随机反馈延时下GBN-ARQ协议发送端延时分析与研究
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摘要
网络的出现使得数据通信技术得到了广泛使用和快速的发展,与其他的通信方式相比,数据通信的最大特点就是对通信的可靠性要求较高。同时,在通信系统中,传输延时也是衡量网络性能的一个重要参数,直接影响到数据包的流量控制。为了保证传输质量,提高通信系统的吞吐性能,在无线通信系统中加入差错控制技术并准确的计算系统延时是无线通信技术发展的重要研究方向。
自适应调制与编码技术是一种链路自适应技术,发送端通过反馈信息判定信道状况后自适应地选择调制与编码方案,最大限度地利用了频谱利用率。本文针对一种常用的差错控制技术——回退N帧自动重发请求(Go-Back-N Automatic Retransmission Request,GBN-ARQ)协议进行了延时分析,重点研究了数据包在发送端的延时情况,在反馈延时随机变化的背景下,提出了一个考虑了链路自适应技术条件下的数据包传输过程的马尔科夫延时模型。该模型首先考虑到无线信道的时变特性对数据通信系统性能的影响,同时随着数据业务的大量增加,频谱资源也越来越紧张,建立链路自适应技术条件下无线信道状态转移情况的模型,在此基础上建立了具有随机反馈延时条件下整个系统状态演变的马尔科夫模型,然后运用矩阵几何理论计算出准确的数据包发送端延时。准确的数据包发送端延时值,可以使发送端的数据包流量得到更好的控制,从而提高整个通信系统的性能。
为了验证该马尔科夫延时模型的准确性,本文还对反馈延时随机变化下的GBN-ARQ协议的发送端延时进行了仿真,仿真结果验证了该模型计算的准确性。
本文的发送端数据包延时模型的计算过程,充分体现了网络延时随机可变的特点,数据和结果都相对精确,为计算无线网络中数据业务的延时提供了一种可靠的方法。同时,本文第4章的理论计算结果,对比分析了系统参数对延时性能的影响。结论表明,多普勒频移和发送端数据包到达率两个参数都不存在最优化的求解。
Since the emergence of the telecommunications network, data communication techniques has been used widely, and developed rapidly. Compared with other means of communication, the most characteristic feature of the data communication is the high reliability. Meanwhile, in a communication system, transmission delay is an important parameter of the network performance,which affects the flow control of the transmitter. In order to ensure the quality of the transmission and to improve the system throughput performance, it is an important researching direction to apply the error-control techniques which request a precise evaluation of the transmission delay.
By adaptive modulating and coding techniques, which are imported for link adaptation, a transmitter can acquire the channel state through the feedback channel, thus it is able to adaptively change the modulating and coding scheme to maximize the spectrum efficiency. In this paper, a widely used error-control technique-Go-Back-N Automatic Retransmission Request (GBN-ARQ) protocol is researched. Because the feedback delay is a random variable, a markov model for the data packets transmission which applies the link adaptation techniques. This model concerns an important fact,the parameter of the wireless channel is time-varying,it can reduce the system performance,and with the development of the date services, spectrum resources are increasingly strained.The state transition model is presented while the link is adaptive. On this basis, the markov model of system states is established while the feedback delay is random variable.Then the transmitting end delay statistics are obtained by using the matrix-geometric methods,so the best flow control can be received,and the performance of the entire communication system is improved.
We validate the transmitting end delay model by simulation. The calculated result of the packets delay at transmitter is same with the simulation result.
In this paper, the calculating process for the transmitting end delay fully concerns the random time-varying feedback delay, meanwhile the results are precise. It provides a reliable way to evaluate the time-delay for a wireless network. Meanwhile, by comparing the simulated results, we analysis the impact on transmitting end delay in different system parameters. The conclusion is that there are no best solution to both the doppler frequency shift and the packet arrival rate of the transmitter.
