Rahul PPT

Rahul PPT

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  Impact of EnvironmentalConditions on Underwater Communications Rahul Goswami Advisor: Dr. Ali Abdi Helen and John C. Hartmann Department of Electrical & Computer Engineering July 30, 2015
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  Abstract Acoustic propagation canbe characterized by attenuation that increases with signal frequency, time-varying multipath propagation and low speed of sound. Underwater acoustic channels are considered to be one of the most difficult communication media in use today. Sound propagates through water at a speed of 1500 m/s and propagates along several paths. The effect of such multipath propagation is interference at the receiver end which hampers reception of the correct information. There also exists ambient and site-specific noise in underwater fading channels. The aim of this study is to focus on the analysis of the Bit Error Rate (BER) with varying Signal- to-noise ratio (SNR) for Frequency Shift Keying (FSK) modulated signals over various conditions in underwater acoustic channels. With a primary objective of reducing the BER, different sediments are introduced to the underwater acoustic channel.
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  Objectives The project dealswith the following factors:    Frequency Shift Keying (FSK) modulation of randomly generated signals.  Non-coherent detection of the transmitted signals at the receiver end.  Underwater acoustic channels  Analysis of multipath fading, absorption, scattering by the water-bed sediments  Comparing different water-bed conditions for better detection of signals
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  Underwater Acoustic Channel Speedof sound underwater Absorption Attenuation Noise Multipath Doppler effect Sound attenuation in sediment
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  Speed of SoundUnderwater Sound speed as a function of depth and ocean cross-section Speed of sound underwater(1500 m/s)> Speed of sound in air (340 m/s)
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  Absorption & Attenuation Pathloss = Absorption Loss + Spreading Loss The overall path loss is given by:
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  Doppler Effect Sediment typeK (spreading factor) Very fine silt 0.17 Fine sand 0.45 Medium sand 0.48 Coarse sand 0.53 Sound attenuation in sediments
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  Experimental Process
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  Transmitter/Receiver Working Principle BFSKModulation Non coherent Demodulation
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  Simulation Results Perfect detectionat high SNR (30 dB) Incorrect detection at low SNR (-5 dB) 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 -0.5 0 0.5 1 1.5 amplitude(volt) time(sec) transmitting information as digital signal 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 -20 0 20 time(sec) amplitude(volt) waveform for binary FSK modulation coresponding binary information 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 -50 0 50 time(sec) amplitude(volt) waveform after passing through channel 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 -0.5 0 0.5 1 1.5 amplitude(volt) time(sec) recived information as digital signal after binary FSK demodulation 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 -0.5 0 0.5 1 1.5 amplitude(volt) time(sec) transmitting information as digital signal 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 -20 0 20 time(sec) amplitude(volt) waveform for binary FSK modulation coresponding binary information 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 -50 0 50 time(sec) amplitude(volt) waveform after passing through channel 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 -0.5 0 0.5 1 1.5 amplitude(volt) time(sec) recived information as digital signal after binary FSK demodulation
