MIMO系统中随机波束形成与自适应调度技术研究
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摘要
移动通信的发展对通信速率和服务质量(QoS)提出了更高的要求。具有高频谱利用率和高性能的通信技术是下一代移动通信系统重要的研究目标之一。多输入多输出(MIMO)技术在不额外增加功率和带宽的条件下成倍增加传输速率和大幅改善链路,能够有效解决频谱资源紧张,并提供高速业务支持,已成为下一代移动通信系统中的一项关键技术。已有的研究大多关注MIMO系统中的点对点传输,而对多用户MIMO系统尤其是多用户分集增益的研究最近几年才成为热点。本文正是在这样的背景下,研究了多用户MIMO系统下行广播信道的自适应传输策略和多用户调度机制两方面的内容
污纸编码虽然已被证明可以实现MIMO下行广播信道的容量域,但它并不能在实际的系统中应用。已有的研究表明正交随机波束形成技术利用部分信道信息反馈和多用户调度,在用户数很多时与污纸编码具有相同的渐进形式,但当用户数较少时,该算法的性能损失严重。正交随机波束形成算法虽然利用多个波束同时与多个用户进行数据传输,获得了空间复用增益,提高了系统和容量性能,但每个波束在传输数据时,都会对其他波束形成干扰,尤其在高信噪比条件下,系统为“干扰受限”。本文首先从理论推导和数值仿真两方面分析了最优波束数目与系统平均信噪比和用户数之间的关系,提出了一种利用部分用户反馈的附加信道信息,通过用户排序进行波束选择和多用户调度的方法。该方法为每个时隙动态选择部分最优波束进行传输,减少波束间干扰,提高系统容量,同时用户排序的调度方法避免了对波束和用户的遍历搜索,大大降低了算法复杂度。本文还给出了一种结合查找表的波束选择和多用户调度算法,仿真结果表明本文提出的算法可达到的容量性能略低于遍历搜索算法,但算法复杂度更低。
正交随机波束形成算法中使用的权重矩阵是在每个时隙内随机生成的,权重矩阵与用户信道矩阵是否匹配将影响到系统和容量性能,因此在每个时隙内选择与信道矩阵最匹配的权重矩阵成为一个新的自由度。Kountouris和Wan的研究证明了多权重矩阵选择方法的有效性。但在他们的算法中需要对信道进行多次测量和反馈,算法实现过程复杂而且反馈量大,为了减少训练时隙个数,将更多的时间用于用户数据传输,提高频谱效率,本文给出了一种仅需要一个训练时隙的多权重矩阵选择方法。该方法中用户仅需要对信道进行一次测量,就可以利用酉矩阵的旋转处理构造多个虚拟的等效信道,通过对等效信道的测量和反馈,基站从构造等效信道的多个酉矩阵中选择最优者进行数据预处理和发射。本文提出的算法仅利用一个训练时隙也可以获得多权重矩阵选择增益。
对MIMO下行系统的多用户调度研究大多以提高系统和容量为目标,没有考虑用户间的公平性,当系统内的多个用户所经历的信道变化相似时,比例公平调度算法在提高系统和容量和公平性之间获得了较好的折中,但它没有考虑系统内异质用户的公平性保障。本文首先定义了一个新的参数,利用请求速率的实时信息和统计信息来描述用户信道质量变化的动态过程。然后给出了两种自适应的比例公平调度算法。当用户信道质量逐渐变差时,本文提出的算法可以给予该用户更多的服务机会,保障其服务质量。
The development of the wireless communication system has the growing demand of the transmission rates and the guaranteed Quality-of-Service(QoS).The MIMO technique can multiple the transmission rate and improve the quality of the data link,and no additional power and spectrum resource are needed.It can also supply the high-speed data service.MIMO technique has become one of the key technologies in the next generation communication systems.Most of former researches focused on the point-to-point transmission.The research on multiuser MIMO systems,especially the multiuser diversity gain drew more and more interest in recent years.Our research work concentrates on the adaptive transmission strategy and multi-user scheduling mechanism of the broadcast downlink channel of the multiuser MIMO systems.