自适应调制与编码技术是一种链路自适应技术,发送端通过反馈信息判定信道状况后自适应地选择调制与编码方案,最大限度地利用了频谱利用率。本文针对一种常用的差错控制技术——回退N帧自动重发请求(Go-Back-N Automatic Retransmission Request,GBN-ARQ)协议进行了延时分析,重点研究了数据包在发送端的延时情况,在反馈延时随机变化的背景下,提出了一个考虑了链路自适应技术条件下的数据包传输过程的马尔科夫延时模型。该模型首先考虑到无线信道的时变特性对数据通信系统性能的影响,同时随着数据业务的大量增加,频谱资源也越来越紧张,建立链路自适应技术条件下无线信道状态转移情况的模型,在此基础上建立了具有随机反馈延时条件下整个系统状态演变的马尔科夫模型,然后运用矩阵几何理论计算出准确的数据包发送端延时。准确的数据包发送端延时值,可以使发送端的数据包流量得到更好的控制,从而提高整个通信系统的性能。
为了验证该马尔科夫延时模型的准确性,本文还对反馈延时随机变化下的GBN-ARQ协议的发送端延时进行了仿真,仿真结果验证了该模型计算的准确性。
本文的发送端数据包延时模型的计算过程,充分体现了网络延时随机可变的特点,数据和结果都相对精确,为计算无线网络中数据业务的延时提供了一种可靠的方法。同时,本文第4章的理论计算结果,对比分析了系统参数对延时性能的影响。结论表明,多普勒频移和发送端数据包到达率两个参数都不存在最优化的求解。
Since the emergence of the telecommunications network, data communication techniques has been used widely, and developed rapidly. Compared with other means of communication, the most characteristic feature of the data communication is the high reliability. Meanwhile, in a communication system, transmission delay is an important parameter of the network performance,which affects the flow control of the transmitter. In order to ensure the quality of the transmission and to improve the system throughput performance, it is an important researching direction to apply the error-control techniques which request a precise evaluation of the transmission delay.
By adaptive modulating and coding techniques, which are imported for link adaptation, a transmitter can acquire the channel state through the feedback channel, thus it is able to adaptively change the modulating and coding scheme to maximize the spectrum efficiency. In this paper, a widely used error-control technique-Go-Back-N Automatic Retransmission Request (GBN-ARQ) protocol is researched. Because the feedback delay is a random variable, a markov model for the data packets transmission which applies the link adaptation techniques. This model concerns an important fact,the parameter of the wireless channel is time-varying,it can reduce the system performance,and with the development of the date services, spectrum resources are increasingly strained.The state transition model is presented while the link is adaptive. On this basis, the markov model of system states is established while the feedback delay is random variable.Then the transmitting end delay statistics are obtained by using the matrix-geometric methods,so the best flow control can be received,and the performance of the entire communication system is improved.
We validate the transmitting end delay model by simulation. The calculated result of the packets delay at transmitter is same with the simulation result.
In this paper, the calculating process for the transmitting end delay fully concerns the random time-varying feedback delay, meanwhile the results are precise. It provides a reliable way to evaluate the time-delay for a wireless network. Meanwhile, by comparing the simulated results, we analysis the impact on transmitting end delay in different system parameters. The conclusion is that there are no best solution to both the doppler frequency shift and the packet arrival rate of the transmitter.
