Channel Simulator 1.4.1 The Reference Model from the Measurement Data 1.4.2 The Simulation Model 1.4.3 Estimated Channel Parameters of the Simulation Model 1.4.4 Comparison of the Two Channel Simulators 28 29 32 33 34 1.5 The Proposed Approach for the Static UWA Channel 1.5.1 Descriptions 1.5.2 Results and Discussions 35 36 38 i ii 1.6 The Proposed Approach for the Case of Doppler Effects 1.6.1 The Measurement Data 1.6.2 The Conventional Measurement-based Simulators 1.6.3 The Proposed Channel Simulator 39 40 41 45 1.7 Conclusions 50 Chapter MODELING OF DOPPLER POWER SPECTRUM FOR SHALLOW UWA CHANNELS 53 2.1 Introduction 53 2.2 The Proposed Doppler Spectrum Model 2.2.1 The Doppler Effects in Shallow UWA Channels 2.2.2 The Proposed Doppler Model for UWA Channels 56 56 59 2.3 The Description of Doppler Spectrum Measurements 2.3.1 Experimental Setup 2.3.2 Measurement Scenarios 2.3.3 Reference Model from the Measurement Data 63 63 64 66 2.4 Parameter Optimizations of the Proposed Model 67 2.5 Measurement and Doppler Modeling Results 2.5.1 Scenario 2.5.2 Scenario 2.5.3 Scenario 68 69 71 75 2.6 Conclusions 77 Chapter UWA-OFDM SYSTEM PERFORMANCE ANALYSIS USING THE MEASUREMENT-BASED UWA CHANNEL MODEL 78 3.1 Introduction 79 3.2 ICI Analysis of UWA-OFDM Systems 3.2.1 SIR Calculation 3.2.2 Ambient Noise Power 3.2.3 SINR Calculation 81 82 83 84 3.3 Capacity Calculation 86 iii 3.4 Numerical Results 3.4.1 The SIR 3.4.2 The SINR 3.4.3 Channel Capacity 3.4.4 Transmit Power 87 88 89 90 92 3.5 Chapter Conclusions 96 CONCLUSIONS 99 APPENDIX 103 LIST OF PUBLICATIONS 105 ABBREVIATIONS ACF Autocorrelation Function AOA Angles of Arrival AOD Angles of Departure AWGN Additive White Gaussian Noise BPSK Binary Phase Shift Keying CIR Channel Impulse Response FCF Frequency Correlation Function ICI Inter-Channel Interference INLSA Iterative Nonlinear Least Square Approximation ISI Inter-Symbol Interference LNA Low Noise Amplifier LOS Line of Sight LPNM Lp-Norm Method MESS Method of Equally Spaced Scatterers MSE Mean Square Error OFDM Orthogonal Frequency Division Multiplexing PDF Probability Density Function PDP Power Delay Profile PN Pseudo-Noise PSD Power Spectra Density Rx Receiver SINR Signal to Interference plus Noise Ratio SIR Signal-to-Interference Ratio SNR Signal to Noise Ratio SOC Sum-of-Cisoids SOS Sum-of-Sinusoids TCF Time Correlation Function iv v T-FCF Time-Frequency Correlation Function TVCIR Time Variant Channel Impulse Response TVCTF Time-Variant Channel Transfer Function Tx Transmitter UWA Underwater Acoustic WLAN Wireless Local Area Network WSSUS Wide-Sense Stationary Uncorrelated Scattering List of Figures Multipath interference in UWA communication systems 1.1 The methodology behind the geometry-based channel modelling [17, 55] 17 1.2 The methodology behind the measurement-based channel modelling [31, 56] 18 1.3 The scheme of designing the geometry-based channel simulator [17, 55] 22 1.4 The geometrical model for shallow UWA channels with randomly distributed scatterers Si,n (•) on the surface (i = 1) and the bottom (i = 2) [55] 23 1.5 The comparison between the normalized FCF of the reference model and that obtained by the geometry-based simulator 29 1.6 1.7 Illustration of the measurement setup in Halong bay 30 ˆ t)|2 for the transmission distance of 150 m 31 The measured |h(τ, 1.8 The measured and normalized PDP ρ(τ ) obtained for the transmission distance of 150 m 1.9 32 The comparison of the normalized FCF obtained by the two simulators to that of the reference model 35 1.10 The flowchart of proposed approach to design the static UWA channel simulator 36 1.11 The comparison between the normalized FCF of the reference model and that obtained by the measurement-based, the geometry-based, and the proposed simulators 38 1.12 The normalized Doppler power spectrum 41 1.13 a) The reference T-FCF derived from the measurement results b) The T-FCF of the channel simulation model designed by the conventional simulator 43 1.14 The comparison between the normalized T-FCF of the reference model and that obtained by the conventional measurement-based simulator 44 1.15 The flowchart of the proposed approach for the case of moving Rx vi 46 100 water environment A closed-form expression of Doppler power spectrum model for underwater acoustic (UWA) channels was proposed The theoretical background of Doppler effects