Although the Dirty Paper Coding(DPC) has been proved to be the optimal strategy to achieve the capacity region of the MIMO downlink broadcast channel,it can't be applied in practical systems.The former studies have shown that by scheduling the multiple users with the feedback of part channel status information,orthogonal random beam-forming technology can achieve the same scaling law with the DPC scheme when the user number in the system is large enough.But if the user number is limited,the performance of the algorithm has suffered serious losses.By using multiple beams to communicate with multiple users simultaneously,ORBF scheme achieves spatial multiplexing gain and improves the system capacity.However,during data-transmitting over each beam,it will interfere with other beams,especially in high Signal-to-Noise-Ratio(SNR) condition,and the system is "interference limited".In this paper,we firstly analyze the optimal beam number in different conditions of various user number and various system average SNR by the theoretical analysis and numerical simulation.And then we propose a strategy of beam selection and multi-user scheduling by user-sorting and using the additional feedback of channel status information of part users.In each slot,the proposed strategy dynamically selects some of the optimal beams for data transmission.It can improve the system capacity by reducing the inter-beam interference.And besides that,the scheduling method by user-sorting avoids the traversal search of beams and users,greatly reducing the complexity of the algorithm.This paper also gives a novel beam selection and multiuser scheduling algorithm combined with lookup tables.The simulation results show that the capacity of the proposed algorithm is slightly less than the traversal search algorithms,but the complexity of the proposed algorithm is much lower.
The weight matrixes used in ORBF are randomly generated in each time slot, whether the weight matrixes match the users' channel matrixes will limit the system performance of the sum rate,so choosing the best-matched weight matrix becomes a new issue.Koutouris and wan's research has proved that choosing the best-matched weight matrix for each time slot is efficient for improving the systems' sum rate.However,their algorithms require each user to investigate the channel and feedback the CSI many times, which leads to a complex process of implementation and too much feedback.We propose a novel method which needs only one training slot to choose the best-matched one from multiple weight matrixes,the proposed method can reduce the number of training slots and give more time for data transmission and improve the spectrum efficiency.In our method users need evaluate the channel status only once,they can use the rotation of unitary matrix to construct several virtual equivalent channels.Through the measurement and feedback the part CSI of the equivalent channels,the base station choose the best one from the unitary matrixes which construct the equivalent channel,and then the data is multiplied with the selected matrixes and transmitted.Our method can get the multi-matrix diversity gain by using only one training slot.
A majority of the researches on multiuser scheduling of the downlink channel of MIMO system focus on improving the sum rate performance of the system,but ignore the fairness over all users.Proportional Fairness Schedule(PFS) gets a tradeoff between the system capacity and fairness when the users in the system experience the homogeneous channel conditions and the fading of the channel varies rapidly.However it ignores the fairness between the users in different conditions.In this paper,we denote a new parameter to describe the dynamic behavior of each user's channel condition.The parameter uses the request rate of the present time slot and the statistical information of the request rate.Two adaptive PFS algorithms with the new parameter are proposed.They can offer more chance to the users who is falling into the bad channel conditions and guarantee their quality of service.
污纸编码虽然已被证明可以实现MIMO下行广播信道的容量域,但它并不能在实际的系统中应用。已有的研究表明正交随机波束形成技术利用部分信道信息反馈和多用户调度,在用户数很多时与污纸编码具有相同的渐进形式,但当用户数较少时,该算法的性能损失严重。正交随机波束形成算法虽然利用多个波束同时与多个用户进行数据传输,获得了空间复用增益,提高了系统和容量性能,但每个波束在传输数据时,都会对其他波束形成干扰,尤其在高信噪比条件下,系统为“干扰受限”。本文首先从理论推导和数值仿真两方面分析了最优波束数目与系统平均信噪比和用户数之间的关系,提出了一种利用部分用户反馈的附加信道信息,通过用户排序进行波束选择和多用户调度的方法。该方法为每个时隙动态选择部分最优波束进行传输,减少波束间干扰,提高系统容量,同时用户排序的调度方法避免了对波束和用户的遍历搜索,大大降低了算法复杂度。本文还给出了一种结合查找表的波束选择和多用户调度算法,仿真结果表明本文提出的算法可达到的容量性能略低于遍历搜索算法,但算法复杂度更低。
正交随机波束形成算法中使用的权重矩阵是在每个时隙内随机生成的,权重矩阵与用户信道矩阵是否匹配将影响到系统和容量性能,因此在每个时隙内选择与信道矩阵最匹配的权重矩阵成为一个新的自由度。Kountouris和Wan的研究证明了多权重矩阵选择方法的有效性。但在他们的算法中需要对信道进行多次测量和反馈,算法实现过程复杂而且反馈量大,为了减少训练时隙个数,将更多的时间用于用户数据传输,提高频谱效率,本文给出了一种仅需要一个训练时隙的多权重矩阵选择方法。该方法中用户仅需要对信道进行一次测量,就可以利用酉矩阵的旋转处理构造多个虚拟的等效信道,通过对等效信道的测量和反馈,基站从构造等效信道的多个酉矩阵中选择最优者进行数据预处理和发射。本文提出的算法仅利用一个训练时隙也可以获得多权重矩阵选择增益。
对MIMO下行系统的多用户调度研究大多以提高系统和容量为目标,没有考虑用户间的公平性,当系统内的多个用户所经历的信道变化相似时,比例公平调度算法在提高系统和容量和公平性之间获得了较好的折中,但它没有考虑系统内异质用户的公平性保障。本文首先定义了一个新的参数,利用请求速率的实时信息和统计信息来描述用户信道质量变化的动态过程。然后给出了两种自适应的比例公平调度算法。当用户信道质量逐渐变差时,本文提出的算法可以给予该用户更多的服务机会,保障其服务质量。