引文
[1]樊昌信.通信原理教程.北京：电子工业出版,2004,16-18
[2]Burton H O, Sullivan D D. Errors and Error Control.Proceedings of the IEEE, 1972,60(11):1293-1301
[3]Borgonovo F, Capone A.Efficiency of error-control schemes for real-time wireless applications on the Gilbert channel.IEEE Transactions on Vehicular Technology, 2005,54(1):246-258
[4]Babich F, Valentinuzzi E, Vatta F.Performance of hybrid ARQ schemes for the LEO satellite channel. In:IEEE Global Telecommunications Conference. Antonio,2001,2709-2713
[5]Shu L, Philip S Y. A hybrid ARQ scheme with parity retransmission for error control of satellite channels.IEEE transactions on communications,1982,30(7): 78-92
[6]王晓萍,任欣.无线通信网中的差错控制技术.信息传输与接入技术,2008,34(4)：23-24
[7]Hancock J, Lindesey W.Optimum performance of self-adaptive systems operating through a Rayleigh-fading medium. IEEE Transactions on Communication Systems,1963,11(4):443-453
[8]Hayes J. Adaptive feedback communications. IEEE Transactions on Communication Technology,1968,16(1):29-34
[9]Goldsmith A J, Chua S G. Variable-rate variable-power MQAM for fading channels. IEEE Transactions on Communications,1997,45(10):1218-1230
[10]Torrance J, Hanzo L. Optimisation of switching levels for adaptive modulation in a slow Rayleigh fading channel. Electronics Letters,1996,32(13):1167-1169
[11]Choi B G, Hanzo L. Optimum mode-switching-assisted constant-power single-and multicarrier adaptive modulation. IEEE Transactions on Vehicular Technology,2003,52(3):536-560
[12]程娟,周宗仪,吴伟民.基于MR-ARQ协议的多业务QoS保证机制研究.无线电通信技术,2006,2(32)：32-35
[13]何波,李军,林家儒等.TDD慢衰落系统中的预重传GBN-ARQ性能分析.电子与信息学报,2006,28(11)：2086-2089
[14]何波,李军,林家儒等.具有缓存结构GBN预测重传.通信学报,2005, 26(12)：24-29
[15]Annamalai A, Vijay B K. Analysis and Optimization of Adaptive Multicopy Transmission ARQ Protocols for Time-Varying Channels. IEEE Transactions on communications,1998,46(10):1356-1368
[16]Ranko Vojinovi'c, Grozdan Petrovi'c, Zoran Petrovi'c. The analysis of the adaptive three-mode ARQ GBN scheme using retransmission cycles Mechanism. Int.J.Electron.Commun. (AEU) 2006,60(3):190-198
[17]Ranko V, Zoran P. A Novel Three-State ARQ Scheme for Variable Error-Tate Channels. Int. J. Electron. Commun. (AEU),2002,56(6):389-395
[18]金顺福,李国萍,张金亮等.基于离散时间排队的ARQ性能分析.计算机工程,2009,35(17)：31-33
[19]刘存明,黎锁平.基于噪声信道的三种单模式GBN-ARQ系统时延性能分析与比较.兰州理工大学学报,2008,34(3):95-99
[20]黎锁平,刘存明,何志鹏.无线数据传输的GBN-ARQ和SR-ARQ系统时延性能研究.信号处理,2009,25(3)：384-388
[21]王春.基于Fano译码复杂度和隐马尔科夫模型的信道建模和预测：[南京理工大学硕士学位论文].南京：南京理工大学,2008,17-18
[22]陆大金.随机过程及其应用.北京：清华大学出版社,1986,38-41
[23]Gilbert E N. Capacity of a burst-noise channel Bell Syst. Tech.J.1960,39(9): 1253-1265
[24]Elliot E O. Estimates of error rates for codes on burst-noise channels. Bell Syst.Tech.J.1963,42(9):1977-1997
[25]Wang H S, Moayeri N. Modeling capacity and joint source/channel coding for Rayleigh fading channels. In:Proc. IEEE Vehicular Technology Conf. Secaucus, 1993:473-479
