数字集群通信协议DMR信道编解码技术的研究
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摘要
对讲机作为专用移动通信系统的一个重要的应用领域,由于它具有可以在无中心节点和通信基础设施的情况下进行快速呼叫等特点,所以在交通运输,公共安全,尤其是在应对自然灾害等突发事件中,公用移动通信系统基础设施遭到严重破坏时,对讲机可以发挥其它移动通信设备无法比拟的作用。但是,由于模拟对讲机频谱利用率低,传输距离有限和语音质量差等缺点限制了对讲机的应用。因此,国内外相关部门和企业都在致力于数字对讲机标准的制定和数字对讲机的研发。
DMR (Digital Mobile Radio)是欧洲电信标准协会于2007年发布的数字对讲机标准,它也是目前世界范围内的主流数字对讲机协议。目前,国外已经研发出基于DMR协议的数字对讲机并开始销售,但在国内,基于DMR协议数字对讲机的研发还处于起步阶段,只有少数几家对讲机企业正在进行研发和测试。本文的课题正是来源于其中一家企业的实际项目,该项目将完成基于DMR协议的数字对讲机的研发。
首先,本文从物理层、数据链路层和呼叫控制层三个方面介绍了DMR协议中的关键技术和参数指标。其次,本文重点介绍了DMR协议信道编码采用的各种码型的特点和编译码原理。接下来,对各种码型进行了编译码算法的设计和仿真实现,并选择传统的数字通信系统通信仿真模型对所设计的译码算法的纠错性能进行了仿真,从仿真的结果可知本文设计的各种译码算法相比于未编码的情况获得了一定的编码增益,验证了译码算法的正确性。同时,分析和总结了各码型在DMR系统语音和数据业务中的应用情况,并对这两种业务的性能进行了仿真。最后,重点研究了BPTC(Block Product Turbo Code)(196,96),因为其在DMR系统中使用最广泛,所以其译码纠错性能的好坏直接影响了DMR系统的通信质量。BPTC(196,96)属于Turbo乘积码,为了获得其最佳的纠错性能可以采用软判决迭代译码。但是本文研究项目使用的硬件平台为ZSP400,其主频为96M,在其上完成迭代译码所消耗的时间大于DMR协议规定的突发时间,所以未采用这种译码方法。尽管如此,如果采用硬判决代数译码的方法,不能很好的发挥BPTC(196,96)的纠错性能,所以本文采用了软判决中可信度这一定义来解决硬判决代数译码的缺陷,使其纠错性能得到了一定的提高,同时又易于在ZSP400上进行实现。
Radio is an important application field of special mobile communication system, which can play an incomparable role comparing with other mobile communication equipment in many field such as, in the transportation, in public safety, especially in dealing with natural disasters emergency when public mobile communication system infrastructure have been severely disrupted, because it can be performed quickly call in the conditions of no center node and non-infrastructure.However, there are several disadvantages limiting the application of radio in analog radio, such as low frequency spectrum utilization rate, limited transmission distance is and low voice quality. Therefore, the domestic and foreign related departments and enterprises are committed to formulate standard of digital radio and development the digital radio.
DMR (Digital Mobile Radio) is the mainstream digital radio protocol, which released in2007by the European Telecommunications Standards Institute. At present, some enterprises have developed digital radio based on DMR protocol and began to sell in foreign countries. But at home, the development of digital radio is at the start stage, only a handful of radio enterprises are under development and testing. The topic of this paper is derived from one of the enterprises'actual project which will be completed the development of digital radio based on DMR protocol.
First of all, this paper introduced the key technology and parameters of the indicators in DMR protocol from physical layer, data link layer and control layer. Secondly, this paper introduced various channel code' characteristics and principle of coding and decoding, which is used in DMR protocol. Next, this paper designed and simulated some coding and decoding algorithms of various channel code, at the same time, it selected the traditional digital communication system simulation model to simulate the decoding algorithms' error correcting performance so that. And, the results of simulation shows that these decoding algorithms compared to no coding situation obtained certain coding gain and validation of these decoding algorithms is correct. At the same time, the paper analyzed and summed up the application of channel code in the DMR system voice and data services, besides, it simulated the performance of two kind of business. Finally, we focus on BPTC (196,96), because of its DMR system most widely used, so the decoding error correction performance will directly influence the quality of communication in DMR system. BPTC (196,96) belongs to Turbo product code. In order to obtain the optimum error correction performance, it can be decoded in soft decision decoding. But this paper's research project uses the hardware platform for the ZSP400which the main frequency is96M, so the time expense of iterative decoding is more than the burst time in DMR on it. Therefore this paper does not use iterative decoding algorithm. Nevertheless, it is a good way to decode the BPTC (196,96) using the hard decision decoding algebra method, so this paper used feasible degree this definition in soft decision to solve defects of the hard decision decoding algebra, which enhanced the error correcting capability and easily be carried out in ZSP400.
