TETRA2系统自适应调制解调技术的研究
摘要
移动通信频谱资源的有限性,决定了未来的移动通信,必须采用频谱利用率高的调制技术和信道抗衰落技术,来提高系统的性能,从而支持高速率数据和多媒体业务的传输。自适应传输技术是新一代移动通信和智能传输的核心技术之一,其中的自适应调制是根据信道的实时状态以及业务的不同特性动态调整传输参数,从而可以充分挖掘系统的传输潜力,提高频谱利用率,以获得最大的传输容量和最高的可靠性。
本文首先概述了数字集群通信系统,以及TETRA标准特性,然后对自适应调制解调技术的起源和发展进行了归纳总结,并对国内外研究现状及前景进行了阐述。介绍了移动通信系统对调制技术的要求,分析了现代数字调制技术的特点,详细分析了QAM调制解调的原理、主要参数和调制信号星座图的分布结构。自适应调制解调系统依据信噪比实时选择调制方式,因此,信号的信噪比估计是自适应调制解调系统的关键技术之一。本文详细分析了最大似然(ML)估计算法和最大后验概率(MAP)估计算法的原理,并给出了信噪比估计的克拉米罗下限。针对自适应MQAM调制解调技术,详细分析了自适应调制解调系统的基本原理、判决准则及性能参数。
最后,在MATALB平台下进行了仿真,并分析了QAM调制在高斯白噪声信道中的误码率,以及信噪比估计误差对自适应调制解调系统的影响。根据自适应调制解调技术的特点,进行了自适应变速率传输仿真系统的方案设计,包括:门限值的选择算法、信噪比区间的设定方法、系统功能的实现等,并对所提出的方案进行了仿真,给出仿真结果,并做了必要的分析。
Future mobile communications have to support the transmission of high rate data and multimedia applications in the radio spectrum, which is already extremely scarce.As one of the key techniques of new generation mobile communication systems and broadband wireless communications systems, adaptive transmission technique can exploit potential channel transmission ability sufficiently so that it enables the systems to reach the maximum transmission capacity and reliability by dynamically adjusting transmission parameters according to channel estimation and traffic QoS requirement.
Firstly, the digital trunking communication system and the characteristic of TETRA standard features are briefly introduced in this dissertation, and then summarize the origin and development of adaptive modulation technology, and describe the international actuality and tendency of adaptive modulation. Introduced the demand of modulation technologies for mobile communication system, and then analyze the modern digital modulation characteristics, the principle of QAM modulation and demodulation, the main parameters and the modulation signal constellation diagram of the distribution structure. Adaptive modulation and demodulation system choose the mode of modulation based on the signal-to-noise ratio of the signals.So,the estimation of signal-to-noise ratio is one of its key technologies.In this paper, analyze the principle of maximum likelihood (ML) estimation algorithm and maximum a posteriori probability (MAP) estimation algorithm, and give the lower limit of CRLB of the signal-to-noise ratio. For adaptive modulation and demodulation, analyze the basic principles, decision criteria and performance parameters.
At last, simulate using MATLAB software, analyze the BER of QAM modulation based on AWGN channel, and the influence of SNR estimation error on adaptive modulation and demodulation system. Design the adaptive variable rate transmission simulation system based on the characteristics of adaptive modulation and demodulation techniques, including: the choice of threshold algorithms, methods of signal-to-noise ratio settings, the realization of system function, and the simulation results and analysis are given.
本文首先概述了数字集群通信系统,以及TETRA标准特性,然后对自适应调制解调技术的起源和发展进行了归纳总结,并对国内外研究现状及前景进行了阐述。介绍了移动通信系统对调制技术的要求,分析了现代数字调制技术的特点,详细分析了QAM调制解调的原理、主要参数和调制信号星座图的分布结构。自适应调制解调系统依据信噪比实时选择调制方式,因此,信号的信噪比估计是自适应调制解调系统的关键技术之一。本文详细分析了最大似然(ML)估计算法和最大后验概率(MAP)估计算法的原理,并给出了信噪比估计的克拉米罗下限。针对自适应MQAM调制解调技术,详细分析了自适应调制解调系统的基本原理、判决准则及性能参数。
最后,在MATALB平台下进行了仿真,并分析了QAM调制在高斯白噪声信道中的误码率,以及信噪比估计误差对自适应调制解调系统的影响。根据自适应调制解调技术的特点,进行了自适应变速率传输仿真系统的方案设计,包括:门限值的选择算法、信噪比区间的设定方法、系统功能的实现等,并对所提出的方案进行了仿真,给出仿真结果,并做了必要的分析。
Future mobile communications have to support the transmission of high rate data and multimedia applications in the radio spectrum, which is already extremely scarce.As one of the key techniques of new generation mobile communication systems and broadband wireless communications systems, adaptive transmission technique can exploit potential channel transmission ability sufficiently so that it enables the systems to reach the maximum transmission capacity and reliability by dynamically adjusting transmission parameters according to channel estimation and traffic QoS requirement.