[26]Zhang Q, Kassam S K. Finite-state Markov model for Rayleigh fading channels. IEEE Trans.Commun,1999,47(11):1688-1692
[27]Catreus S, Erceg V, Gesbert D etal.Adaptive modulation and MIMO coding for broadband wireless data networks. IEEE Commun,2001,40(6):108-115
[28]Wang H S, Moayeri N.Finite-state Markov channel-A useful model for radio communication channels. IEEE Trans. Veh. Technol,1995,44(2):163-171
[29]Razavilar J K, Liu J R, Marcus S I. Jointly optimize bit-rate/delay control policy for wireless packet networks with fading channels. IEEE Trans. Commun,2002, 50(3):484-494
[30]Liu Q, Zhou S, Giannakis G B. Queuing with adaptive modulation and coding over wireless link:Cross-layer analysis and design. IEEE Trans. Wireless Commun,2005,4(3):1142-1153
[31]Wang H S, Chang P C. On verifying the first-order Markovian assumption for a Rayleigh fading channel model. IEEE Trans,1996,45(3):353-357
[32]Guan Y L, Turner L F.Generalised FSMC model for radio channels with correlated fading. IEEE Proc. Commun,1999,146(2):133-137
[33]Zorzi M, Rao R R. Lateness probability for a retransmission Scheme for error control on a two state Markov channel.IEEE Trans. Commun,1999,47(10): 1537-1548
[34]Kim J G, Krunz M M.Delay analysis of selective repeat ARQ for a Markovian source over wireless channel. IEEE Trans. Veh. Technol,2000,49(5):1968-1981
[35]Badia L, Rossi M, Zorzi M. SR ARQ packet delay statistics in Markov channels in the presense of variable arrival rate. IEEE Trans. Wireless Commun.2006, 5(7):1639-1644
[36]Rosso M, Badia L, Zorzi M. SR-ARQ delay statistics on N-state Markov channels with finite round trip delay. In:Proc. IEEE GLOBECOM. Antonio, 2004,5(11):3032-3036
[37]杨光,罗鹏程,周经伦等.基于HARQ机制的数据链通信性能分析.信号处理,2009,25(12)：1840-1847
[38]Long B L, Ekram H. Queueing Analysis for GBN and SR ARQ Protocols under Dynamic Radio Link Adaptation with Non-Zero Feedback Delay. IEEE Trans. Wireless Commun,2007,6(9):3418-3428
[39]Neuts M F. Matrix Geometric Solutions in Stochastic Models-An Algorithmic Approach. Baltimore.MD:John Hopkins Univ. Press,1981,1-141
[40]杨家玮,盛敏,刘勤.移动通信基础.电子工业出版社,2005：37-41
[41]李煜国.多径瑞利信道下OFDM信号的识别方法研究：[西安电子科技大学硕士学位论文].西安：西安电子科技大学,2009,13-15
[42]张秀峰.OFDM系统中自适应调制与编码技术研究：[湖南大学硕士学位论文].长沙：湖南大学,2008,7-11
[43]陆琪.无线通信衰落信道的实现：[大连海事大学硕士学位论文].大连：大连海事大学,2007,5-15
[44]Yip K W, Ng T S. A simulation model for Nakagami-m fading channels m<1. IEEE Trans Commun,2000,48(2):214-221
[45]侯晓辉.相关Nakagami信道的仿真方法分析及其特性仿真：[南京邮电大学硕士学位论文].南京：南京邮电大学,2008,6-10
[46]雷鸣,徐月善,蔡鹏等.自适应调制系统在衰落中的性能分析.北京邮电大学学报.2004,27(1)：31-35
[47]宋平.链路自适应技术的研究：[东南大学硕士学位论文].南京：东南大学,2007,5-10
[48]高红伟.LTE UPA系统链路自适应技术研究：[东南大学硕士学位论文].南京：东南大学,2007,5-7
[49]刘次华.随机过程(第二版).武汉：华中科技大学出版社,1998,33-34
[50]Alfa A S. Discrete time queues and matrix-analytic methods. Sociedad de Esta distica e Investigation Operativa,2002,10(2):147-210
