嵌入D2D的蜂窝网络中基于功率效率的功率控制研究

发布时间：2018-04-14 01:02

本文选题：D2D通信 + 功率控制　；参考：《西安电子科技大学》2014年硕士论文

【摘要】：新一代蜂窝移动通信系统正向更广的覆盖范围、更大的资源利用率、更高的系统容量以及绿色节能的目标发展。然而,蜂窝移动通信可用的频谱资源十分有限,如何在有限的频谱资源条件下实现上述发展目标成为业界的研究重点。业界主张将D2D通信技术引入到蜂窝网络中,旨在增加系统的频谱利用率、提升系统容量、减轻基站负荷、降低设备功耗等。本文主要对嵌入D2D通信技术的蜂窝网络中基于功率效率的功率控制开展了一系列探索性研究。首先,针对基于非协作博弈迭代算法在求解时仅最大化每个终端所能达到的功率效率,而并没有顾及整体的优化目标这一不足,提出一种基于SINR增量迭代的求解算法。该算法的基本思想是:采用分步迭代的方式,在每次迭代过程中增加D2D通信接收端的SINR或者增加蜂窝通信接收端的SINR,或者同时增加D2D通信接收端与蜂窝通信接收端的SINR,使得优化模型的效用函数得到提高;而选择增加哪类设备的SINR则取决于增加该设备的SINR所带来的收益情况,我们用前后两次迭代中效用函数的增加量来代表收益,收益越大,则增加其SINR。该算法是一种基于部分遍历的做法,通过有选择性的增加设备的SINR使得遍历过程朝着效用函数逐渐增大的方向前进,该算法不依赖于特定的效用函数,具有普适性,可作为在有限时间复杂度内的次优解求解方案。然后,重点研究了基于综合功率效率最大化的功率控制策略。针对现有研究中基于用户总功率效率最大化的功率控制策略并不能很好的反映每个用户真实的功率效率情况,我们首先提出一种基于最低用户功率效率最大化的功率控制策略,可保证系统中每个通信终端的功率效率都不至于太低,这对于电池供电的终端而言,可在续航能力受限的条件下提高终端进行数据交互的能力。其次,我们将以最大化系统功率效率为目标的功率分配由全网优化退化为在D2D基本单元内进行。最后,提出一种基于综合功率效率最大化的功率控制策略,即构建一个可同时反映用户功率效率和系统功率效率的目标函数,并采用基于SINR增量迭代的求解算法进行求解。该策略兼顾了用户的功率效率以及系统功率效率,在这两个方面都可以取得较好的性能,且对这两个方面的趋近程度可根据一个比例因子来调整,是一种可动态适应不同系统需求的方案。最后,通过一系列的仿真实验证明我们所提出的求解算法和功率控制策略是合理且有效的。
[Abstract]:The new generation of cellular mobile communication systems are moving towards the goal of wider coverage, greater resource utilization, higher system capacity and green energy conservation.However, the spectrum resources available for cellular mobile communications are very limited. How to achieve the above development goals under the limited spectrum resources has become the research focus of the industry.The industry advocates to introduce D2D communication technology into cellular networks in order to increase the spectrum efficiency of the system, enhance the system capacity, reduce the base station load, and reduce the power consumption of the equipment.In this paper, a series of exploratory research on power control based on power efficiency in cellular networks embedded in D2D communication technology is carried out.Firstly, a new iterative algorithm based on SINR incremental iteration is proposed to solve the problem, which only maximizes the power efficiency of each terminal and does not take into account the overall optimization goal.The basic idea of the algorithm is to adopt the method of step by step iteration.The utility function of the optimization model is improved by adding the SINR of the D2D communication receiver or the SINR of the cellular communication receiver or the SINR of the D2D communication receiver and the cellular communication receiver simultaneously during each iteration.However, the SINR of which kind of equipment is added depends on the profit brought by increasing the SINR of the device. We use the increase of utility function in the two iterations to represent the income, and the larger the income, the more the sinr.The algorithm is based on partial ergodic. By adding the SINR of the equipment selectively, the traversal process moves towards the direction of increasing the utility function gradually. The algorithm is not dependent on the specific utility function, so it is universal.It can be used as a suboptimal solution in finite time complexity.Then, the power control strategy based on the maximization of integrated power efficiency is studied.In view of the fact that the current power control strategy based on maximizing the total power efficiency of users can not well reflect the actual power efficiency of each user, we first propose a power control strategy based on maximizing the power efficiency of the lowest user.It can ensure that the power efficiency of each communication terminal in the system is not too low, which can improve the terminal's ability of data exchange under the condition of limited battery power supply.Secondly, the power allocation with the goal of maximizing the power efficiency of the system is reduced from the whole network optimization to the D2D basic unit.Finally, a power control strategy based on the maximization of comprehensive power efficiency is proposed, which is to construct an objective function that can reflect both user power efficiency and system power efficiency, and the algorithm based on SINR incremental iteration is used to solve the problem.The strategy takes into account both the power efficiency of the user and the power efficiency of the system, and can achieve good performance in both aspects, and the degree of convergence of these two aspects can be adjusted according to a scale factor.It is a scheme that can dynamically adapt to different system requirements.Finally, a series of simulation experiments show that the proposed algorithm and power control strategy are reasonable and effective.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN929.5

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