DMR (Digital Mobile Radio)是欧洲电信标准协会于2007年发布的数字对讲机标准,它也是目前世界范围内的主流数字对讲机协议。目前,国外已经研发出基于DMR协议的数字对讲机并开始销售,但在国内,基于DMR协议数字对讲机的研发还处于起步阶段,只有少数几家对讲机企业正在进行研发和测试。本文的课题正是来源于其中一家企业的实际项目,该项目将完成基于DMR协议的数字对讲机的研发。
首先,本文从物理层、数据链路层和呼叫控制层三个方面介绍了DMR协议中的关键技术和参数指标。其次,本文重点介绍了DMR协议信道编码采用的各种码型的特点和编译码原理。接下来,对各种码型进行了编译码算法的设计和仿真实现,并选择传统的数字通信系统通信仿真模型对所设计的译码算法的纠错性能进行了仿真,从仿真的结果可知本文设计的各种译码算法相比于未编码的情况获得了一定的编码增益,验证了译码算法的正确性。同时,分析和总结了各码型在DMR系统语音和数据业务中的应用情况,并对这两种业务的性能进行了仿真。最后,重点研究了BPTC(Block Product Turbo Code)(196,96),因为其在DMR系统中使用最广泛,所以其译码纠错性能的好坏直接影响了DMR系统的通信质量。BPTC(196,96)属于Turbo乘积码,为了获得其最佳的纠错性能可以采用软判决迭代译码。但是本文研究项目使用的硬件平台为ZSP400,其主频为96M,在其上完成迭代译码所消耗的时间大于DMR协议规定的突发时间,所以未采用这种译码方法。尽管如此,如果采用硬判决代数译码的方法,不能很好的发挥BPTC(196,96)的纠错性能,所以本文采用了软判决中可信度这一定义来解决硬判决代数译码的缺陷,使其纠错性能得到了一定的提高,同时又易于在ZSP400上进行实现。
Radio is an important application field of special mobile communication system, which can play an incomparable role comparing with other mobile communication equipment in many field such as, in the transportation, in public safety, especially in dealing with natural disasters emergency when public mobile communication system infrastructure have been severely disrupted, because it can be performed quickly call in the conditions of no center node and non-infrastructure.However, there are several disadvantages limiting the application of radio in analog radio, such as low frequency spectrum utilization rate, limited transmission distance is and low voice quality. Therefore, the domestic and foreign related departments and enterprises are committed to formulate standard of digital radio and development the digital radio.
DMR (Digital Mobile Radio) is the mainstream digital radio protocol, which released in2007by the European Telecommunications Standards Institute. At present, some enterprises have developed digital radio based on DMR protocol and began to sell in foreign countries. But at home, the development of digital radio is at the start stage, only a handful of radio enterprises are under development and testing. The topic of this paper is derived from one of the enterprises'actual project which will be completed the development of digital radio based on DMR protocol.
First of all, this paper introduced the key technology and parameters of the indicators in DMR protocol from physical layer, data link layer and control layer. Secondly, this paper introduced various channel code' characteristics and principle of coding and decoding, which is used in DMR protocol. Next, this paper designed and simulated some coding and decoding algorithms of various channel code, at the same time, it selected the traditional digital communication system simulation model to simulate the decoding algorithms' error correcting performance so that. And, the results of simulation shows that these decoding algorithms compared to no coding situation obtained certain coding gain and validation of these decoding algorithms is correct. At the same time, the paper analyzed and summed up the application of channel code in the DMR system voice and data services, besides, it simulated the performance of two kind of business. Finally, we focus on BPTC (196,96), because of its DMR system most widely used, so the decoding error correction performance will directly influence the quality of communication in DMR system. BPTC (196,96) belongs to Turbo product code. In order to obtain the optimum error correction performance, it can be decoded in soft decision decoding. But this paper's research project uses the hardware platform for the ZSP400which the main frequency is96M, so the time expense of iterative decoding is more than the burst time in DMR on it. Therefore this paper does not use iterative decoding algorithm. Nevertheless, it is a good way to decode the BPTC (196,96) using the hard decision decoding algebra method, so this paper used feasible degree this definition in soft decision to solve defects of the hard decision decoding algebra, which enhanced the error correcting capability and easily be carried out in ZSP400.