[2]Burton H O, Sullivan D D. Errors and Error Control.Proceedings of the IEEE, 1972,60(11):1293-1301
[3]Borgonovo F, Capone A.Efficiency of error-control schemes for real-time wireless applications on the Gilbert channel.IEEE Transactions on Vehicular Technology, 2005,54(1):246-258
[4]Babich F, Valentinuzzi E, Vatta F.Performance of hybrid ARQ schemes for the LEO satellite channel. In:IEEE Global Telecommunications Conference. Antonio,2001,2709-2713
[5]Shu L, Philip S Y. A hybrid ARQ scheme with parity retransmission for error control of satellite channels.IEEE transactions on communications,1982,30(7): 78-92
[6]王晓萍,任欣.无线通信网中的差错控制技术.信息传输与接入技术,2008,34(4)：23-24
[7]Hancock J, Lindesey W.Optimum performance of self-adaptive systems operating through a Rayleigh-fading medium. IEEE Transactions on Communication Systems,1963,11(4):443-453
[8]Hayes J. Adaptive feedback communications. IEEE Transactions on Communication Technology,1968,16(1):29-34
[9]Goldsmith A J, Chua S G. Variable-rate variable-power MQAM for fading channels. IEEE Transactions on Communications,1997,45(10):1218-1230
[10]Torrance J, Hanzo L. Optimisation of switching levels for adaptive modulation in a slow Rayleigh fading channel. Electronics Letters,1996,32(13):1167-1169
[11]Choi B G, Hanzo L. Optimum mode-switching-assisted constant-power single-and multicarrier adaptive modulation. IEEE Transactions on Vehicular Technology,2003,52(3):536-560
[12]程娟,周宗仪,吴伟民.基于MR-ARQ协议的多业务QoS保证机制研究.无线电通信技术,2006,2(32)：32-35
[13]何波,李军,林家儒等.TDD慢衰落系统中的预重传GBN-ARQ性能分析.电子与信息学报,2006,28(11)：2086-2089
[14]何波,李军,林家儒等.具有缓存结构GBN预测重传.通信学报,2005, 26(12)：24-29
[15]Annamalai A, Vijay B K. Analysis and Optimization of Adaptive Multicopy Transmission ARQ Protocols for Time-Varying Channels. IEEE Transactions on communications,1998,46(10):1356-1368
[16]Ranko Vojinovi'c, Grozdan Petrovi'c, Zoran Petrovi'c. The analysis of the adaptive three-mode ARQ GBN scheme using retransmission cycles Mechanism. Int.J.Electron.Commun. (AEU) 2006,60(3):190-198
[17]Ranko V, Zoran P. A Novel Three-State ARQ Scheme for Variable Error-Tate Channels. Int. J. Electron. Commun. (AEU),2002,56(6):389-395
[18]金顺福,李国萍,张金亮等.基于离散时间排队的ARQ性能分析.计算机工程,2009,35(17)：31-33
[19]刘存明,黎锁平.基于噪声信道的三种单模式GBN-ARQ系统时延性能分析与比较.兰州理工大学学报,2008,34(3):95-99
[20]黎锁平,刘存明,何志鹏.无线数据传输的GBN-ARQ和SR-ARQ系统时延性能研究.信号处理,2009,25(3)：384-388
[21]王春.基于Fano译码复杂度和隐马尔科夫模型的信道建模和预测：[南京理工大学硕士学位论文].南京：南京理工大学,2008,17-18
[22]陆大金.随机过程及其应用.北京：清华大学出版社,1986,38-41
[23]Gilbert E N. Capacity of a burst-noise channel Bell Syst. Tech.J.1960,39(9): 1253-1265
[24]Elliot E O. Estimates of error rates for codes on burst-noise channels. Bell Syst.Tech.J.1963,42(9):1977-1997
[25]Wang H S, Moayeri N. Modeling capacity and joint source/channel coding for Rayleigh fading channels. In:Proc. IEEE Vehicular Technology Conf. Secaucus, 1993:473-479