Firstly, the digital trunking communication system and the characteristic of TETRA standard features are briefly introduced in this dissertation, and then summarize the origin and development of adaptive modulation technology, and describe the international actuality and tendency of adaptive modulation. Introduced the demand of modulation technologies for mobile communication system, and then analyze the modern digital modulation characteristics, the principle of QAM modulation and demodulation, the main parameters and the modulation signal constellation diagram of the distribution structure. Adaptive modulation and demodulation system choose the mode of modulation based on the signal-to-noise ratio of the signals.So,the estimation of signal-to-noise ratio is one of its key technologies.In this paper, analyze the principle of maximum likelihood (ML) estimation algorithm and maximum a posteriori probability (MAP) estimation algorithm, and give the lower limit of CRLB of the signal-to-noise ratio. For adaptive modulation and demodulation, analyze the basic principles, decision criteria and performance parameters.
At last, simulate using MATLAB software, analyze the BER of QAM modulation based on AWGN channel, and the influence of SNR estimation error on adaptive modulation and demodulation system. Design the adaptive variable rate transmission simulation system based on the characteristics of adaptive modulation and demodulation techniques, including: the choice of threshold algorithms, methods of signal-to-noise ratio settings, the realization of system function, and the simulation results and analysis are given.
引文
1汤敏,蔡润,周蓓磊,王宗欣.第三代移动通信中的自适应调制和编码方法.复旦学报. 2004.2,Vol.43,No.1:82~86
2郑祖辉,陆锦华,郑岚.数字集群移动通信系统.第3版.电子工业出版社,2008:16~54
3 ETSI EN 300 392-1 v1.4.0, Terrestrial Trunked Radio (TETRA);Voice plus Data(V+D);Part 1:General network design. 2008,07
4 ETSI EN 300 392-2 v3.2.1, Terrestrial Trunked Radio (TETRA); Voice plus Data(V+D); Part 2: Air Interface(AI), 2007,09
5 Mehdi Nouri, Vincenzo Lottici, Ruggero Reggiannini, Diana Ball, Mark Rayne, Sepura Ltd. TEDS: a High Speed Digital Mobile Communication Air Interface for Professional Users, Part I: Overview of Physical Layer. IEEE Vehicular Technology Magazine. 2006,12
6 J. F. Hayes. Adaptive Feedback Communications. IEEE Trans. on Commun. Technol. Vol. Com-16,Feb.1968:29-34
7 J. K. Cavers. Variable-rate transmission for Rayleigh fading channels. IEEE Trans. on Commun., vol. Com-20: 1522. Feb. 1972
8 W. T. Webb. QAM: The modulation scheme for future mobile radio communications Electronics&communication engineering journal. Aug. 1992:167~176
9 W. T. Webb, R. Steele. Variable rate QAM for mobile radio. IEEE Trans. on Commun. Vol. 43, July I995:2223~2229
10 A. J. Goldsmith, S. G. Chua. Varible-rate variable-power MQAM for fading channels. IEEE Trans. on Commun. Vol. 45, no.10, October 1997:1218~1230
11 T.Xiaoyi, A.J.Goldsmith. An adaptive modulation scheme for simultaneous voice and date transmission over fading channel. IEEE Journal of selected areas in communications. Vo1.17,No.5,May 1999:839~849
12 T. Ue, S. Sampei, N. Morinaga. Symbol rate and modulation level controlled adaptive modulation system with TDMA/TDD for high bit rate transmission in high delay spread environments. Electronics Letters. 1996,32(4):304~305
13 H. Matsuoka, S. Sampei, N. Morinaga, Y. Kamio. Adaptive modulation systemwith variable coding rate concatenated code for high quality multi-media communication systems. IEEE Trans. Commun. E79-B,Mar,1996:328~334
