摘要
人体通信是一种依托人体作为信号传输通道的新型近场通信方式,其作为实现普适计算的关键技术之一,因低功耗、结构简单和安全性好的优势将在众多领域中得到广泛应用。而表面波导人体通信凭借其在高速通信方面的优势,迅速成为了人体通信研究领域中的热点。但是当前的表面波导人体通信研究存在两个问题：首先是研究中对人体的建模并不精确,因而人体通信信号内在的传输机制尚不明确。同时研究中通常使用基于经验的人工参数调节方法来对通信装置进行优化,未将建模研究的成果应用于优化问题中。以上问题限制了人体通信系统性能的提升。为了解决这些的问题,本文利用电磁场正问题和逆问题的分析方法,从理论与应用两方面对表面波导人体通信建模问题进行了深入的研究,主要包括以下四个方面：
1)表面波导人体通信电磁场求解方法分析(建模理论研究)
为了有效分析表面波导人体通信的建模问题,本文首先建立了一套系统的人体通信信号传输机制的求解方法。其中圆柱坐标系下的分层介质表面波导理论被选择为本文中的电磁场解析求解方法,而四面体棱边有限元法和基于Helmholtz方程弱形式的Galerkin加权余量法被选择为本文中的电磁场数值求解方法。这些求解方法构成了对人体通信建模问题进行研究的理论基础和分析手段,这也是在人体通信研究领域对电磁场求解方法首次系统性地总结。
2)表面波导人体通信模型研究(建模理论研究)
为了解决现有人体通信理论模型存在的建模不精确和通信机理不明确的问题,本文根据人体的实际情况,使用电磁场的解析求解方法提出了一种基于分层介质圆柱表面波导理论新型的人体通信理论模型。同时,与理论模型对应的人体数值模型的计算结果被用来佐证理论模型计算结果的正确性。通过计算结果可知,本文提出的新型人体通信理论模型无论从预测变化趋势方面还是计算精度方面均明显优于现有理论模型。该模型是目前表面波导人体通信研究领域最为精确的理论模型,能够完整的刻画电磁波在人体表面的传输机制,可为优化表面波导人体人体通信信号分布和提高系统性能提供理论依据。
3)人体通信模型简化问题研究(建模理论研究)
人体通信装置的逆优化问题需要大规模的人体模型计算,而前一部分提出的人体通信理论模型和数值模型的计算复杂度较大,这成为了将模型研究的结论应用于人体通信装置优化问题的瓶颈之一。为了解决这一问题,本文对人体通信模型的简化问题进行了详细的研究,提出了一种简化人体通信数值模型。相比于标准的表面波导人体通信数值模型,该简化人体数值模型可在保持88%的计算精度的前提下将计算时间减少2/3,非常适合用于对人体通信信号的传输特性进行快速估计。模型简化研究的结论将被应用于对人体通信信号发射器的优化中,使得计算时间从原来的62.5天,减少到20.8天,大大提高了计算效率。
4)人体通信发射器设计与逆优化研究(建模应用研究)
现有的表面波导人体通信信号发射器一般是通过基于经验的人工参数调整方法来实现性能优化,因而存在集成性差和信号强度低、发射效率差两方面的缺陷。为了解决以上问题,本文首次将电磁场逆优化问题和人体数值模型引入人体通信装置设计与优化研究中,首先提出了一种基于印制电路板工艺的集成式人体通信信号发射器,然后使用电磁场逆优化方法对前文中提出的集成式信号发射器的信号强度和信号发射效率两方面的性能指标进行了优化。经过优化,集成式信号发射器在有效通信距离内的信号幅值是现有发射器的7.4倍以上,而其信号发射效率约是现有发射器的3.3倍。电磁场逆优化方法大大提高人体通信系统的整体性能,也将促进人体通信硬件和装置研究领域的发展。
Human Body Communication (HBC) is an emerging communication technology that uses human body as transmission channel. As an inevitable part of Pervasive Computing technology, HBC will be used widely in many application fields. In high speed communication application, surface waveguide HBC have extremely high performance and is becoming hot spot rapidly in relative research domains. But in the domain of surface waveguide research, there are also fundamental flaws like imprecise theoretical model and unclear transmission mechanism of signal. Also the achievements of HBC modeling research have not been used in the design and optimization of HBC equipment. To solve such problems, we take in-depth study on modeling theory and modeling application of HBC by direct and inverse analysis of electromagnetic problem.