[26]Zhang Q, Kassam S K. Finite-state Markov model for Rayleigh fading channels. IEEE Trans.Commun,1999,47(11):1688-1692
[27]Catreus S, Erceg V, Gesbert D etal.Adaptive modulation and MIMO coding for broadband wireless data networks. IEEE Commun,2001,40(6):108-115
[28]Wang H S, Moayeri N.Finite-state Markov channel-A useful model for radio communication channels. IEEE Trans. Veh. Technol,1995,44(2):163-171
[29]Razavilar J K, Liu J R, Marcus S I. Jointly optimize bit-rate/delay control policy for wireless packet networks with fading channels. IEEE Trans. Commun,2002, 50(3):484-494
[30]Liu Q, Zhou S, Giannakis G B. Queuing with adaptive modulation and coding over wireless link:Cross-layer analysis and design. IEEE Trans. Wireless Commun,2005,4(3):1142-1153
[31]Wang H S, Chang P C. On verifying the first-order Markovian assumption for a Rayleigh fading channel model. IEEE Trans,1996,45(3):353-357
[32]Guan Y L, Turner L F.Generalised FSMC model for radio channels with correlated fading. IEEE Proc. Commun,1999,146(2):133-137
[33]Zorzi M, Rao R R. Lateness probability for a retransmission Scheme for error control on a two state Markov channel.IEEE Trans. Commun,1999,47(10): 1537-1548
[34]Kim J G, Krunz M M.Delay analysis of selective repeat ARQ for a Markovian source over wireless channel. IEEE Trans. Veh. Technol,2000,49(5):1968-1981
[35]Badia L, Rossi M, Zorzi M. SR ARQ packet delay statistics in Markov channels in the presense of variable arrival rate. IEEE Trans. Wireless Commun.2006, 5(7):1639-1644
[36]Rosso M, Badia L, Zorzi M. SR-ARQ delay statistics on N-state Markov channels with finite round trip delay. In:Proc. IEEE GLOBECOM. Antonio, 2004,5(11):3032-3036
[37]杨光,罗鹏程,周经伦等.基于HARQ机制的数据链通信性能分析.信号处理,2009,25(12)：1840-1847
[38]Long B L, Ekram H. Queueing Analysis for GBN and SR ARQ Protocols under Dynamic Radio Link Adaptation with Non-Zero Feedback Delay. IEEE Trans. Wireless Commun,2007,6(9):3418-3428
[39]Neuts M F. Matrix Geometric Solutions in Stochastic Models-An Algorithmic Approach. Baltimore.MD:John Hopkins Univ. Press,1981,1-141
[40]杨家玮,盛敏,刘勤.移动通信基础.电子工业出版社,2005：37-41
[41]李煜国.多径瑞利信道下OFDM信号的识别方法研究：[西安电子科技大学硕士学位论文].西安：西安电子科技大学,2009,13-15
[42]张秀峰.OFDM系统中自适应调制与编码技术研究：[湖南大学硕士学位论文].长沙：湖南大学,2008,7-11
[43]陆琪.无线通信衰落信道的实现：[大连海事大学硕士学位论文].大连：大连海事大学,2007,5-15
[44]Yip K W, Ng T S. A simulation model for Nakagami-m fading channels m<1. IEEE Trans Commun,2000,48(2):214-221
[45]侯晓辉.相关Nakagami信道的仿真方法分析及其特性仿真：[南京邮电大学硕士学位论文].南京：南京邮电大学,2008,6-10
[46]雷鸣,徐月善,蔡鹏等.自适应调制系统在衰落中的性能分析.北京邮电大学学报.2004,27(1)：31-35
[47]宋平.链路自适应技术的研究：[东南大学硕士学位论文].南京：东南大学,2007,5-10
[48]高红伟.LTE UPA系统链路自适应技术研究：[东南大学硕士学位论文].南京：东南大学,2007,5-7
[49]刘次华.随机过程(第二版).武汉：华中科技大学出版社,1998,33-34
[50]Alfa A S. Discrete time queues and matrix-analytic methods. Sociedad de Esta distica e Investigation Operativa,2002,10(2):147-210