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Volume 152 Issue 5 May 2013
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Research Articles
Research on the Structure and Signal Transmission of Rotary Piezoelectric Dynamometer Zhenyuan Jia, Yongyan Shang, Zongjin Ren, Yifei Gao and Shengnan Gao........................... 1 Piezoelectric Sensor of Control Surface Hinge Moment Zongjin Ren, Shengnan Gao, Zhenyuan Jia,Yongyan Shang and Yifei Gao ............................ 11 Research Algorithm on Building Intelligent Transportation System based on RFID Technology Chuanqi Chen ............................................................................................................................ 18 Using Displacement Sensor to Determinate the Fracture Toughness of PMMA Bone Cement Yongzhi Xu, Youzhi Wang ......................................................................................................... 27 Study on the Applications of Fiber Bragg Grating and Wireless Network Technologies in Telemetry System of Atmospheric Precipitation Han Bing, Tan Dongjie, Li Liangliang, Liu Jianping ...................................................................................................................................... 33 An Energy-Efficient Adaptive Clustering Protocol for Wireless Sensor Network Lü Tao, Zhu Qing-Xin, Zhu Yu-Yu ............................................................................................ 41 A Case Study of Event Detection Performance Measure in WSNs Using Gini Index Luhutyit Peter Damuut, Dongbing Gu ........................................................................................ 51 Fault Diagnosis of Tool Wear Based on Weak Feature Extraction and GA-B-spline Network Weiqing Cao, Pan Fu, Genhou Xu............................................................................................. 60 The Research Abort Concept Restructuring of the Sensor Semantic Networks Guanwei ..................................................................................................................................... 68 Coordinating Reasoning Method for Semantic Sensor Networks Shi Yun Ping .............................................................................................................................. 76 A Novel Intelligent Transportation Control Supported by Wireless Sensor Network Zhe Qian, Jianqi Liu. .................................................................................................................. 84 Research on the Special Railway Intelligence Transportation Hierarchy and System Integration Methodology Meng-Jie Wang, Xi-Fu Wang, Wen-Ying Zhang, Xue Feng ...................................................... 89 Application of a Heterogeneous Wireless Framework for Radiation Monitoring in Nuclear Power Plant Gu Danying ................................................................................................................................ 98
Acoustic Emission Signal Analysis of Aluminum Alloy Fatigue Crack Wenxue Qian, Xiaowei Yin, Liyang Xie...................................................................................... 105 A New Ultra-lightweight Authentication Protocol for Low Cost RFID Tags Xin Wang, Qingxuan Jia, Xin Gao, Peng Chen, Bing Zhao....................................................... 110 AGC Design in Frequency Modulation System for Voice Communication via Underwater Acoustic Channel Cheng En, Chen Sheng-Li, Li Ye, Ke Fu-Yuan, Yuan Fei ......................................................... 116 Joint Source-Channel Coding for Underwater Image Transmission Chen Hua-Bin, Chen Wei-Ling, Li Ye, Cheng En, Yuan Fei...................................................... 122 Study on the Applications of Cross-Layer Information Fusion in Target Recognition Xing Liu, Shoushan Jiang .......................................................................................................... 129 A Simple Tree Detector Using Laser and Camera Fusion D. Wang, J. H. Liu, J. L. Wang, T. Li.......................................................................................... 137 Simulation and Analysis of T-Junction Microchannel Kainat Nabi, Rida Rafi, Muhammad Waseem Ashraf, Shahzadi Tayyaba, Zahoor Ahmad, Muhammad Imran, Faran Baig and Nitin Afzulpurkar................................................................ 146 Mass Flow Measurement of Fluids by a Helically Coiled Tube Tian Zhou, Zhiqiang Sun, Zhenying Dong, Saiwei Li, Jiemin Zhou........................................... 152 Comparative Creep Evaluation between the Use of ISO 376 and OIML R60 for Silicon Load Cell Characterization Ebtisam H. Hasan, Rolf Kumme, Günther Haucke and Sascha Mäuselein .............................. 158 Development of Noise Measurements. Part 3. Passive Method of Electronic Elements Quality Characterization Yuriy Bobalo, Zenoviy Kolodiy, Bohdan Stadnyk, Svyatoslav Yatsyshyn ................................. 164 Application of Mixed Programming in the Simulation of Lorenz Chaotic System's Dynamics Characteristics Based on Labview and Matlab Peng Zhou, Gang Xu, Liang Chen............................................................................................. 169 A Nanostructure with Dual-Band Plasmonic Resonance and Its Sensing Application Zongheng Yuan, Jing Huan , Xiaonan Li and Dasen Ren. ........................................................ 174 A Glucose Sensor Based on Glucose Oxidase Immobilized by Electrospinning Nanofibrous Polymer Membranes Modified with Carbon Nanotubes You Wang, Hui Xu, Zhengang Wang, Ruifen Hu, Zhiyuan Luo, Zhikang Xu, Guang Li......... 180 The Platform Architecture and Key Technology of Cloud Service that Support Wisdom City Management Liang Xiao .................................................................................................................................. 186
