In the hybrid communication scenario of the Heterogeneous Cloud Radio Access Network and Device-to-Device in 5G, spectrum efficiency promotion and the interference controlling caused by spectrum reuse are still challenges. In this article, a novel resource management method, consisting of power and channel allocation, is proposed to solve this problem. An optimization model to maximum the system throughput and spectrum efficiency of the system, which is constrained by Signal to Interference plus Noise Ratio requirements of all users in diverse layers, is established. To solve the non-convex mixed integer nonlinear optimization problem, the optimization model is decomposed into two sub-problems, which are all solvable quasi-convex power allocation and non-convex channel allocation. The first step is to solve a power allocation problem based on solid geometric programming with the vertex search method. Then, a channel allocation constructed by three-dimensional hypergraph matching is established, and the best result of this problem is obtained by a heuristic greed algorithm based on the bipartite conflict graph and µ-claw search. Finally, the simulation results show that the proposed scheme improves the throughput performance at least 6% over other algorithms.

中文翻译：

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设备到设备底层 H-CRAN 网络的基于超图的资源分配

在5G异构云无线接入网和终端到终端的混合通信场景下，频谱效率提升和频谱复用带来的干扰控制仍然是挑战。在本文中，提出了一种由功率和信道分配组成的新资源管理方法来解决这个问题。建立了系统的最大系统吞吐量和频谱效率的优化模型，该模型受不同层中所有用户的信干噪比要求的约束。为求解非凸混合整数非线性优化问题，将优化模型分解为两个子问题，分别为可解拟凸功率分配和非凸信道分配。第一步是使用顶点搜索方法解决基于立体几何规划的功率分配问题。然后，建立了通过三维超图匹配构造的信道分配，并通过基于二部冲突图和μ爪搜索的启发式贪婪算法获得了该问题的最佳结果。最后，仿真结果表明，所提出的方案比其他算法提高了至少 6% 的吞吐量性能。