generated by the transmitter/receiver (Tx/Rx) movement, or by the motion of sea-surface was analyzed by using the geometry model for shallow UWA channels As a result, the Doppler power spectrum can be modeled as a summation of the Spike-shape and the Gaussian-shape The Spike-shape presents the Doppler component from the Tx/Rx movement, while the Gaussianshape presents the Doppler component from the sea-surface motion The proposed model is validated through curve fitting with the Doppler power spectrum measurement results of a real shallow UWA channel in Halong bay, Vietnam The optimal parameters of the proposed model are derived from the measurement results by applying an optimization algorithm called the Lp-norm method The curve fitting results show that our proposed model matches well with the measurements Therefore, the proposed Doppler model can accurately describe the Doppler effects for shallow UWA channels The proposed model can be used to design UWA channel simulators for the performance evaluation of UWA communication systems By using the measurement-based UWA channel model, the performance of UWA-OFDM systems under the influence of both the ICI and the noise effect was analyzed The UWA channel model was examined regarding the channel characteristics, ambient noise, and Doppler effect In contrast to other studies, which considered ocean noise as white noise, we calculated the SINR in the presence of both the ICI and the ambient noise as a function of the signal bandwidth and number of sub-carriers The system capacity of the UWA-OFDM system are then derived from the SINR results Moreover, the required transmit power for a given system capacity and transmission band was analyzed The transmit power should be chosen carefully in order to obtain the desired SNR by minimizing the ICI effect The optimized results of the number of sub-carriers, the 101 signal bandwidth, and the transmit power, provide practical guidelines for choosing proper transmission parameters for the considered UWA-OFDM system B Futures research directions This dissertation studied the approaches of designing shallow UWA channel simulators The statistical characterization of channel models and the performance analysis of the simulators were addressed For effective design of UWA channel simulators, a Doppler power spectrum model for UWA channels was proposed Furthermore, in this dissertation, channel modeling and system performance analysis are unified into one for more general visualization rather only demonstrate on one of them as most papers have done so far However, there is still unsolved problem, which will be described in the following • In this dissertation, the effective approach of designing UWA channel simulators was proposed For the case of static UWA channel (i.e there is no relative movement between the Tx and Rx), all channel parameters of the proposed simulator are exploited from the measurement data However, for the case of moving Tx/Rx, Doppler frequencies of propagation paths still need to be computed by the optimization method In the future work, we will apply the proposed Doppler model to obtain the Doppler frequencies without applying any optimization method • In the future work, we will apply the proposed Doppler model to evaluate the Doppler effect on the performance of UWA communication systems The inter-carrier interference (ICI) resulting from the Doppler effect in UWA-OFDM systems can be analyzed by using the proposed model Based on the analytical results, Doppler compensation algorithms can be proposed • In this dissertation, the UWA-OFDM system performance was analyzed by using the measurement-based UWA channel and the theoretical approximated ambient noise In the future work, we will 102 develop the noise model based on the actual measurement data and use it to analyze the system performance • The performance analysis of the MIMO UWA-OFDM system should be implemented APPENDIX Verification of the Relation between the Spike Doppler Frequency and the Rx Speed To compare the estimated Rx speed Vn,R from Eq 2.14 with the setting Rx speed VR , we launched a measurement in West Lake, a shallow water environment, in Hanoi, Vietnam on February 14, 2017 The water depth was about m while the Tx transducer and Rx hydrophone were secured at a depth of m The experiment configuration is set up as illustrated in