引文
[1]ETSI TS 102 361-1. "Electromagnetic compatibility and Radio spectrum Matters(ERM); Digital Mobile Radio(DMR)Systerms; Part 1:DMR Air Interface(AI)protocol"[s].2007.
[2]ETSI TS 102 36 1-2. "Electromagnetic compatibility and Radio spectrum Matters(ERM); Digital Mobile Radio(DMR)Systerms; Part 2:DMR voice and generic services and facilities" [s].2007.
[3]ETSI TS 102 36 1-3. "Electromagnetic compatibility and Radio spectrum Matters(ERM); Digital Mobile Radio(DMR)Systerms; Part 3:DMR Data protocol" [s].2007.
[4]ETSI TS 102 36 1-4. "Electromagnetic compatibility and Radio spectrum Matters(ERM); Digital Mobile Radio(DMR)Systerms; Part 4:DMR trunking protocol" [s].2007.
[5]Thesling W H. Block decoding with soft output information[P]. US:5930272,1999.
[6]Yejun He. Performance Evaluation of Adaptive Two-Dimensional Turbo Product Codes Composed of Hamming Codes [J]. IEEE International Conference on Integration Technology, 2007:103-107.
[7]Fu-Gang Wang, Yi Tang, Fan Yang. The iterative decoding algorithm research of Turbo Product Codes[J]. International Conference on Apperceiving Computing and Intelligence Analysis (ICACIA),2010:97-100.
[8]Chunyu Wang, Xiaoming Xie. The cascaded digital decimation filter based on DMR protocol [J]. Interational Conference on Electrical and Control Engineering (ICECE),2011:429-432
[9]David Freeman, Arnold Michelson. Two-dimensional product code with robust soft-decision decoding[J]. IEEE Transactions on Communications,1996:1222-1226.
[10]江藤良纯,金子敏信等著,张秀琴译.纠错码及其应用[M].北京：科学出版社,2004.
[11]王新梅,肖国镇等著.纠错码——原理与方法[M].西安：西安电子科技大学出版社,2006.
[12]张永光,楼才义等著.信道编码及其识别分析[M].北京：电子工业出版社,2010.
[13]郑祖辉,陆锦华等著.数字集群移动通信系统(第2版)[M].北京：电子工业出版社,2005.
[14](美)：ShuLinJr著,何元智译.差错控制编码[M].北京：机械工业出版社,2007.
[15]周炯槃,庞沁华,续大我等著.通信原(第3版)[M].北京：北京邮电大学出版社,2008.
[16]樊昌信,曹丽娜著.通信原理(第6版)[M].北京：国防工业出版社,2006.
[17]张元楷.基于ZSP400的C程序优化方法研究[D].西安：西安电子科技大学,2009.
[18]张喆.基于ZSP400的FFT算法的研究和实现[D].西安：西安电子科技大学,2009.
[19]文富鹏.基于Chase算法的Turbo乘积码解码算法研究与应用[D].四川：电子科技大学,2010.
[20]李伟.DMR数字端机射频模块研究与开发[D].西安：西安电子科技大学,2009.
[21]谭瑾博.DMR高层协议转发模式仿真以及协议性能研究[D].西安：西安电子科技大学,2009.
[22]丁婧.DMR数字端机物理层传输技术的研究[D].西安：西安电子科技大学,2009.
[23]刘辉,谢晓明.基于DMR通信协议的信道编码的研究[J].现代电子技术,2009年,第23期.
[24]吴震宇.Turbo乘积码编译码算法的研究[M].辽宁：大连理工大学,2009.
[25]徐卓.Turbo乘积码的Chase迭代译码算法研究与实现[D].四川：电子科技大学,2009.
[26]任友.RS码编译码算法研究及其硬件实现[D].四川：电子科技大学,2003.
[27]于湘珍,刘军,王秋娟.RS码在汉信码中的纠错性能分析及仿真[J].南京理工大学学报,2011年,第35卷,第1期.