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AGC Design in Frequency Modulation System for Voice Communication via Underwater Acoustic Channel
1 CHENG En, 1 CHEN Sheng-Li, 2 Li Ye, 1 KE Fu-Yuan, 1* YUAN Fei
1 Key Laboratory of Underwater Acoustic Communication and Marine Information Technology of the Ministry of Education (Xiamen University), Xiamen, 361005, P. R. China
2 Key Laboratory of Computer Network of Shandong Province, Shandong Computer Science Center, Jinan, 250014, P. R. China * Tel.: 086-0592-2580143
E-mail: [email protected]
Received: 8 April 2013 /Accepted: 15 May 2013 /Published: 27 May 2013 Abstract: The FM modulation improves the anti-interference ability by sacrificing the bandwidth of the communication channel. In the underwater acoustic communication, as the bandwidth of the communication channel is very limited, the theory and experiment study show that if we are not deal with the original signal, the modulated signal cannot be transmitted through the underwater channel. In the research of underwater FM system, we find a better way to filtering and AGC. Adding filtering and AGC can not only control the bandwidth of the modulated signal but also improve the anti-noise ability integrally. Copyright © 2013 IFSA. Keywords: Underwater acoustic communication, FM modulation, Filtering and AGC. 1. Introduction
The common kind of modulation about underwater communication is SSB modulation, because compared with the FM modulation, the SSB modulation use a narrower bandwidth. [1-2] However, the anti-noise ability of the SSB modulation is not well while compare to the FM modulation. To balance the use of bandwidth anti-noise ability, base on the main frequency field of man voice, if we can add effectively filtering and amplitude control on the voice before FM modulation, we can control the bandwidth of the modulated signal and improve the anti-noise ability integrally. The filter is five orders Butterworth low-pass filter. This paper mention three AGC methods, the method of amplitude equalization can control the bandwidth of the modulated signal and improve the anti-noise ability integrally, but it will also bring major background noise. The method of amplitude
limiting can control the bandwidth of the modulated signal but can’t improve anti-noise ability obviously [3]. The third method is AGC, it’s the comprehensive of amplitude limiting and amplitude equalization, it use different gain on the signals with different range of amplitude, it can control the bandwidth of the modulated signal and improve the anti-noise ability without bring a major background noise. It is a suited AGC method for the underwater FM system.
2. The Modulation Theory of FM Frequency modulation means that the
instantaneous frequency changed proportionally by the modulation signal [4]. The FM modulation signal can be given as
))(2cos( 0 dttmKtfAS fFM
(1)
Article number P_1200
Sensors & Transducers, Vol. 152, Issue 5, May 2013, pp. 116-121
117
Here the fK is the sensitivity of frequency
modulation, its unit is ( V/Hzrad ), the maximum
frequency shift is
2
|)t(m|Kf
f
, and the index of
modulation is mf f
fB
, the bandwidth of modulated
signal is )mff(2B , the mf is the maximum frequency of the signal. Compared with the wireless channel on the land, the most special characteristic of underwater channel is its exceeding limited bandwidth. Though the formulation of bandwidth we can find that the FM modulation system which is used on the land can’t be used in underwater sound communication. If we can make the maximum frequency of the sound within a limited range, we can really reduce the occupy bandwidth of the modulated signal.
The bandwidth of the underwater transducer is fixed. One side, we hope to make the bandwidth of the modulated signal within the effective range of the underwater transducer. On the other side, we hope to use the bandwidth of the transducer effectively so that we can improve the anti-interference ability.
From )mff(2B and
2
|)t(m|Kf
f
, the
bandwidth B can be expressed as
mf
mf
f2|)t(m|k
)f2
|)t(m|k(2B
(2)
For the filtered sound signal, it’s maximum frequency fm is fixed, so the question can be convert to how to get the optimal answer of )t(mk f when
the B has a obvious upper limit.
2.1. Relationship Between Bandwidth and )t(mk f
From the formulation 2 we can know that
bandwidth B and )t(mk f has a linear relation, it
means that when the bandwidth has a maximum, the )t(mk f will have a maximum too, the index of
the frequency modulation will be high, certainly the anti-noise ability will be better. For the FM modulation system, the sensitivity of frequency modulation fk is usually fixed, so we can see that
|m(t)| have a linear relation with bandwidth B.
2.2. Relationship of fB , and )(tm when
fK is Fixed
Set the modulation signal as )1000sin())40cos(1()( ttAtm , the
waveform as Fig. 1 shows. For different A, we can get different frequency spectrum of (signal spectrum) and the envelope which is generated by the corresponding fm constant [5] as the Fig. 2 to Fig. 4 had shown.
