基于细胞分裂技术的ZF预编码MIMO-NOMA系统的节能功率分配

Abdolrasoul Sakhaei Gharagezlou, Mahdi Nangir, Nima Imani
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引用次数: 1

摘要

本文从能源效率(EE)的角度对系统的性能进行了研究。为了检查EE的性能,为每个用户分配适当的功率。本文所讨论的系统是一个采用非正交多址(NOMA)方法的多输入多输出(MIMO)系统。该系统中的预编码被认为是零强迫(ZF)。还假定通道状态信息(CSI)模式是完美的。首先,研究了影响信道的所有参数,如路径损耗和波束形成,然后得到了信道矩阵。为提高系统性能,为信道条件较差的用户提供了较好的条件。这些条件是通过向这些用户分配更合适的功率来创造的,换句话说,根据用户与基站(BS)的距离以及每个用户的信道条件来划分总发射功率。利用最小用户速率和最大传输功率两个约束条件,提出了EE最大化问题。这是一个非凸问题,利用最优化性质变成了凸问题,由于问题是有约束的,利用拉格朗日对偶函数变成了无约束问题。数值和仿真结果验证了这些数学关系,结果表明,与现有方法相比,所提方案的性能得到了提高。仿真结果与两种不同的算法具有相同的目标函数有关。此外,为了与其他方法的性能进行比较,还对这两种算法的输出结果进行了比较。
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Energy Efficient Power Allocation in MIMO-NOMA Systems with ZF Precoding Using Cell Division Technique
—In this paper, the performance of a system in terms of the energy efficiency (EE) is studied. To check the EE performance, an appropriate power is allocated to each user. The system in question in this paper is a multiple-input multiple-output (MIMO) system with non-orthogonal multiple access (NOMA) method. Precoding in this system is considered to be the zero forcing (ZF). It is also assumed that the channel state information (CSI) mode is perfect. First, all the parameters that affect the channel, such as path loss and beam forming are investigated, and then the channel matrix is obtained. To improve system performance, better conditions are provided for users with poor channel conditions. These conditions are created by allocating more appropriate power to these users, or in other words, the total transmission power is divided according to the distance of users from the base station (BS) and the channel conditions of each user. The problem of maximizing the EE is formulated with two constraints of the minimum user rate and the maximum transmission power. This is a non-convex problem that becomes a convex problem using optimization properties, and because the problem is constrained it becomes an unconstrained problem using the Lagrange dual function. Numerical and simulation results are presented to prove the mathematical relationships which show that the performance of the proposed scheme is improved compared to the existing methods. The simulation results are related to two different algorithms with a same objective function. Furthermore, to comparison with performance of other methods, output of these two algorithms are also compared with each other.
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