与D2D共存的SCMA蜂窝网络容量分析及和速率最大化
Capacity Analysis and Sum Rate Maximization for the SCMA Cellular Network Coexisting with D2D Communications
摘要：
稀疏码多址接入（SCMA）是5G无线通信新接口的非正交多址接入（NOMA）技术中最受关注的方案。5G中旨在提高本地通信频谱效率的另一种有效技术是设备到设备（D2D）通信。因此，我们利用与D2D通信共存的SCMA蜂窝网络来满足物联网（IOT）的连接需求，并提高混合网络的系统和速率性能。我们首先推导出所有用户容量的信息论表达式，并根据蜂窝用户和D2D用户之间的相互干扰找到蜂窝用户的容量界限。然后，我们考虑蜂窝用户和D2D用户联合的功率优化问题，以最大化系统和速率。为了解决非凸优化问题，我们提出了一种基于几何规划（GP）的迭代功率分配算法。仿真结果表明，该算法收敛速度快，并能很好地提高和速率性能。
英文摘要：
Sparse code multiple access (SCMA) is the most concerning scheme among non-orthogonal multiple access (NOMA) technologies for 5G wireless communication new interface. Another efficient technique in 5G aimed to improve spectral efficiency for local communications is device-to-device (D2D) communications. Therefore, we utilize the SCMA cellular network coexisting with D2D communications for the connection demand of the Internet of things (IOT), and improve the system sum rate performance of the hybrid network. We first derive the information-theoretic expression of the capacity for all users and find the capacity bound of cellular users based on the mutual interference between cellular users and D2D users. Then we consider the power optimization problem for the cellular users and D2D users jointly to maximize the system sum rate. To tackle the non-convex optimization problem, we propose a geometric programming (GP) based iterative power allocation algorithm. Simulation results demonstrate that the proposed algorithm converges fast and well improves the sum rate performance.
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