无线协作中继传输技术研究
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摘要
在无线通信系统中，多径传播所引起的信号衰落严重影响了传输的质量，并极大限制了系统的容量。多天线分集技术是一种可以有效对抗衰落的方法，然而由于体积、功耗以及硬件复杂性等方面的限制，一些通信系统的移动终端很难配置多个天线。在这种背景下，协作分集技术被提出并得到了日益广泛的关注。
协作分集在一些文献中也称为协作式MIMO，是一种新的空域分集方式，使具有单天线的移动终端通过共享彼此的天线也可以获得分集的效果。由于移动终端间的距离通常远远大于数倍的波长，信道间的相关性大大降低，从而可以使信道容量最大化。然而，移动终端的多天线化是发展的必然趋势，在多天线终端的无线网络中仍然存在协作问题，具有多天线终端的协作式MIMO可以使系统性能得到进一步的提升。本文围绕采用解码转发方式的多天线终端协作式MIMO，研究了中继选择、功率分配和协作方法等问题。
首先，对多天线终端协作式MIMO系统的中继选择方法进行了研究。对四种经典的用户分组方法进行了介绍，并对其性能进行了比较。鉴于最差链路优先算法在性能上和可行性上都较好，本文接下来对最差链路优先算法的具体过程进行了分析。并在此基础上研究了基于最差链路优先算法的用户间信道优先匹配算法。进而，本文对用户间信道优先匹配算法在多天线终端系统中的能量增益进行了理论分析，并推导了相应公式。最后一部分内容对用户间信道优先匹配算法在多天线终端系统中的性能进行了仿真，并结合理论对仿真结果进行了分析。其间用随机选择算法对比分析了其选择用户的合理性；为显现出其在多天线系统中特性的变化，在这将该算法在单天线系统中的性能也做了仿真分析。另外，还涉及改变小区内用户数和算法门限以研究算法本身性能的仿真分析。
其次，对多天线终端协作式MIMO的功率分配方法进行了研究，提出了几种典型的功率分配算法，阐述它们的原理，推导相关的理论公式，通过仿真分析比较不同功率分配算法的性能。然后，简单介绍协作分集的一些基本概念、信号的时分传输方案和中继节点的信号处理方式，并在传统MIMO的基础上得出协作MIMO的系统模型，介绍几种源节点和中继节点的功率分配方法，针对不同的方法给出系统的信道容量的表达式，并从理论上推导出中继的中断概率和系统信道容量中断的判断方法。最后，以系统信道容量的中断概率为判断依据，通过软件仿真比较不同功率分配方法的系统性能，并总结出不同条件下适宜采用的功率分配方法。由仿真结果知，在小信噪比或是中继节点距离源节点较近时，协作比非协作效果好，在协作系统中，中继的反注水和最优注水系统中断概率最低；而当大信噪比或者中继距离源节点较远时，协作系统不如非协作系统，此时采用传统MIMO系统比较适宜。
最后，随着无线通信技术的发展，频谱资源变得越来越紧张，认知无线电（Cognitive Radio，CR)技术已经被公认为是提高网络频谱资源利用率问题的有效解决方法。尽管协作通信技术能够提高系统的抗衰落能力，认知无线电技术可以提高无线频谱的使用效率，但这还不足以解决无线通信中存在的上述两个问题。协作通信技术和认知无线电技术结合己经成为近年来的研究热点。两种技术结合将为同时提高系统的抗衰落性能、信道容量和频谱利用率提供一种可能的解决方案。其次，研究共存式(underlay)频谱共享模式下认知网络协作分集技术，将研究CR系统在峰值传输功率限制条件下的协作策略及性能分析。现有的对协作分集容量、中断概率及误码率(BER)等的分析主要是针对固定频谱分配情况。对共存式频谱共享环境下的认知无线电单节点协作系统性能进行了分析，并给出了基于译码转发模式的认知系统协作中断概率近似表达式，仿真结果验证了理论分析的正确性。
In a wireless communication system, the quality of transmission is affectedseriously by signal fading caused by multipath propagation, and the capacity of thesystem is limited greatly. Multi-antenna diversity technology is a kind of methodthat can confront a fading effectively, however, due to the restrictions of volume,power consumption and hardware complexity, mobile terminals of somecommunication system are difficult to configure multiple antennas. In this context,cooperative diversity technology is put forward and receives widespread attentionincreasingly.