The development of the wireless communication system has the growing demand of the transmission rates and the guaranteed Quality-of-Service(QoS).The MIMO technique can multiple the transmission rate and improve the quality of the data link,and no additional power and spectrum resource are needed.It can also supply the high-speed data service.MIMO technique has become one of the key technologies in the next generation communication systems.Most of former researches focused on the point-to-point transmission.The research on multiuser MIMO systems,especially the multiuser diversity gain drew more and more interest in recent years.Our research work concentrates on the adaptive transmission strategy and multi-user scheduling mechanism of the broadcast downlink channel of the multiuser MIMO systems.
Although the Dirty Paper Coding(DPC) has been proved to be the optimal strategy to achieve the capacity region of the MIMO downlink broadcast channel,it can't be applied in practical systems.The former studies have shown that by scheduling the multiple users with the feedback of part channel status information,orthogonal random beam-forming technology can achieve the same scaling law with the DPC scheme when the user number in the system is large enough.But if the user number is limited,the performance of the algorithm has suffered serious losses.By using multiple beams to communicate with multiple users simultaneously,ORBF scheme achieves spatial multiplexing gain and improves the system capacity.However,during data-transmitting over each beam,it will interfere with other beams,especially in high Signal-to-Noise-Ratio(SNR) condition,and the system is "interference limited".In this paper,we firstly analyze the optimal beam number in different conditions of various user number and various system average SNR by the theoretical analysis and numerical simulation.And then we propose a strategy of beam selection and multi-user scheduling by user-sorting and using the additional feedback of channel status information of part users.In each slot,the proposed strategy dynamically selects some of the optimal beams for data transmission.It can improve the system capacity by reducing the inter-beam interference.And besides that,the scheduling method by user-sorting avoids the traversal search of beams and users,greatly reducing the complexity of the algorithm.This paper also gives a novel beam selection and multiuser scheduling algorithm combined with lookup tables.The simulation results show that the capacity of the proposed algorithm is slightly less than the traversal search algorithms,but the complexity of the proposed algorithm is much lower.
The weight matrixes used in ORBF are randomly generated in each time slot, whether the weight matrixes match the users' channel matrixes will limit the system performance of the sum rate,so choosing the best-matched weight matrix becomes a new issue.Koutouris and wan's research has proved that choosing the best-matched weight matrix for each time slot is efficient for improving the systems' sum rate.However,their algorithms require each user to investigate the channel and feedback the CSI many times, which leads to a complex process of implementation and too much feedback.We propose a novel method which needs only one training slot to choose the best-matched one from multiple weight matrixes,the proposed method can reduce the number of training slots and give more time for data transmission and improve the spectrum efficiency.In our method users need evaluate the channel status only once,they can use the rotation of unitary matrix to construct several virtual equivalent channels.Through the measurement and feedback the part CSI of the equivalent channels,the base station choose the best one from the unitary matrixes which construct the equivalent channel,and then the data is multiplied with the selected matrixes and transmitted.Our method can get the multi-matrix diversity gain by using only one training slot.
A majority of the researches on multiuser scheduling of the downlink channel of MIMO system focus on improving the sum rate performance of the system,but ignore the fairness over all users.Proportional Fairness Schedule(PFS) gets a tradeoff between the system capacity and fairness when the users in the system experience the homogeneous channel conditions and the fading of the channel varies rapidly.However it ignores the fairness between the users in different conditions.In this paper,we denote a new parameter to describe the dynamic behavior of each user's channel condition.The parameter uses the request rate of the present time slot and the statistical information of the request rate.Two adaptive PFS algorithms with the new parameter are proposed.They can offer more chance to the users who is falling into the bad channel conditions and guarantee their quality of service.
引文
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