14 T. Ikeda, S. Sampei and N. Morinaga. TDMA based adaptive modulation with dynamic channel assignment(AMDCA) for large capacity voice transmission in microcellular systems. Electronics Letters. Vo1,32(13),1996:1175~1176
15 K. Hamaguchi, Y. Kamio, E. Moriyama. Implementation and performance of QAM-level-controlled adaptive modulation for land mobile communications. Electronics letters. 1997,33(18):1529~1531
16 T. Ue, S. Sampei, N. Morinaga. Symbol rate controlled adaptive modulation /TDMA/TDD for wireless personal communication systems. IEEE Trans. Commun. Vol,E78-B,No. 8, August 1995:1117~1124
17 S. Sampei, N. Morinaga, and Y. Kamio, Adaptive modulation/TDMA with a BDDFE for 2Mbps multi-media wireless communication systems. In Proc. Vehicularlar Technology Conf. Vol.l,July1995:311~315
18 T. Ue, S. Sampei, N. Morinaga, and K. Hamaguchi, Symbol rate and modulation level-controlled adaptive modulationTDMA/TDD Systems for high-bit-rate wireless data transmission, IEEE Trans. on Vehicular Technology, Vol.47, No.4, 1998: 1134~1147
19张水英.自适应调制帧格式的设计与实现.浙江工业大学硕士论文. 2003:24~29
20谈振辉.数字移动通信系统中的调制技术.现代通信技术.1994,03
21 J. G. Proakis. Digital Communications. Fourth Edition. McGraw-Hill. 2000
22 Jonqyin Sun, Irving S. Reed. Performance of MDPSK, MPSK, and Noncoherent MFSK in Wireless Rician Fading Channels. IEEE Trans, on Commun. 1999,47(6)
23 PERTER Marc Fortune, Lajos Hanzo, Raymond Steele, Nonmem. On the Computation of 16QAM and 64QAM Performance in Rayleigh-Fading Channels. IEEE Trans, on Commun. 1992,E75-B(6)
24 R. M. Gagliardi, C. M. Thomas. PCM Data Reliability Monitoring through Estimation of Signal-to-Noise Ratio. IEEE Trans. Commun. 1968,16(3): 479~486
25 D. R. Pauluzzi, N. C. Beaulieu. A Comparison of SNR Estimation Techniques for the AWGN Channel. IEEE Trans. Commun. 2000,48(10):1681~1691
26 Yunfei Chen, Noman C. Beaulieu. An Approximate Maximum Likelihood Estimator for SNR Jointly Using Pilot and Data Symbols. IEEE Commun. Lett. 2005,9(6):517~520
27 B. Shah, S. Hinedi. The Split Symbol Moments SNR Estimator in Narrow-Band Channels. IEEE Trans. Aerosp. Electron. Syst,1990,26(5):37~747
28 Dong Joon Shin, Wonjin Sung, In-Kyung Kim. Simple SNR Estimation Methods for QPSK Modulated Short Bursts. IEEE Global Telecommunications Conference, San Antanio,2001,6:3644~3647
29 R. Matzner. An SNR Estimation Algorithm for Complex Baseband Signals Using Higher Order Statistics. Facta Universitatis,1993,6:41~52
30 R. Matzner, F. Engleberger. An SNR Estimation Algorithm for Complex Baseband Signals Using Higher Order Statistics. Proc. IEEE 1nt. Symp. Information Theory,Trondheim Norway,1994:119
31 N. C. Beaulieu, A. S. Toms, D. R. Pauluzzi. Comparison of Four SNR Estimators for QPSK Modulation. IEEE Commun. Lett.,2000,4(2):43-45
32范海波,陈军,曹志刚. AWGN信道中非恒包络信号SNR估计算法.电子学报,2002,30(9):1369~1372
33詹亚锋,曹志刚,马止新.无线数字通信的盲信噪比估计.清华大学学报. 2003,43(7):957~961
34 B. Li, R. DiFazio, A.Zeira. A Low Bias Algorithm to Estimate Negative SNRs in an AWGN Channel. IEEE Commun. Lett.,2002,6(11):469~471
35潘中富,李振东,梁庆林. AWGN信道FPSK信号幅度与信噪比的估计.通信学报,2004
36 H. Meyr, M. Moeneclaey, S. A. Fechtel. Digital Communication Receivers. Synchronization, Channel Estimation, and Signal Processing. John Wiley&Sons, INC. New York, 1998
37张贤达,保铮.通信信号处理.北京:国防工业出版社,2000:72~78
38 N. S. Alagha. Cramer-rao bounds of SNR estimation for BPSK and QPSK modulated signals. IEEE Commun. Letters.,5(1), 2001:10~12