1) Analysis System of Surface Waveguide HBC
To analyze the modeling of Surface Waveguide HBC effectively, we propose an analysis system based on analytical method and numerical method of electromagnetic fields. The theory of waveguide on stratified media is chosen as analytical method, and the edge-based FEM and Galerkin weighted residual method are used as numerical method. The analysis system is the theory foundation and analysis method of this paper.
2) Model of Surface Waveguide HBC
To solve the problem of imprecise theoretical model and unclear signal transmission mechanism in existing Surface Waveguide HBC research, a theoretical model based on stratified media cylinder is presented. A numerical model analyzed by Finite Element Method (FEM) is used for comparison and validating the theoretical model. Results of theoretical and numerical models shows that the new theoretical model proposed in this paper is superior to existing theoretical models in both calculation accuracy and prediction of trend, and is able to characterize accurate propagation mechanism of HBC signal. The propagation mechanism derived from the theoretical model is useful to provide design information for the transmitter and the modeling of the propagation channel in HBC.
3) Research on the Simplification of HBC Model
In the optimization of HBC equipment, theoretical and numerical model proposed in last part cost too much time and calculation resource. To solve this problem, we take a in-depth study in the calculation efficiency and simplification of HBC model, and propose a simplified numerical model of HBC. The calculation time of the simplified numerical model is just1/3of the complete numerical model, which keeps88%accuracy. The simplified numerical is very useful for fast evaluation of transmission mechanism of HBC signal and will be used for optimization of signal transmitter.
4) Design and Inverse Optimization of Signal Transmitter
The existing signal transmitter of HBC is badly in integration of transmitter structure and efficiency and intensity of HBC signal. In prior studies, researchers often used direct analysis method of electromagnetic field, which did not achieve a good result. To solve those problems above, we introduce the inverse analysis into research of Surface Waveguide HBC. A new structure of signal transmitter is proposed to enhance the integration of transmitter, and the inverse optimization method based on NSGA-II algorithm is used to optimize the new structure of transmitter for efficiency and intensity. After optimization, the intensity and efficiency of new transmitter is much better than the existing transmitter.
引文
[1]Weiser M, Brown J S. The coming age of calm technology[M]//Beyond calculation. Springer New York,1997:75-85.
[2]Satyanarayanan M. Pervasive computing:Vision and challenges[J]. Personal Communications, IEEE,2001,8(4):10-17.
[3]Saha D, Mukherjee A. Pervasive computing:a paradigm for the 21st century[J]. Computer, 2003,36(3):25-31.
[4]吴朝晖,潘纲.普适计算[D].中国计算机学会文集,清华大学出版社.北京,2006.
[5]IEEE 802.15:https://mentor.ieee.org/802.15/documents
[6]Zimmerman T G. Personal area networks (PAN):near-field intra-body communication[D]. Massachusetts Institute of Technology,1995.
[7]Zimmerman T G. Personal area networks:near-field intrabody communication[J]. IBM systems Journal,1996,35(3.4):609-617.
[8]Fujii K, Ito K, Tajima S. A study on the receiving signal level in relation with the location of electrodes for wearable devices using human body as a transmission channel[C]//Antennas and Propagation Society International Symposium,2003. IEEE. IEEE,2003,3:1071-1074.
[9]Fujii K, Ito K. Evaluation of the received signal level in relation to the size and carrier frequencies of the wearable device using human body as a transmission channel[C]//Antennas and Propagation Society International Symposium,2004. IEEE. IEEE,2004,1:105-108.
