Cross-Layer Resource Management in Software Defined Ultra Dense Wireless Networks

This paper focuses on the energy management problem of ultra dense wireless networks. The work modes of small cells are controlled by the software defined approach to reduce the system energy consumption. Considering the quality of service (QoS) requirements of users and coverage ratio requirement, the energy minimization problem are formulated as a mixedinteger nonlinear programming (MINLP) problem. To deal with this problem, we utilize the sparse character of the beamforming vector and the method of reweighted l1 norm to approximate l0 norm. Because the coverage ratio requirement constraint is still non-convex, we proposed a heuristic iterative algorithm to obtain a practical solution. Simulation results show that the proposed heuristic algorithm can achieve good performance compared with the conventional sparsity (SP) based algorithm.