Joint User Scheduling and Power Allocation Optimization for Energy-Efficient NOMA Systems With Imperfect CSI
Joint User Scheduling and Power Allocation Optimization for Energy-Efficient NOMA Systems With Imperfect CSI
复制标题
不完美 CSI 节能 NOMA 系统的联合用户调度和功率分配优化
DOI：
10.1109/jsac.2017.2777672
复制
发表时间：
2017-12-01
影响因子：
16.4
通讯作者：
Leung, Victor C. M.
中科院分区：
文献类型：
--
作者：
Fang, Fang;Zhang, Haijun;Leung, Victor C. M.
非正交多址(NOMA)在接收端利用连续干扰消除技术来提高频谱效率。通过使用该技术，多个用户可以在同一个子信道上被多路复用，从而获得高和速率。以往对NOMA系统的研究大多假定信道状态信息(CSI)是完美的。然而，在本文中，我们通过考虑不完善的CSI来研究下行NOMA单小区网络的能量效率改进。将能量有效的资源调度问题描述为具有中断概率极限、系统最大功率、最小用户数据速率和共享同一子信道的最大多路复用用户数等约束的非凸优化问题。不同于以往的工作，多路复用用户的最大数目可以大于两个，并且在NOMA中首次研究了不完全CSI的资源分配。为了有效地解决这一问题，首先将概率混合问题转化为非概率问题。为了最大化系统的能量效率，提出了一种迭代的用户调度和功率分配算法。基于穷举搜索的最优用户调度作为系统性能的基准，但其计算复杂度较高。为了在系统性能和计算复杂度之间取得平衡，提出了一种新的次优用户调度方案，用于在不同的子信道上调度用户。基于用户调度方案，利用拉格朗日方法推导出最优功率分配表达式。通过将分数形式问题转化为等价的减法形式优化问题，提出了一种最大化系统能量效率的迭代功率分配算法。仿真结果表明，所提出的用户调度算法接近于达到最优性能。
Non-orthogonal multiple access (NOMA) exploits successive interference cancellation technique at the receivers to improve the spectral efficiency. By using this technique, multiple users can be multiplexed on the same subchannel to achieve high sum rate. Most previous research works on NOMA systems assume perfect channel state information (CSI). However, in this paper, we investigate energy efficiency improvement for a down-link NOMA single-cell network by considering imperfect CSI. The energy efficient resource scheduling problem is formulated as a non-convex optimization problem with the constraints of outage probability limit, the maximum power of the system, the minimum user data rate, and the maximum number of multiplexed users sharing the same subchannel. Different from previous works, the maximum number of multiplexed users can be greater than two, and the imperfect CSI is first studied for resource allocation in NOMA. To efficiently solve this problem, the probabilistic mixed problem is first transformed into a non-probabilistic problem. An iterative algorithm for user scheduling and power allocation is proposed to maximize the system energy efficiency. The optimal user scheduling based on exhaustive search serves as a system performance benchmark, but it has high computational complexity. To balance the system performance and the computational complexity, a new suboptimal user scheduling scheme is proposed to schedule users on different subchannels. Based on the user scheduling scheme, the optimal power allocation expression is derived by the Lagrange approach. By transforming the fractional-form problem into an equivalent subtractive-form optimization problem, an iterative power allocation algorithm is proposed to maximize the system energy efficiency. Simulation results demonstrate that the proposed user scheduling algorithm closely attains the optimal performance.