[10]Fujii K, Takahashi M, Ito K. Study on the electromagnetic field distributions of realistic Japanese adult male and female models with a wearable device using the human body as a transmission channel[C]//Antennas and Propagation Society International Symposium 2006, IEEE. IEEE,2006:2121-2124.
[11]Ito K, Fujii K. Development and investigation of the transmission mechanism of the wearable devices using the human body as a transmission channel[C]//Antenna Technology Small Antennas and Novel Metamaterials,2006 IEEE International Workshop on. IEEE,2006:140-143.
[12]Hachisuka K, Nakata A, Takeda T, et al. Development and performance analysis of an intra-body communication device[C]//TRANSDUCERS, Solid-State Sensors, Actuators and Microsystems,12th International Conference on,2003. IEEE,2003,2:1722-1725.
[13]Hachisuka K, Terauchi Y, Kishi Y, et al. Simplified circuit modeling and fabrication of intrabody communication devices[J]. Sensors and actuators A:physical,2006,130: 322-330.
[14]Shinagawa M, Fukumoto M, Ochiai K, et al. A near-field-sensing transceiver for intra-body communication based on the electro-optic effect[C]//Instrumentation and Measurement Technology Conference,2003. IMTC'03. Proceedings of the 20th IEEE. IEEE,2003,1:296-301.
[15]Shinagawa M, Fukumoto M, Ochiai K, et al. A near-field-sensing transceiver for intrabody communication based on the electrooptic effect[J]. Instrumentation and Measurement, IEEE Transactions on,2004,53(6):1533-1538.
[16]Hwang J H, Sung J B, Hyoung C H, et al. Analysis of signal interference in human body communication using human body as transmission medium[C]//Antennas and Propagation Society International Symposium 2006, IEEE. IEEE,2006:495-498.
[17]Hwang J H, Hyoung C H, Sung J B, et al. EM Simulation and Analysis on the Ground Electrode of Human Body Communication[C]//Microwave Conference,2006.36th European. IEEE,2006:1122-1123.
[18]Hwang J H, Myoung H J, Kang T W, et al. Reverse effect of ground electrode on the signal loss of human body communication[C]//Antennas and Propagation Sooiety International Symposium,2008. AP-S 2008. IEEE. IEEE,2008:1-4.
[19]Choi S, Song S J, Sohn K, et al. A 24.2-μW Dual-Mode Human Body Communication Controller for Body Sensor Network[C]//Solid-State Circuits Conference,2006. ESSCIRC 2006. Proceedings of the 32nd European. IEEE,2006:227-230.
[20]Choi S, Song S J, Sohn K, et al. A low-power star-topology body area network controller for periodic data monitoring around and inside the human body[C]//Wearable Computers, 2006 10th IEEE International Symposium on. IEEE,2006:139-140.
[21]Song S J, Cho N, Kim S, et al. A 2Mb/s wideband pulse transceiver with direct-coupled interface for human body communications[C]//Solid-State Circuits Conference,2006. ISSCC 2006. Digest of Technical Papers. IEEE International. IEEE,2006:2278-2287.
[22]Song S J, Cho N, Kim S, et al. A 4.8-mW 10-Mb/s wideband signaling receiver analog front-end for human body communications[C]//Solid-State Circuits Conference,2006. ESSCIRC 2006. Proceedings of the 32nd European. IEEE,2006:488-491.
[23]Song S J, Lee S J, Cho N, et al. Low power wearable audio player using human body communications[C]//Wearable Computers,2006 10th IEEE International Symposium on. IEEE,2006:125-126.
[24]Song S J, Cho N, Kim S, et al. A 0.9 V 2.6 mW body-coupled scalable PHY transceiver for body sensor applications[C]//Solid-State Circuits Conference,2007. ISSCC 2007. Digest of Technical Papers. IEEE International. IEEE,2007:366-609.