Fig. 1. The modulation signal waveform (A=1).
(a). Single spectrum.
(b). Envelope of FM index.
Fig. 2. Single spectrum and FM index (A=1).
The horizontal ordinate of (a) of Figs. 2, 3, 4 means the times of the frequency resolution k , the corresponding frequency is fkf , the horizontal
ordinate of the signal spectrum in the behind is also the times of the frequency resolution k. Make a compare with Fig. 2,3,4: the bigger of the modulating signal’s amplitude the bigger range of the modulated signal’s amplitude, the bigger of the modulating signal’s frequency spectrum range, the bigger of the modulating signal’s amplitude dynamic range the bigger of the corresponding fm constant’s dynamic range. The mf f)1(2B shows that the
bandwidth may surpass the bandwidth of the underwater acoustic transducer, so the maximum of the amplitude need to be limited. To make sure the bandwidth of the modulated signal is in the range of the effective bandwidth and make the fm constant have a small dynamic range, we need to add an Auto Gain Control (AGC).
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118
(a). Single spectrum.
(b). Envelope of FM index.
Fig. 3. Single Spectrum and FM Index (A=5).
(a). Signal spectrum.
(b). Envelope of FM index.
Fig. 4. Signal spectrum and FM index.
3. Algorithm Theory and Simulation 3.1. Amplitude Equalization
The ideal of this algorithm is to modulate signal with full bandwidth, and adjust the amplitude of the input sound signal to a same maximum voltage under the stationary sensitivity of frequency modulation. The principle block diagram is like the Fig. 5.
The main job of the delay block is to deal with the part of real number and make sure the number of it’s sampling is the same as the part of imaginary [6], when we simulation on the PC we can leave out the
delay block. Presume there is a real signal x(t), the
analytic signal of it is ^
a )t(xj)t(x)t(x , and it is
a complex signal, the
)t(x is the Hilbert transform of
the x(t),
t
1*)t(x)t(x
(* means convolution) (3)
)(nVi
dV
)(iA )(nVo
Fig. 5. The block diagram of amplitude equalization.
The analytic can be express ast
1*)t(x)t(x
,
makes )(tA equal to )t(x)t(x2
2
, the A(t) is
the envelope of x(t). Presume that
)wncos()i(A)n(Vi , dV is the amplitude we need,
the output is
)wncos(V)wncos()i(A*)i(A/V
)n(V*)i(A/V)n(V
dd
ido
(4)
The output will be stabilized at dV , this is the
principle of equalization amplitude algorithm. The bandwidth of the transducer is kHz10 , presume
fK = 9000( V/Hzrad ), the corresponding dV is
3 V. In the simulation A must can make the amplitude of the original modulating signal bigger than 3. The result is show in Fig. 6.
Picture (a) (b) in the Fig. 6 means the waveform of the original signal and equalization amplitude, Fig. 6 (c) means the signal spectrum by the direct frequency modulation from the original signal, compare with the Fig. 6.(c) (d), we can find that equalization amplitude before modulating can reduce the occupy frequency of the modulated signal. Fig. 6(e) (f) means the FM index between equalization amplitude and not equalization amplitude. Make a compare between them we can find that the FM index is reduce after equalization. Base on the
mf f)1(2B we can see that use the equalization
amplitude we can control the occupy frequency of the modulated signal obviously, by this way we can make sure the bandwidth of the modulated signal is in the effective range of the underwater acoustic transducer. Use the voice signal to text, we find that the equalization amplitude will bring a major background noise, the MOS grade is in 3, so we need to consider limiting algorithm.
Sensors & Transducers, Vol. 152, Issue 5, May 2013, pp. 116-121
119
(a). Original input signal.
(b). Amplitude equalization.
(c). Signal spectrum of direct FM.
(d). Signal spectrum of amplitude equalization FM.
(e). FM index of direct FM
(f). FM index with amplitude equalization.
Fig. 6. The Effect of amplitude equalization.
3.2. Amplitude Limit The basic idea of the amplitude limiting algorithm:
to the modulating signal which have a big dynamic range, we only need to make sure the maximum bandwidth of the modulated signal is no large than the maximum bandwidth of the effective bandwidth [7] e functional block diagram is shown in Fig. 7.
Set an appropriate threshold (if use the hardware circuit we can use diode to realize), the simulation result is show in Fig. 8.
Compare with (a) (b) in the Fig. 8, we can find that use the limiting algorithm we can reduce the frequency range of the modulated signal, the compare with (e) (f) show that use the limiting algorithm the dynamic range of the FM index is still big and there is a small part than 1, the anti-noise ability will be low. The same to the analysis of Fig. 7, limiting can control the range of the modulated signal’s bandwidth to adjust to the bandwidth of the underwater acoustic transducer.