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  Graphical Analysis -10 -50 5 10 15 20 25 30 10 -3 10 -2 10 -1 10 0 Theoretical BER vs SNR Curve for BFSK over Rayleigh Fading channel E b /N o (dB) BER -10 -5 0 5 10 15 20 25 30 10 -300 10 -200 10 -100 10 0 BER vs SNR Curve for BFSK over AWGN channel BER • BERAWGN < BERRayleigh • BER decreases for high SNR
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  Experimental Observations PLAIN WATER SNR(i ndB) BER - 0.3507 0.5028 0.1921 0.4868 0.208 0.4965 0.5053 0.2413 0.5523 0.0168 0.5655 0.0152 1.1123 0.0029 1.3421 0.0004 1.8143 0.00041 2.5 0.0003 PLAIN WATER SNR(in dB) BER -0.3507 0.5028 0.1921 0.4868 0.208 0.4965 0.5053 0.2413 0.5523 0.0168 0.5655 0.0152 1.1123 0.0029 1.3421 0.0004 1.8143 0.00041 2.5 0.0003 ROCK-BED SNR(in dB) BER -0.2829 0.5018 0.0262 0.4945 0.2081 0.4948 0.21 0.4528 0.2143 0.2253 0.2176 0.1698 0.221 0.0665 0.4186 0.0142 0.4295 0.0028 0.5134 0.0017 0.5567 0.0009 0.6601 0 0.6616 0.000166 ROCK-BED SNR(in dB) BER 0.7528 0.0003 0.7615 0.0003 0.762 0.000166 0.7827 0.000166 0.7916 0.000166 0.7926 0.0003 0.8078 0.000166 0.8134 0.000166 0.821 0.000166 0.9127 0.000166 0.9213 0 0.9304 0.000166 0.9921 0.000166 SAND-BED SNR(in dB) BER -0.1458 0.4858 -0.0141 0.488 0.0315 0.3213 0.0642 0.2143 0.0932 0.2202 0.1816 0.0664 0.2597 0.0247 0.1121 0.1013 0.3023 0.0011 0.3142 0.0009 SAND-BED SNR(in dB) BER 0.3219 0.0003 0.3803 0.0043 0.4119 0.0115 0.4213 0.00016 6 0.7135 0.00016 6 1.2137 0.00016 6 1.3121 0 1.5213 0 2.4316 0
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  -1 0 12 3 4 5 6 7 10 -4 10 -3 10 -2 10 -1 10 0 SNR(dB) BitErrorRate BER vs SNR plot for underwater communication scenarios Rock-bed Plain water Sand-bed B E R vs S NR plot for underwater com m unication scenarios Rock-bed P lain w ater S and-bed Data Transm ission R ate: 100 bits per second Num ber of bits per transm ission: 6000 Frequency used for FS K m odulation: 6.9 kH z (for 0) and 7 kH z(for 1) S am pling rate: 96000 sam ples per second Experimental Analysis
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  Conclusion -1 0 12 3 4 5 6 7 10 -4 10 -3 10 -2 10 -1 10 0 SNR(dB) BitErrorRate BER vs SNR plot for underwater communication scenarios Rock-bed Plain water Sand-bed -1 0 1 2 3 4 5 6 7 10 -4 10 -3 10 -2 10 -1 10 0 S N R (dB ) BitErrorRate B E R vs S N R plot for underw ater com m unication scenarios R oc k-bed P lain w ater S and-bed D ata Transm iss ion R ate: 100 bits per second N um ber of bits per transm ission: 6000 F requenc y used for F S K m odulation: 6.9 kH z (for 0) and 7 kH z(for 1) S am pling rate: 96000 sam ples per sec ond  BERwater>BERrocks>BERsand Absorptionsand >Absorptionrocks Scatteringrocks>Scatteringsand
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  1] Milica Stojanovic(Northeaster University) & James Preisig (Woods Hole Oceanographic Institution): Underwater Acoustic CommunicationChannels: Propagation Models and Statistical Characterization, January 2009  [2] F. De Rango, F. Veltri, P. Fazio, D.E.I.S. Department, University of Calabria, Italy, 87036 : A Multipath fading Channel model for Underwater Shallow Acoustic Communications  [3] S. Anandalatchoumy & G. Sivaradje, Department of Electronics & Communication Engineering, Pondicherry Engineering College, Pondicherry, India : Comprehensive Study of Acoustic channel models for Underwater wireless communication networks, International journal on Cybernetics & Informatics (IJCI), Vol 4 , No 2, April 2015  [4] K. Saraswathi, Netravathi K. A., Dr. S. Ravishankar, Asst. Prof., RV College of Engineering, Bangalore : A Study on channel modeling of underwater acoustic communication, International Journal of Research in Computer andCommunication Technology, Vol 3, Issue 1, January- 2014  [5] Emerson de Sousa Costa, Eduardo Bauzer Medeiros & Joao Batista Carvalho Filardi : Underwater Acoustics modeling in finite depth shallow waters (Chp 22 of Modeling and Measurement Methods for Acoustic Waves and for Acoustic Microdevices)   [6] Dr. Aoife Moloney, School of Electronics & Communications, Dublin Institute of Technology: Non Coherent Detection (Lecture 26), April 2005  [7] Yoo Jung Kim : The Underwater Propagation of sound and its applications, Dartmouth Undergraduate Journal of Science, March 11, 2012 References