[25]Cho N, Yan L, Bae J, et al. A 60 kb/s-10 Mb/s adaptive frequency hopping transceiver for interference-resilient body channel communication[J]. Solid-State Circuits, IEEE Journal of,2009,44(3):708-717.
[26]Cho N, Yoo J, Song S J, et al. The human body characteristics as a signal transmission medium for intrabody communication[J]. Microwave Theory and Techniques, IEEE Transactions on,2007,55(5):1080-1086.
[27]Wegmueller M, Felber N, Fichtner W, et al. Measurement system for the characterization of the human body as a communication channel at low frequency[C]//Engineering in Medicine and Biology Society,2005. IEEE-EMBS 2005.27th Annual International Conference of the. IEEE,2005:3502-3505.
[28]Wegmueller M S, Kuhn A, Froehlich J, et al. An attempt to model the human body as a communication channel[J]. Biomedical Engineering, IEEE Transactions on,2007,54(10): 1851-1857.
[29]Wegmueller M S, Oberle M, Felber N, et al. Galvanical coupling for data transmission through the human body[C]//Instrumentation and Measurement Technology Conference, 2006. IMTC 2006. Proceedings of the IEEE. IEEE,2006:1686-1689.
[30]Wang J, Nishikawa Y, Shibata T. Analysis of on-body transmission mechanism and characteristic based on an electromagnetic field approach[J]. Microwave Theory and Techniques, IEEE Transactions on,2009,57(10):2464-2470.
[31]Bae J, Cho H, Song K. et al. The signal transmission mechanism on the surface of human body'for body channel communication[J]. Microwave Theory and Techniques, IEEE Transactions on,2012,60(3):582-593.
[32]Bae J, Song K, Lee H, et al. A 0.24-nJ/b Wireless Body-Area-Network Transceiver With Scalable Double-FSK Modulation[J]. Solid-State Circuits, IEEE Journal of,2012,47(1): 310-322.
[33]Lee H, Lee K, Hong S, et al. A 5.5 mW IEEE-802.15.6 wireless body-area-network standard transceiver for multichannel electro-acupuncture application[C]//Solid-State Circuits Conference Digest of Technical Papers (ISSCC),2013 IEEE International. IEEE, 2013:452-453.
[34]Roh T, Hong S, Cho H, et al. A 259.6 μW nonlinear HRV-EEG chaos processor with body channel communication interface for mental health monitoring[C]//Solid-State Circuits Conference Digest of Technical Papers (ISSCC),2012 IEEE International. IEEE,2012: 294-296.
[35]Cho H, Bae J, Yoo H J. A 39 μW body channel communication wake-up receiver with injection-locking ring-oscillator for wireless body area network[C]//Circuits and Systems (ISCAS),2012 IEEE International Symposium on. IEEE,2012:2641-2644.
[36]Lee S, Roh T, Hong S, et al. A 2.1 μW real-time reconfigurable wearable BAN controller with dual linked list structure[C]//Circuits and Systems (ISCAS),2012 IEEE International Symposium on. IEEE,2012:1540-1543.
[37]LEE S, LONG Y A N, ROH T, et al. A 75 μW Real-Time Scalable Body Area Network Controller and a 25 μW ExG Sensor IC for Compact Sleep Monitoring Applications[J]. IEEE journal of solid-state circuits,2012,47(1):323-334.
[38]张俊.基于Turbo码的人体通信信道技术研究[D].浙江大学,2012.
[39]马力,沈海斌,赵宇.一种自适应双模式阻塞防碰撞方法中国发明专利ZL201110020482.32012
[40]倪光正.工程电磁场原理[M].高等教育出版社,2009.
[41]倪光正,杨仕友,钱秀英.工程电磁场数值计算[M].机械工业出版社,2004.
[42]梁灿彬,秦光戎,梁竹健.电磁学[M].高等教育出版社,1980.