3.3. The Suitable AGC Algorithm
For equalization amplitude algorithm (Fig. 6), even though we can use the bandwidth well, but the test result show that as the part of unvoiced sound and the part of voiced sound will be amplify at a same value in sometime, it will bring a large noise, the quality of sound will decline quickly; for the amplitude limiting algorithm(Fig. 8), even though we can insure the bandwidth of the modulated signal is in the range of the effective bandwidth, but the dynamic range of the signal amplitude is still big, the frequency-modulation index of many small-signal is low, the corresponding ability will be low, the use ratio of the bandwidth is very low too.
Analysis the two drawbacks of the above algorithms and then design an AGC algorithm to overcome the drawbacks of those two algorithms as effectively as possible. The idea of this algorithm is:
equalization the 11 , xx to a number ±A , to the
amplitude in the range of 21 , xx use the
dynamic gain algorithm to amplify, and equalization all other number to ±B so that we can small the dynamic range. It’s functional block diagram is show in Fig. 9.
Fig. 7. Functional block diagram of amplitude algorithm.
Sensors & Transducers, Vol. 152, Issue 5, May 2013, pp. 116-121
120
(a). Original input signal.
(b). Amplitude limit output.
(c).Signal spectrum of direct FM.
(d).Signal spectrum with amplitude limit.
(e). FM index of direct FM.
(f). FM index with amplitude limit.
Fig. 8. The result of amplitude limit.
Fig. 9. Functional block diagram of AGC.
The corresponding relation between input, output and the amplify times is shown in Table 1. According to Table 1, set 2.0x1 , 5.1A , 8.2x2 , 3B .
Takes the dynamic gain function between [-x1, x1] as
bxxak 22 )( (5)
After amplification, the output is
xky (6)
According to the corresponding relation in above, we set a as 1.321., b as 1.07, we will get the simulation picture as in Fig. 10. Set different number we can get different result of AGC. Base on the way to analysis Fig. 6, compare with Fig. 10 and Fig. 8, Fig. 6, the ACG algorithm can meet the requirements: the AGC algorithm is design on the merit and demerit of the two algorithms, first this algorithm can insure the bandwidth of the modulated signal is in the range of the effective bandwidth, retain the acoustic of the sound well, it can also improve the FM Index and anti-noise ability. After test, the sound signal which is modulated by this modulation system can be demodulated well.
Table 1. The relation between input and output.
Input voltage magnification times Output
[- 1x ， 1x ] amplitude equalization ±A
[± 1x ,± 2x]
b)xx(*a 22 ±[A,B
]
Surpass 2x or
small- 2x amplitude equalization ±B
4. Conclusion There are many differences between underwater
communication and land communication, it mainly embodied in the complexity of the channel. When we study the underwater communication we always reference the technical of land communication base on the special character of underwater sound communication channel. This paper is base on the bandwidth of underwater sound communication channel and the limited of it to design a suitable AGC module in the FM system before the modulation, make the system suitable to underwater communication.
Sensors & Transducers, Vol. 152, Issue 5, May 2013, pp. 116-121
121
(a). Original input signal.
(b). AGC output.
(c). Signal spectrum of direct FM .
(d). Signal spectrum with AGC.
(e). FM index of direct FM.
(f). FM index with AGC.
Fig. 10. The result of AGC.
Acknowledgements
This work was supported by the Fundamental Research Funds for the Central Universities (2011121050, 2012121028), the National Natural Science Foundation of China (61001142, 61071150) and the Science Technology Project of Xiamen Government (3502z20123011).
References [1]. Mandar Chitre, Shiraz Shahabudeen, Milica
Stojanovic, Recent Advances in Underwater Acoustic Communications & Networking, in Proceedings of the OCEANS, 2008, pp. 1-10.
[2]. Gao Chun-Xian, Research of underwater speech communication of small submarine, Xiamen University, China, 2007.
[3]. Hyun-Shin Park, A Study on AGC scheme based on real time frequency characteristics, in Proceedings of the 43rd International Universities Power Engineering Conference (UPEC’2008), 2008, pp. 1-5.
[4]. Li Dao-Hu, Jia Xin-Cheng, The design and implementation of audio AGC, Journal of Henan Mechanical and Electrical Engineering College, Vol. 17, No. 4, 2009.
[5]. Tian Zhi-Sheng, A kind of Accurately Automatic Gain Control Circuit Base on Phase Lock loop, Observation and Control Technology, 2005.
[6]. Tao Yi, The research of anti-multipath modulation system in shallow sea communication channel, Xiamen University, China, 2008.
[7]. Mrutyunjaya Panda, Sarat Kumar Patra, Performance Measures of Ultra-Wideband Communication System, Sensors & Transducers, Vol. 124, Issue 1, January 2011, pp. 120-126.
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