基于非正交多址的认知MIMO网络次用户系统容量优化

针对未来移动通信系统对大容量、高频谱利用率的需求，提出基于非正交多址（NOMA）技术的认知多输入多输出（MIMO）网络次用户系统容量优化方法。首先对发送信号进行预编码，随后按照信道质量增益对认知用户进行分簇，再对分簇之后的用户进行功率分配，最后将得到的NP-hard型多簇目标函数转化为求各子簇的容量；同时兼顾认知用户服务质量（QoS）及满足串行干扰消除（SIC）的条件，利用Lagrange函数结合Karush-Kuhn-Tucker （KKT）条件求解出分簇之后的最优功率分配系数，且该系数是0到1之间的常数。仿真结果表明，所提方法优于平均功率分配方法，并且在信道质量较差时，相比基于正交多址（OMA）技术的认知MIMO，显著提高了次用户系统容量。

Capacity optimization of secondary user system in MIMO cognitive networks based on non-orthogonal multiple access

Concerning the demands of large capacity and high spectrum utilization in future mobile communication system, a method for optimizing the capacity of secondary user system in Multiple-Input Multiple-Output (MIMO) cognitive networks based on Non-Orthogonal Multiple Access (NOMA) was proposed. Firstly, the transmitted signals were pre-coded, and then the cognitive users were clustered according to channel gains. Secondly, the power allocation was performed for users after clustering. Finally, the Non-deterministic Polynomial-hard (NP-hard) multi-cluster objective function was transformed into solving the capacity of each sub-cluster. Meanwhile, taking into account Quality of Service (QoS) of cognitive users and requirement of Successive Interference Cancellation (SIC), the optimal power allocation coefficient, which is a constant between 0 and 1, was solved by using Lagrange function and Karush-Kuhn-Tucker (KKT) condition. The simulation results show that, the proposed method outperforms the average power allocation method. And when the channel quality is poor, compared with the MIMO cognitive network based on Orthogonal Multiple Access (OMA), the proposed method has improved the capacity of secondary user system significantly.