Sect 2.3.1 The Doppler spectrum measurement data was collected for two different scenarios while keeping the consistent Rx speed of 0.5 m/s In the first scenario, the Rx, at a distance of 100 m, starts to move towards the fixed Tx Firstly, the Rx speed is increased, and when it reached the value of 0.5 m/s, we keep it unchanged for interval of 15 s Then, we collected the received signal during this interval The measurement result of Doppler spectrum is obtained by applying the concept of the spectrogram in Sect 2.3.3 Subsequently, the optimal parameters are estimated by using the proposed model in Eq 2.9 and the method of parameter optimization LPNM in Sect 2.4 The results of these parameters are A = −17.6 dB, fm = 0.6876 Hz, w = 6.4615 Hz, C = 202.8722, and fSpike = 4.1632 Hz Using the optimal value of fSpike = 4.1632 Hz and Eq 2.14, we can estimate the speed of Rx Vn,R = 0.5204 m/s, which matches well with the actual Rx speed VR = 0.5 m/s In a similar way, for the second scenario, the Rx moves away from the fixed Tx at a distance of 50 m We measured and modeled Doppler spectrum when the Rx speed is 0.5 m/s The optimal parameters of the proposed model A = −12.4, dB, fm = −0.9642 Hz, w = 5.7981 Hz, C = 240.0687, and fSpike = −4.3299 Hz are derived from the measurement results Consequently, the Rx speed Vn,R = 0.54124 m/s is computed from the optimal value of fSpike = −4.3299 Hz This speed matches well with the setting speed of Rx VR = 0.5 m/s 103 104 a) The Rx moves towards the fixed Tx -5 -10 Measured spectrum Reference model Proposed Model -15 -20 -25 -30 -35 -40 -20 -15 -10 -5 Doppler shift [Hz] 10 15 20 Normalized Doppler spectrum [dB] Normalized Doppler spectrum [dB] The comparison between the reference model and the proposed model for each scenario is shown in in Fig 3.12 It can be seen that the proposed model is in good agreement with the reference model (i.e the measurement data) b) The Rx moves away from the fixed Tx -5 -10 -15 -20 -25 -30 Measured spectrum Reference model Proposed Model -35 -40 -20 -15 -10 -5 10 15 20 Doppler shift [Hz] Figure 3.12: Results of Doppler spectrum measurement and modeling while the Rx moves with the consistent speed of VR = 0.5 m/s LIST OF PUBLICATIONS C1 Ha, D V.; N Van Duc, and M Patzold (2015), SINR analysis of OFDM systems using a geometry-based underwater acoustic channel model, in ”IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)”, pp 683-687 C2 D H Do; Q K Nguyen; D V Ha ; N Van Duc (2016), A time synchronization method for OFDM-based underwater acoustic communication systems, in ”2016 International Conference on Advanced Technologies for Communications (ATC)”, pp 131-134 J1 Ha, D V.; T V Chien; V D Nguyen (2016), Proposals of multipath timevariant channel and additive coloured noise modelling for underwater acoustic OFDM-based systems, International Journal of Wireless and Mobile Computing, Vol 11, No 4, pp 329-338 J2 Ha, D V; V D Nguyen (2016), Methods of designing shallow underwater acoustic channel simulators, Acoustics Australia, Vol 44, No 3, pp 439-448 J3 Ha, D V; V D Nguyen; Q K Nguyen (2017), Modeling of Doppler Power Spectrum for Underwater Acoustic Channels, Journal of Communications and Networks, Vol 19, No 3, pp 270-281 105 Bibliography [1] Cao, Bùi Văn ( 2012) Nghiên cứu ảnh hưởng yếu tố môi trường biển đến cự ly hoạt động thiết bị thủy âm Tạp chí Khoa học Công nghệ Hàng hải số 32.aaaaaaaaaaaa [2] Ha, D T and V D Nguyen (2013a) Analysis of underwater channel characteristics Part I: Background Journal of Science and Technology, Technical Universities, ISSN: 08683980 (96), 26–32 [3] Ha, D T and V D Nguyen (2013b) Analysis 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AND TRAINING HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY DO VIET HA MÔ HÌNH ĐẶC TÍNH KÊNH TRUYỀN CHO THÔNG TIN THỦY ÂM VÙNG NƯỚC NÔNG CHANNEL MODELING FOR SHALLOW UNDERWATER ACOUSTIC COMMUNICATIONS... invaluable instructions in presenting my dissertation I would also like to express my deepest gratitude to my parents, my husband, my son, and my daughter They were always supporting me and encouraging... These parameters should be chosen carefully in order to obtain the desired capacity and SINR with minimizing the ICI effect The results provide practical guidelines for choosing proper transmission
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