39杜思深,王晓川,杨宁.自适应编码调制技术在通信中的应用.军事通信.2005.7:14~18
40张睿,李建东.变速率QAM调制.通信学报. 1988.Vol 19.No.4:8~12
41 Lay Teen Ong, Mohammad Shikh-Bahaei, and Jonathon A. Chambers. VariableRate and Variable Power MQAM System Based on Bayesian Bit Error Rate and Channel Estimation Techniques. IEEE Trans. on Commun. VOL. 56, NO. 2, 2008:177~182
42李艳峰,赵旦峰,李欣.一种自适应调制方案.信息与电子工程. Vo1.4,No.1. Feb., 2006
43范晨.自适应调制编码系统门限调整算法研究.北京邮电大学学报. 2006.04
44 A. Goldsmith and P. Varaiya. Capacity of fading channels with channel side information. IEEE Trans.on Information Theory vol. IT-43, pp. 1896-1992, November 1997
45 Jianhua Lu,K.B.Letaief. M-PSK and M-QAM BER Computation Using Signal-Space Concepts.IEEE Transactions On Communication , Vol.47, No.2,February 1999
46 Jianhua Lu, K. B .Letaief, Justin C-I Chuang. M-PSK and M-QAM BER Computation Using Signal-Space Concepts. IEEE Trans.on Commun. 1999
2郑祖辉,陆锦华,郑岚.数字集群移动通信系统.第3版.电子工业出版社,2008:16~54
3 ETSI EN 300 392-1 v1.4.0, Terrestrial Trunked Radio (TETRA);Voice plus Data(V+D);Part 1:General network design. 2008,07
4 ETSI EN 300 392-2 v3.2.1, Terrestrial Trunked Radio (TETRA); Voice plus Data(V+D); Part 2: Air Interface(AI), 2007,09
5 Mehdi Nouri, Vincenzo Lottici, Ruggero Reggiannini, Diana Ball, Mark Rayne, Sepura Ltd. TEDS: a High Speed Digital Mobile Communication Air Interface for Professional Users, Part I: Overview of Physical Layer. IEEE Vehicular Technology Magazine. 2006,12
6 J. F. Hayes. Adaptive Feedback Communications. IEEE Trans. on Commun. Technol. Vol. Com-16,Feb.1968:29-34
7 J. K. Cavers. Variable-rate transmission for Rayleigh fading channels. IEEE Trans. on Commun., vol. Com-20: 1522. Feb. 1972
8 W. T. Webb. QAM: The modulation scheme for future mobile radio communications Electronics&communication engineering journal. Aug. 1992:167~176
9 W. T. Webb, R. Steele. Variable rate QAM for mobile radio. IEEE Trans. on Commun. Vol. 43, July I995:2223~2229
10 A. J. Goldsmith, S. G. Chua. Varible-rate variable-power MQAM for fading channels. IEEE Trans. on Commun. Vol. 45, no.10, October 1997:1218~1230
11 T.Xiaoyi, A.J.Goldsmith. An adaptive modulation scheme for simultaneous voice and date transmission over fading channel. IEEE Journal of selected areas in communications. Vo1.17,No.5,May 1999:839~849
12 T. Ue, S. Sampei, N. Morinaga. Symbol rate and modulation level controlled adaptive modulation system with TDMA/TDD for high bit rate transmission in high delay spread environments. Electronics Letters. 1996,32(4):304~305
13 H. Matsuoka, S. Sampei, N. Morinaga, Y. Kamio. Adaptive modulation systemwith variable coding rate concatenated code for high quality multi-media communication systems. IEEE Trans. Commun. E79-B,Mar,1996:328~334
14 T. Ikeda, S. Sampei and N. Morinaga. TDMA based adaptive modulation with dynamic channel assignment(AMDCA) for large capacity voice transmission in microcellular systems. Electronics Letters. Vo1,32(13),1996:1175~1176
15 K. Hamaguchi, Y. Kamio, E. Moriyama. Implementation and performance of QAM-level-controlled adaptive modulation for land mobile communications. Electronics letters. 1997,33(18):1529~1531
16 T. Ue, S. Sampei, N. Morinaga. Symbol rate controlled adaptive modulation /TDMA/TDD for wireless personal communication systems. IEEE Trans. Commun. Vol,E78-B,No. 8, August 1995:1117~1124
17 S. Sampei, N. Morinaga, and Y. Kamio, Adaptive modulation/TDMA with a BDDFE for 2Mbps multi-media wireless communication systems. In Proc. Vehicularlar Technology Conf. Vol.l,July1995:311~315
