【作者】 陈凯；

【导师】 乐光新； 刘丹谱；

【作者基本信息】 北京邮电大学 ， 通信与信息系统， 2010， 博士

【摘要】 多发送多接收天线(MIMO)是无线通信领域的重大技术突破,它能在不增加带宽的情况下成倍地提高通信系统的频谱利用率和信道容量,是下一代移动通信系统的关键技术之一。协作中继通信技术作为MIMO走向实用化的重要途径,融合了分集方案与中继传输的技术优势,引起了业界的广泛关注。本文以实现协作中继通信技术在无线通信网络中的应用为目标,主要从分布式多源协作中继通信网络的中继选择与性能分析、基于正交频分多址接入(OFDMA)的协作中继蜂窝系统的联合资源优化和认知无线电系统中的协作频谱共享这3个角度对协作中继通信技术进行了研究与分析。具体内容包括：1、中继选择是协作中继通信网络中的一个重要问题。针对无中心控制节点,且各节点能量受限、能力有限的分布式多源协作中继通信网络,本文提出了一种主动中继选择策略(M-PRS),分析了M-PRS的高信噪比中断概率,并从中断概率、分集复用折衷(DMT)和实现开销及复杂度这几个方面,将M-PRS分别与一种被动中继选择策略(M-RRS)和一种分布式空时编码策略(M-DSTC)进行了比较。研究结果表明,M-PRS是一种适用的协作中继传输策略,它可以在中断概率性能仅有较小损失的情况下,‘有效降低网络的实现开销。2、在基于OFDMA的协作中继蜂窝系统中,如何在特定的系统目标下,以最优的方式使用系统的各种有限资源,是当前研究的热点问题之一。本文以最大化加权和速率(WSR)为系统优化目标,基于优化理论,提出了一种最优资源分配算法,该算法可以实现子载波分配、功率分配、中继选择和传输模式选择的联合优化。与其他基于优化理论提出的最优资源分配算法相比,该算法能够实现不依赖于系统参数的稳定收敛,从而保证了算法执行的稳定性,并可因此降低算法的复杂度。本文还分析了该算法在不同中继处理方式(包括解码转发(DF)和放大转发(AF))下的实现和性能。通过理论分析和计算机仿真实验,本文闸明了选择加权和速率作为系统优化目标的合理性,即既可以灵活地实现多种不同的系统公平性,又可以降低最优资源分配算法的计算复杂度,同时也验证了该算法在充分利用中继节点能力提高系统容量方面的性能优势。3、下一代的无线通信系统必须具备保证用户最低服务质量要求(QoS)的能力,同时在某些场合,系统可能还会对用户公平性提出较高要求。在这样的背景下,针对基于OFDMA的协作中继蜂窝系统,本文提出了一种可以保证用户最低QoS要求的公平资源分配问题,该问题同样包含了子载波分配、功率分配、中继选择和传输模式选择的联合优化。鉴于该问题最优求解方法的高复杂度,本文提出了一种基于等功率分配的次优求解算法。由于必须保证用户的最低QoS要求,因此该问题不一定有可行解,考虑到算法的完整性和实用性,本文还在该算法中引入了呼叫接纳控制(CAC)机制,并讨论了3种呼叫接纳控制策略。理论分析和仿真结果表明,该算法可以在大幅降低计算复杂度的前提下,获得接近于等功率分配时最优搜索算法的性能,同时该算法还能实现系统效率和用户公平性之间的有效折衷。4、认知无线电(CR)技术作为缓解频谱资源匮乏、提高频谱利用效率的一种有效途径,正受到越来越广泛的关注。由于认知无线电系统也会受到多径衰落的影响,因此将协作中继通信技术应用到认知无线电系统之中是非常必要的。基于频谱共享的所有权模型,本文研究了授权用户在有服务质量要求的情况下,与认知用户进行协作频谱共享的方法。通过假设授权用户可以将它的部分信道使用时间租借给认知用户使用,以便在直传信道条件不佳时,换取认知用户的协作中继传输,满足并改善服务质量,本文建立了一种授权用户和认知用户之间基于选择式合作博弈框架的协作频谱共享模型,研究了该模型的求解方法,并提出了一种低复杂度的分布式实现策略。理论分析和仿真结果表明,该策略既可以大幅降低授权用户的业务中断概率,保证授权用户的服务质量,并提高它的传输能力,又可以使认知用户获得传输数据的机会,因而能够实现授权用户与认知用户之间的双赢。更多还原