[43]Kong J A.电磁波理论：英文版[M].高等教育出版社,2002.
[44]谢处方,饶克谨.电磁场与电磁波[M].高等教育出版社,2006.
[45]Rao N N. Fundamentals of electromagnetics for electrical and computer engineering[M]. Pearson Prentice Hall,2009.
[46]张善杰.矢量分析、圆柱函数和球函数[M].南京大学出版社,2011.
[47]谷超豪.数学物理方程[M].高等教育出版社,2002.
[48]王竹溪,郭敦仁.特殊函数概论[M].北京大学出版社,2000.
[49]奚定平.贝塞尔函数[M].高等教育出版社,1998.
[50]李世智.电磁场辐射与散射问题的矩量法[M].电子工业出版社,1985.
[51]王长清,祝西里,等.电磁场计算中的时域有限差分法[M].北京大学出版社,1994.
[52]Hrennikoff A. Solution of problems of elasticity by the framework method[J]. Journal of applied mechanics,1941,8(4):169-175.
[53]Courant R. Variational methods for the solution of problems of equilibrium and vibrations[J]. Bull. Amer. Math. Soc,1943,49(1):23.
[54]Barton M L, Cendes Z J. New vector finite elements for three-dimensional magnetic field computation[J]. Journal of Applied Physics,1987,61(8):3919-3921.
[55]Jin J M, Jin J, Jin J M. The finite element method in electromagnetics[M]. New York: Wiley,2002.
[56]周克定.工程电磁场数值计算理论方法及应用[M].高等教育出版社,1994.
[57]汤井田,肖晓,刘长生.被动源电磁测深自适应矢量有限元及双模反演[M].中南大学出版社,2010.
[58]Wu J Y, Lee R. The advantages of triangular and tetrahedral edge elements for electromagnetic modeling with the finite-element method[J]. Antennas and Propagation, IEEE Transactions on,1997,45(9):1431-1437.
[59]Horn R A, Johnson C R. Matrix analysis[M]. Cambridge university press,1990.
[60]张禾瑞,赫鈵新.高等代数[M].高等教育出版社,2007.
[60]李庆扬,莫孜中,祁力群.非线性方程组的数值解法[M].科学出版社,1987.
[62]Holland J H. Adaption in natural and artificial systems. An introductory analysis with applications to biology, control, and artificial intelligence[J].1975.
[63]周明,运筹学,孙树栋,等.遗传算法原理及应用[M].国防工业出版社,1999.
[64]雷英杰,张善文,李续武. MATLAB遗传算法工具箱及应用[M].西安电子科技大学出版社,2005.
[65]Sivanandam S N, Deepa S N. Introduction to genetic algorithms[M]. Springer Publishing Company, Incorporated,2007.
[66]Horn R A, Johnson C R. Matrix analysis[M]. Cambridge university press,1990.
[67]Ward L C, Byrne N M, Rutter K, et al. Reliability of multiple frequency bioelectrical impedance analysis:an intermachine comparison[J]. American Journal of Human Biology, 1997,9(1):63-72.
[68]Norton K A. The propagation of radio waves over the surface of the earth and in the upper atmosphere part1 [J]. Proceedings of the institute of Radio Engineers,1936,24(10): 1367-1387.
[69]Norton K A. The propagation of radio waves over the surface of the earth and in the upper atmosphere-part2 [J]. Proceedings of the Institute of Radio Engineers,1937,25(9): 1203-1236.
[70]林凡.电磁脉冲生物效应的剂量研究及安全标准探讨[D].华东师范大学,2004.
[71]梁安慧.变姿态人体模型的电磁剂量学研究[D].西安电子科技大学,2006.
[72]Gabriel C. Compilation of the Dielectric Properties of Body Tissues at RF and Microwave Frequencies[R]. KING'S COLL LONDON (UNITED KINGDOM) DEPT OF PHYSICS, 1996.