18 T. Ue, S. Sampei, N. Morinaga, and K. Hamaguchi, Symbol rate and modulation level-controlled adaptive modulationTDMA/TDD Systems for high-bit-rate wireless data transmission, IEEE Trans. on Vehicular Technology, Vol.47, No.4, 1998: 1134~1147
19张水英.自适应调制帧格式的设计与实现.浙江工业大学硕士论文. 2003:24~29
20谈振辉.数字移动通信系统中的调制技术.现代通信技术.1994,03
21 J. G. Proakis. Digital Communications. Fourth Edition. McGraw-Hill. 2000
22 Jonqyin Sun, Irving S. Reed. Performance of MDPSK, MPSK, and Noncoherent MFSK in Wireless Rician Fading Channels. IEEE Trans, on Commun. 1999,47(6)
23 PERTER Marc Fortune, Lajos Hanzo, Raymond Steele, Nonmem. On the Computation of 16QAM and 64QAM Performance in Rayleigh-Fading Channels. IEEE Trans, on Commun. 1992,E75-B(6)
24 R. M. Gagliardi, C. M. Thomas. PCM Data Reliability Monitoring through Estimation of Signal-to-Noise Ratio. IEEE Trans. Commun. 1968,16(3): 479~486
25 D. R. Pauluzzi, N. C. Beaulieu. A Comparison of SNR Estimation Techniques for the AWGN Channel. IEEE Trans. Commun. 2000,48(10):1681~1691
26 Yunfei Chen, Noman C. Beaulieu. An Approximate Maximum Likelihood Estimator for SNR Jointly Using Pilot and Data Symbols. IEEE Commun. Lett. 2005,9(6):517~520
27 B. Shah, S. Hinedi. The Split Symbol Moments SNR Estimator in Narrow-Band Channels. IEEE Trans. Aerosp. Electron. Syst,1990,26(5):37~747
28 Dong Joon Shin, Wonjin Sung, In-Kyung Kim. Simple SNR Estimation Methods for QPSK Modulated Short Bursts. IEEE Global Telecommunications Conference, San Antanio,2001,6:3644~3647
29 R. Matzner. An SNR Estimation Algorithm for Complex Baseband Signals Using Higher Order Statistics. Facta Universitatis,1993,6:41~52
30 R. Matzner, F. Engleberger. An SNR Estimation Algorithm for Complex Baseband Signals Using Higher Order Statistics. Proc. IEEE 1nt. Symp. Information Theory,Trondheim Norway,1994:119
31 N. C. Beaulieu, A. S. Toms, D. R. Pauluzzi. Comparison of Four SNR Estimators for QPSK Modulation. IEEE Commun. Lett.,2000,4(2):43-45
32范海波,陈军,曹志刚. AWGN信道中非恒包络信号SNR估计算法.电子学报,2002,30(9):1369~1372
33詹亚锋,曹志刚,马止新.无线数字通信的盲信噪比估计.清华大学学报. 2003,43(7):957~961
34 B. Li, R. DiFazio, A.Zeira. A Low Bias Algorithm to Estimate Negative SNRs in an AWGN Channel. IEEE Commun. Lett.,2002,6(11):469~471
35潘中富,李振东,梁庆林. AWGN信道FPSK信号幅度与信噪比的估计.通信学报,2004
36 H. Meyr, M. Moeneclaey, S. A. Fechtel. Digital Communication Receivers. Synchronization, Channel Estimation, and Signal Processing. John Wiley&Sons, INC. New York, 1998
37张贤达,保铮.通信信号处理.北京:国防工业出版社,2000:72~78
38 N. S. Alagha. Cramer-rao bounds of SNR estimation for BPSK and QPSK modulated signals. IEEE Commun. Letters.,5(1), 2001:10~12
39杜思深,王晓川,杨宁.自适应编码调制技术在通信中的应用.军事通信.2005.7:14~18
40张睿,李建东.变速率QAM调制.通信学报. 1988.Vol 19.No.4:8~12
41 Lay Teen Ong, Mohammad Shikh-Bahaei, and Jonathon A. Chambers. VariableRate and Variable Power MQAM System Based on Bayesian Bit Error Rate and Channel Estimation Techniques. IEEE Trans. on Commun. VOL. 56, NO. 2, 2008:177~182
42李艳峰,赵旦峰,李欣.一种自适应调制方案.信息与电子工程. Vo1.4,No.1. Feb., 2006
43范晨.自适应调制编码系统门限调整算法研究.北京邮电大学学报. 2006.04
44 A. Goldsmith and P. Varaiya. Capacity of fading channels with channel side information. IEEE Trans.on Information Theory vol. IT-43, pp. 1896-1992, November 1997
45 Jianhua Lu,K.B.Letaief. M-PSK and M-QAM BER Computation Using Signal-Space Concepts.IEEE Transactions On Communication , Vol.47, No.2,February 1999
46 Jianhua Lu, K. B .Letaief, Justin C-I Chuang. M-PSK and M-QAM BER Computation Using Signal-Space Concepts. IEEE Trans.on Commun. 1999