【作者】 安宁；

【导师】 薛其坤；

【作者基本信息】 北京邮电大学 ， 电子科学与技术， 2019， 硕士

【摘要】 现阶段,各国对5G移动通信网络技术的探索与建设正在火速进行。第四代移动通信系统为用户带来了多样化的业务服务,尤其是移动端的多媒体以及在线视频等数据量需求较大的业务。然而,随着未来终端数量的不断倍增,用户对移动场景的无缝覆盖服务需求越来越大,给5G网络提出了新要求:(1)能够实现更高的数据传输速率、更大的网络容量、更少的能耗和更小的时延。(2)在较差的信道状态环境下可以提供无缝覆盖服务,尤其是一些特殊场景如高速移动场景。因此,如何在移动场景下追求较大的系统容量、较少能量的消耗的同时,可以准确的、延迟小的、高效的为用户提供可靠的信息传输,成为第五代无线通信的移动场景下的研究热点。本文主要针对移动场景下的可靠性传输和最小化时延进行波束成型设计和功率资源和计算资源的分配。本文的第三章提出了一种基于集中式大规模MIMO双时隙协作多天线车车通信传输场景,研究目标是在列车发送功率满足限制条件的情况下实现车车通信总速率的最优。通过自适应的调整每个时隙的波束成型设计不断地迭代优化系统总速率。本文的第四章研究了分布式多天线车车通信传输系统的优化问题。不同于第三章,第四章考虑了轨旁基站的回程链路能量消耗限制,研究目标是最大化系统传输总速率与功率消耗的差值,最后求解了两个时隙的分布式基站的波束成型矩阵。不同于高速行车场景,第五章研究了移动D2D用户的视频解码任务,在保证用户QoS的同时最小化系统能耗。在求解问题的过程中,通过寻找非凸的目标函数与限制条件的替代函数,将问题模型转化为凸优化问题,最后用凸优化工具计算了D2D用户的功率与计算资源。本文结合了5G通信的愿景,分析和研究了移动场景下资源分配策略,并对算法进行了分析与验证,通过使用MATLAB工具证明了所提出算法的合理性和有效性。更多还原

【Abstract】 At this stage,the exploration and construction of 5G mobile communication network technologies are rapidly progressing.The fourth-generation mobile communication system brings a variety of business services to users,especially mobile multimedia and online games,which require a large amount of data.However,with the continuous increase of the number of terminals in the future,users have more and more demand for seamless coverage services for mobile scenes,and put forward new requirements for 5G networks:(1)capable of achieving higher data transmission rates and larger networks.Capacity,less energy consumption and less time delay.(2)Provides seamless coverage services in poor channel state environments,especially for special scenarios such as high-speed mobile scenarios.Therefore,how to achieve a larger system capacity and less energy consumption in a mobile scenario,while providing accurate,slow,and efficient information transmission for users,becomes a fifth-generation wireless communication mobile scene.Research hotspots.This paper focuses on beamforming design and allocation of power resources and computing resources for reliability transmission and minimized delay in mobile scenarios.The third chapter of this paper proposes a centralized large-scale MIMO dual-slot cooperative multi-antenna vehicle communication transmission scenario.The research goal is to achieve the optimal total vehicle-to-vehicle communication speed when the train transmission power meets the constraints.The total system rate is continually iteratively optimized by adaptively adjusting the beamforming design of each time slot.The fourth chapter of this paper studies the optimization problem of distributed multi-antenna vehicle communication transmission system.Different from the third chapter,the fourth chapter considers the energy consumption limit of the backhaul link of the trackside base station.The research goal is to maximize the difference between the total transmission rate and the power consumption of the system.Finally,the distributed base station of the two time slots is solved.Beamforming matrix.Different from the high-speed driving scenario,the fifth chapter studies the video decoding task of mobile D2D users,which minimizes system energy consumption while ensuring user QoS.In the process of solving the problem,the problem model is transformed into a convex optimization problem by looking for the non-convex objective function and the substitution function of the constraint condition.Finally,the power and computation resources of the D2D user are calculated by the convex optimization tool.This paper combines the vision of 5G communication,analyzes and studies the resource allocation strategy in mobile scene,and analyzes and verifies the algorithm.The rationality and effectiveness of the proposed algorithm are proved by using MATLAB tools.This paper analyzes and studies the resource management algorithm in mobile scene,and analyzes and verifies the algorithm.The rationality and effectiveness of the proposed algorithm are proved by using MATLAB tools.更多还原