Robust resource allocation for multi-tier cognitive heterogeneous networks

How to improve system capacity and spectral efficiency is a key issue for next generation wireless communication. Heterogeneous network (HetNet) has been considered as a new promising technique for enhancing the quality of service and spectrum efficiency due to different radio access technology and network structures. However, conventional resource allocation algorithms in HetNets are achieved under the assumption of perfect parameter information which may be invalid in practical systems. In this paper, a robust rate maximization resource allocation problem for multiuser cognitive HetNets is formulated to flexibly use network resource and improve overall capacity where robust cross-tier interference constraint and maximum transmit power constraint of base station are simultaneously considered. The semi-infinite programming problem is converted into a geometric programming problem by using relaxation approaches. Simulation results show that the proposed algorithm can guarantee transmission performance of macrocell users and microcell users under channel uncertainties.