Cooperative diversity is also called cooperative MIMO in some literature, it isa kind of new way of spatial diversity, which makes the mobile terminal with singleantenna can achieve the result of diversity by sharing each other's antenna. Due tothe distance between the mobile terminal is usually several times far greater than thewavelength, the correlations between channels are reduced greatly, which canmaximize the channel capacity. However, multi-antenna of mobile terminals is theinevitable trend of development, and there still exists collaboration problem in thewireless network of multiple antenna terminal, cooperative MIMO with multipleantenna terminal can improves the performance of the system further more. In thispaper, surrounding by the multiple antenna terminal cooperative MIMO usingdecoding retransmission way, its collaborative approach, power distribution andcooperation partner selection problem based on the cognitive are studied.
First of all, the collaboration partner selection method of multi-antennaterminal cooperative MIMO system is studied. Four classic users grouping methodsare introduced, and their performances are compared. As the performance andfeasibility of the worst link priority algorithm are both better, the specific processesof the worst link priority algorithm are futher analyzed. And on the basis of this, thechannel priority matching algorithm between users based on the worst link priorityalgorithm is studied. Thus, in this paper, the energy gain of the channel preferredmatching algorithm between users in multi-antenna terminal system are analyzed intheory, and the corresponding formulas are deduced. In the last part of the content,the performance of the channel priority matching algorithm between users inmulti-antenna terminal system is simulated, and the simulation results are analyzedconnecting with the theory. The rationality of selecting the user is analyzedcomparatively by random selection algorithm and the performance of this algorithmin a single antenna system is also simulated and analyzed in order to show its changeof properties in the multiple antenna system. In addition, it also involves the change of users in the neighborhood ang threshold of algorithm to study simulation analysisof the algorithm itself performance.
Second, the power allocation methods of multi-antenna terminal cooperativeMIMO are studied, several typical power allocation algorithms are proposed, theirprinciples are illustrated, related theoretical formulas are derived, and theperformances of different power allocation algorithm are compared through thesimulation analysis. Then, the basic concept of cooperative diversity, signaltime-division transmission scheme and the way of signal processing of relay nodeare introduced simply, and the system model of cooperative MIMO on the basis ofthe traditional MIMO, a few power allocation methods of provenance node andrelay node are introduced, the expressions of channel capacity of the system aregiven aiming at different methods, and deduced the judgment method of theinterrupt probability of relay and the interrupt of system channel capacitytheoretically. Finally, on the basis of the interrupt probability of system channelcapacity, the performance of the system channel capacity with different powerallocation methods are compared through software simulation, and suitable powerallocation methods under the different conditions are sum up. By the simulationresults, the effect of collaboration is better in in the conditions of small SNR or withthe relay node near the source node. In the collaboration system, the outageprobability of the relay of water anti-injection and the optimal water injectionsystem are lowest; and when signal-to-noise ratio is large or relay is far from thesource node, the collaboration system is inferior to the non-collaboration system, itis appropriate to use traditional MIMO system at this moment.
Finally, with the development of wireless communication technology, spectrumresource becomes more and more scarce, cognitive radio (Cognitive Radio, CR)technology has been recognized as the effective solution to increase the resourceutilization problems of networks spectrum. Although collaborative communicationtechnology can improve the antifading ability of the system and cognitive radiotechnology can improve the efficiency of the use of wireless spectrum, these are notenough to solve the two problems existing in the wireless communication which arementioned above. Collaborative communication technology and cognitive radiotechnology have become a research hot topic in recent years. Combining with twokinds of technology will provide a possible solution to improve fading resistance,channel capacity, spectral efficiency of system at the same time. Cognitive networkcooperative diversity technology at coexistence type (underlay) of spectrum sharingmode is researched, and the collaboration strategies of CR system under the peaktransmission power constraints is analyzed on its performance. The existing analysisof cooperative diversity capacity, interrupt probability and bit error rate (BER) aremainly aiming at fixed spectrum allocation. The performance of cognitive radio single node collaboration system is analyzed under the environment of coexistencetype spectrum sharing, and the approximate expressions of interruption probabilityof cognitive system cooperative based on the pattern of decode forward is obtained,the simulation results verify the correctness of theoretical analysis.