[73]FCC. Body Tissue Dielectric Parameter Tool [EB/OL]. http://transition.fcc.gov/oet/ rfsafety/dielectric.html.
[74]刘式达,刘式适.特殊函数[M].气象出版社,2002.
[75]Chew W C. Waves and fields in inhomogenous media[M]. New York: IEEE press,1995.
[76]Abramowitz M, Stegun I A. Handbook of Mathematical Function with Formulas, Graphs, and Mathematical Tables[J]. National Bureau of Standsards, Applied Mathematics Series, 1970,55.
[77]Peterson A F. Absorbing boundary conditions for the vector wave equation[J]. Microwave and Optical Technology Letters,1988,1(2):62-64.
[78]Zasowski T, Meyer G, Althaus F, et al. UWB signal propagation at the human head[J]. Microwave Theory and Techniques, IEEE Transactions on,2006,54(4):1836-1845.
[79]Zasowski T, Meyer G, Althaus F, et al. Propagation effects in UWB body area networks[C]//Ultra-Wideband,2005. ICU 2005.2005 IEEE International Conference on. IEEE,2005:16-21.
[80]Dhatt G, Touzot G. Finite Element Method[M]. Wiley-ISTE,2012.
[81]Barlow H M, Brown J, MA P. Radio surface waves[M]. Oxford: Clarendon Press,1962.
[82]黄卡玛,赵翔.电磁场中的逆问题及应用[M].科学出版社,2005.
[83]雷刚.电磁逆问题的统计分析方法[D].华中科技大学,2009.
[84]刘磊.新型天线高维多目标优化设计理论和技术研究[D].浙江大学,2012
[85]雷德明.多目标智能优化算法及其应用[M].科学出版社,2009.
[86]Srinivas N, Deb K. Muiltiobjective optimization using nondominated sorting in genetic algorithms[J]. Evolutionary computation,1994,2(3):221-248.
[87]Sawaragi Y, Nakayama H, Tanino T. Theory of multiobjective optimization[M]. New York: Academic Press,1985.
[88]Rao S S. Engineering optimization:theory and practice[M]. Wiley,2009.
[89]Harvey R T, Patterson J H. An implicit enumeration algorithm for the time/cost tradeoff problem in project network analysis[J]. Foundations of Control Engineering,1979,4(2): 107-117.
[90]Robinson D R. A dynamic programming solution to cost-time tradeoff for CPM[J]. Management Science,1975,22(2):158-166.
[91]Coello C A C, Lamont G B, Veldhuizen D A V. Evolutionary algorithms for solving multi-objective problems[M]. Springer,2007.
[92]Schaffer J D. Multiple Objective Optimization with Vector Evaluated Genetic Algorithms[C]//Proceedings of the 1st International Conference on Genetic Algorithms and their Applications, Pittsburgh.1985.
[93]Eklund N H, Embrechts M J. GA-based multi-objective optimization of visible spectra for lamp design[J]. Smart Engineering System Design:Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining and Complex Systems,1999:451-456.
[94]Coello C A C, Christiansen A D. Two new GA-based methods for multiobjective optimization[J]. Civil Engineering Systems,1998,15(3):207-243.
[95]Goldberg D E. Genetic algorithms in search, optimization, and machine learning[M]. Addison-Wesley Publishing Company,1989
[96]Fonseca C M, Fleming P J. Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization[C]//Proceedings of the fifth international conference on genetic algorithms.1993,423:416-423.
[97]Zitzler E, Thiele L. Multiobjective evolutionary algorithms:A comparative case study and the strength pareto approach[J]. Evolutionary Computation, IEEE Transactions on,1999, 3(4):257-271.
[98]Deb K, Pratap A, Agarwal S, et al. A fast and elitist multiobjective genetic algorithm: NSGA-Ⅱ[J]. Evolutionary Computation, IEEE Transactions on,2002,6(2):182-197.
[99]郑金华.多目标进化算法及其应用[M].科学出版社,2007.