[28]Theodore S.Rappaport著,周文安,付秀花,王志辉等译.无线通信原理与应用(第2版)[M].北京：电子工业版社,2006.
[29]Simon Haykin著,宋铁成,徐平平等译.通信系统(第4版)[M].北京：电子工业版社,2012.
[2]ETSI TS 102 36 1-2. "Electromagnetic compatibility and Radio spectrum Matters(ERM); Digital Mobile Radio(DMR)Systerms; Part 2:DMR voice and generic services and facilities" [s].2007.
[3]ETSI TS 102 36 1-3. "Electromagnetic compatibility and Radio spectrum Matters(ERM); Digital Mobile Radio(DMR)Systerms; Part 3:DMR Data protocol" [s].2007.
[4]ETSI TS 102 36 1-4. "Electromagnetic compatibility and Radio spectrum Matters(ERM); Digital Mobile Radio(DMR)Systerms; Part 4:DMR trunking protocol" [s].2007.
[5]Thesling W H. Block decoding with soft output information[P]. US:5930272,1999.
[6]Yejun He. Performance Evaluation of Adaptive Two-Dimensional Turbo Product Codes Composed of Hamming Codes [J]. IEEE International Conference on Integration Technology, 2007:103-107.
[7]Fu-Gang Wang, Yi Tang, Fan Yang. The iterative decoding algorithm research of Turbo Product Codes[J]. International Conference on Apperceiving Computing and Intelligence Analysis (ICACIA),2010:97-100.
[8]Chunyu Wang, Xiaoming Xie. The cascaded digital decimation filter based on DMR protocol [J]. Interational Conference on Electrical and Control Engineering (ICECE),2011:429-432
[9]David Freeman, Arnold Michelson. Two-dimensional product code with robust soft-decision decoding[J]. IEEE Transactions on Communications,1996:1222-1226.
[10]江藤良纯,金子敏信等著,张秀琴译.纠错码及其应用[M].北京：科学出版社,2004.
[11]王新梅,肖国镇等著.纠错码——原理与方法[M].西安：西安电子科技大学出版社,2006.
[12]张永光,楼才义等著.信道编码及其识别分析[M].北京：电子工业出版社,2010.
[13]郑祖辉,陆锦华等著.数字集群移动通信系统(第2版)[M].北京：电子工业出版社,2005.
[14](美)：ShuLinJr著,何元智译.差错控制编码[M].北京：机械工业出版社,2007.
[15]周炯槃,庞沁华,续大我等著.通信原(第3版)[M].北京：北京邮电大学出版社,2008.
[16]樊昌信,曹丽娜著.通信原理(第6版)[M].北京：国防工业出版社,2006.
[17]张元楷.基于ZSP400的C程序优化方法研究[D].西安：西安电子科技大学,2009.
[18]张喆.基于ZSP400的FFT算法的研究和实现[D].西安：西安电子科技大学,2009.
[19]文富鹏.基于Chase算法的Turbo乘积码解码算法研究与应用[D].四川：电子科技大学,2010.
[20]李伟.DMR数字端机射频模块研究与开发[D].西安：西安电子科技大学,2009.
[21]谭瑾博.DMR高层协议转发模式仿真以及协议性能研究[D].西安：西安电子科技大学,2009.
[22]丁婧.DMR数字端机物理层传输技术的研究[D].西安：西安电子科技大学,2009.
[23]刘辉,谢晓明.基于DMR通信协议的信道编码的研究[J].现代电子技术,2009年,第23期.
[24]吴震宇.Turbo乘积码编译码算法的研究[M].辽宁：大连理工大学,2009.
[25]徐卓.Turbo乘积码的Chase迭代译码算法研究与实现[D].四川：电子科技大学,2009.
[26]任友.RS码编译码算法研究及其硬件实现[D].四川：电子科技大学,2003.
[27]于湘珍,刘军,王秋娟.RS码在汉信码中的纠错性能分析及仿真[J].南京理工大学学报,2011年,第35卷,第1期.
[28]Theodore S.Rappaport著,周文安,付秀花,王志辉等译.无线通信原理与应用(第2版)[M].北京：电子工业版社,2006.
[29]Simon Haykin著,宋铁成,徐平平等译.通信系统(第4版)[M].北京：电子工业版社,2012.