协作分集在一些文献中也称为协作式MIMO，是一种新的空域分集方式，使具有单天线的移动终端通过共享彼此的天线也可以获得分集的效果。由于移动终端间的距离通常远远大于数倍的波长，信道间的相关性大大降低，从而可以使信道容量最大化。然而，移动终端的多天线化是发展的必然趋势，在多天线终端的无线网络中仍然存在协作问题，具有多天线终端的协作式MIMO可以使系统性能得到进一步的提升。本文围绕采用解码转发方式的多天线终端协作式MIMO，研究了中继选择、功率分配和协作方法等问题。
首先，对多天线终端协作式MIMO系统的中继选择方法进行了研究。对四种经典的用户分组方法进行了介绍，并对其性能进行了比较。鉴于最差链路优先算法在性能上和可行性上都较好，本文接下来对最差链路优先算法的具体过程进行了分析。并在此基础上研究了基于最差链路优先算法的用户间信道优先匹配算法。进而，本文对用户间信道优先匹配算法在多天线终端系统中的能量增益进行了理论分析，并推导了相应公式。最后一部分内容对用户间信道优先匹配算法在多天线终端系统中的性能进行了仿真，并结合理论对仿真结果进行了分析。其间用随机选择算法对比分析了其选择用户的合理性；为显现出其在多天线系统中特性的变化，在这将该算法在单天线系统中的性能也做了仿真分析。另外，还涉及改变小区内用户数和算法门限以研究算法本身性能的仿真分析。
其次，对多天线终端协作式MIMO的功率分配方法进行了研究，提出了几种典型的功率分配算法，阐述它们的原理，推导相关的理论公式，通过仿真分析比较不同功率分配算法的性能。然后，简单介绍协作分集的一些基本概念、信号的时分传输方案和中继节点的信号处理方式，并在传统MIMO的基础上得出协作MIMO的系统模型，介绍几种源节点和中继节点的功率分配方法，针对不同的方法给出系统的信道容量的表达式，并从理论上推导出中继的中断概率和系统信道容量中断的判断方法。最后，以系统信道容量的中断概率为判断依据，通过软件仿真比较不同功率分配方法的系统性能，并总结出不同条件下适宜采用的功率分配方法。由仿真结果知，在小信噪比或是中继节点距离源节点较近时，协作比非协作效果好，在协作系统中，中继的反注水和最优注水系统中断概率最低；而当大信噪比或者中继距离源节点较远时，协作系统不如非协作系统，此时采用传统MIMO系统比较适宜。
最后，随着无线通信技术的发展，频谱资源变得越来越紧张，认知无线电（Cognitive Radio，CR)技术已经被公认为是提高网络频谱资源利用率问题的有效解决方法。尽管协作通信技术能够提高系统的抗衰落能力，认知无线电技术可以提高无线频谱的使用效率，但这还不足以解决无线通信中存在的上述两个问题。协作通信技术和认知无线电技术结合己经成为近年来的研究热点。两种技术结合将为同时提高系统的抗衰落性能、信道容量和频谱利用率提供一种可能的解决方案。其次，研究共存式(underlay)频谱共享模式下认知网络协作分集技术，将研究CR系统在峰值传输功率限制条件下的协作策略及性能分析。现有的对协作分集容量、中断概率及误码率(BER)等的分析主要是针对固定频谱分配情况。对共存式频谱共享环境下的认知无线电单节点协作系统性能进行了分析，并给出了基于译码转发模式的认知系统协作中断概率近似表达式，仿真结果验证了理论分析的正确性。
In a wireless communication system, the quality of transmission is affectedseriously by signal fading caused by multipath propagation, and the capacity of thesystem is limited greatly. Multi-antenna diversity technology is a kind of methodthat can confront a fading effectively, however, due to the restrictions of volume,power consumption and hardware complexity, mobile terminals of somecommunication system are difficult to configure multiple antennas. In this context,cooperative diversity technology is put forward and receives widespread attentionincreasingly.