【Abstract】 Multiple Input and Multiple Output (MIMO) is a breakthrough in the wireless communication field. It is a key technology which might be adopted by the next generation mobile communication systems, because it can greatly improve the spectrum utilization and channel capacity without increasing the bandwidth.As a practical measure of MIMO, cooperative relaying communication has attracted much attention due to its ability to explore the inherent spatial diversity in relay channels. Aiming at applying cooperative relaying communication technologies in the wireless communication networks, this dissertation has studied and analyzed cooperative relaying communication technologies from three aspects:relay selection strategies in distributed cooperative relaying communication networks and their performance analysis, joint resource optimization in Orthogonal Frequency Division Multiple Access (OFDMA) based cooperative relaying cellular networks and cooperative spectrum sharing in cognitive radio systems.The major contributions are outlined as follows.1.How to select relays from all potential relays to aid the transmission of the source is an important problem in cooperative relaying communication networks.For distributed multi-source cooperative relaying communication networks without a central control unit and with limitation on energy and capacity for each node, a proactive relay selection strategy (M-PRS) is proposed, and its high signal-to-noise ratio(SNR) outage probability is analyzed.Then it is compared with a reactive relay selection strategy (M-RRS) and a distributed space-time coding strategy (M-DSTC) in outage probability, diversity-multiplexing tradeoff (DMT) and implementation overhead and complexity. The theoretical analysis and computer simulations show that M-PRS is an appropriate cooperative relaying transmission strategy which is able to effectively lower the network implementation overhead with only a small performance loss in the outage probability.2.In OFDMA based cooperative relaying cellular systems, how to optimally allocate all kinds of limited resource under a specific system goal is one of the key problems which are under extensive investigation. By taking the weighted sum rate (WSR) as the system optimization goal, an optimal resource allocation algorithm based on optimization theory is proposed.The algorithm can jointly optimize subcarrier allocation, power allocation, relay selection and transmission mode selection. Compared with other optimal resource allocation algorithms which are also based on optimization theory, our algorithm is able to achieve stable convergence independent of system parameters which lowers its computational complexity accordingly in the long run. The implementation and performance of the algorithm under different relay strategies (including decode-and-forward (DF) and amplify-and-forward (AF)) are also discussed. Theoretical analysis and computer simulations illustrate that choosing the weighted sum rate as the system optimization goal is rational, because it is able to both simplify the implementation of different fairness criterions and reduce the computational complexity of the algorithm. We also validate that the algorithm has advantages in fully utilizing the capabilities of relays to improve the system capacity.3.The next generation wireless communication system should have the capability to guarantee users’lowest quality of service (QoS), and in some scenarios, the system should also have the capacity to guarantee fairness among users.Taking these notions into consideration, for OFDMA-based cooperative relaying cellular systems, a fair resource allocation problem that is able to guarantee users’lowest QoS is proposed. The problem also includes the joint optimization of subcarrier allocation, power allocation, relay selection and transmission mode selection. Due to the high complexity involved in optimally solving the problem, a suboptimal algorithm based on equal power allocation is developed. To make sure that there is a feasible solution to the problem, and the algorithm is integral and practical, call admission control (CAC) mechanisms are introduced and three CAC strategies are discussed. Research results indicate that our algorithm obtains a performance close to the optimal exhaustive search when equal power allocation is applied with a much lower computational complexity, and achieves an effective tradeoff between system efficiency and fairness among users.4.As a promising technology to deal with the scarcity of spectrum resource and improve the spectrum utilization, cognitive radio (CR) has attracted more attention in recent years.It is necessary to apply cooperative communication technologies into CR systems because they also suffer adverse impacts from multipath fading. Based on the property-right model of spectrum sharing, the strategy by which a primary user (PU) with QoS requirement shares its spectrum with secondary users (SUs) in a cooperative way is studied. By assuming the PU is able to lease some of its channel usage time to the SU in order to exchange the cooperative transmission of the SU and improve its QoS when it does not have a good direct link, a spectrum leasing model based on selective cooperation and cooperative game framework is proposed.The solution to this model is discussed and a distributed implementation strategy with low complexity and overhead is developed. Theoretical analysis and computer simulations show that our strategy can greatly reduce PU’s service outage probability, and hence guarantee its QoS and improve its transmission capability. At the same time, the strategy makes it possible for the SU to acquire transmission opportunities. Therefore, the strategy is able to produce a win-win outcome for both the PU and the SU.更多还原