Cooperative diversity is also called cooperative MIMO in some literature, it isa kind of new way of spatial diversity, which makes the mobile terminal with singleantenna can achieve the result of diversity by sharing each other's antenna. Due tothe distance between the mobile terminal is usually several times far greater than thewavelength, the correlations between channels are reduced greatly, which canmaximize the channel capacity. However, multi-antenna of mobile terminals is theinevitable trend of development, and there still exists collaboration problem in thewireless network of multiple antenna terminal, cooperative MIMO with multipleantenna terminal can improves the performance of the system further more. In thispaper, surrounding by the multiple antenna terminal cooperative MIMO usingdecoding retransmission way, its collaborative approach, power distribution andcooperation partner selection problem based on the cognitive are studied.
First of all, the collaboration partner selection method of multi-antennaterminal cooperative MIMO system is studied. Four classic users grouping methodsare introduced, and their performances are compared. As the performance andfeasibility of the worst link priority algorithm are both better, the specific processesof the worst link priority algorithm are futher analyzed. And on the basis of this, thechannel priority matching algorithm between users based on the worst link priorityalgorithm is studied. Thus, in this paper, the energy gain of the channel preferredmatching algorithm between users in multi-antenna terminal system are analyzed intheory, and the corresponding formulas are deduced. In the last part of the content,the performance of the channel priority matching algorithm between users inmulti-antenna terminal system is simulated, and the simulation results are analyzedconnecting with the theory. The rationality of selecting the user is analyzedcomparatively by random selection algorithm and the performance of this algorithmin a single antenna system is also simulated and analyzed in order to show its changeof properties in the multiple antenna system. In addition, it also involves the change of users in the neighborhood ang threshold of algorithm to study simulation analysisof the algorithm itself performance.
Second, the power allocation methods of multi-antenna terminal cooperativeMIMO are studied, several typical power allocation algorithms are proposed, theirprinciples are illustrated, related theoretical formulas are derived, and theperformances of different power allocation algorithm are compared through thesimulation analysis. Then, the basic concept of cooperative diversity, signaltime-division transmission scheme and the way of signal processing of relay nodeare introduced simply, and the system model of cooperative MIMO on the basis ofthe traditional MIMO, a few power allocation methods of provenance node andrelay node are introduced, the expressions of channel capacity of the system aregiven aiming at different methods, and deduced the judgment method of theinterrupt probability of relay and the interrupt of system channel capacitytheoretically. Finally, on the basis of the interrupt probability of system channelcapacity, the performance of the system channel capacity with different powerallocation methods are compared through software simulation, and suitable powerallocation methods under the different conditions are sum up. By the simulationresults, the effect of collaboration is better in in the conditions of small SNR or withthe relay node near the source node. In the collaboration system, the outageprobability of the relay of water anti-injection and the optimal water injectionsystem are lowest; and when signal-to-noise ratio is large or relay is far from thesource node, the collaboration system is inferior to the non-collaboration system, itis appropriate to use traditional MIMO system at this moment.
Finally, with the development of wireless communication technology, spectrumresource becomes more and more scarce, cognitive radio (Cognitive Radio, CR)technology has been recognized as the effective solution to increase the resourceutilization problems of networks spectrum. Although collaborative communicationtechnology can improve the antifading ability of the system and cognitive radiotechnology can improve the efficiency of the use of wireless spectrum, these are notenough to solve the two problems existing in the wireless communication which arementioned above. Collaborative communication technology and cognitive radiotechnology have become a research hot topic in recent years. Combining with twokinds of technology will provide a possible solution to improve fading resistance,channel capacity, spectral efficiency of system at the same time. Cognitive networkcooperative diversity technology at coexistence type (underlay) of spectrum sharingmode is researched, and the collaboration strategies of CR system under the peaktransmission power constraints is analyzed on its performance. The existing analysisof cooperative diversity capacity, interrupt probability and bit error rate (BER) aremainly aiming at fixed spectrum allocation. The performance of cognitive radio single node collaboration system is analyzed under the environment of coexistencetype spectrum sharing, and the approximate expressions of interruption probabilityof cognitive system cooperative based on the pattern of decode forward is obtained,the simulation results verify the correctness of theoretical analysis.
引文
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