  Taking full advantages of both heterogeneous networks (HetNets) and cloud
access radio access networks (CRANs), heterogeneous cloud radio access networks
(H-CRANs) are presented to enhance both the spectral and energy efficiencies,
where remote radio heads (RRHs) are mainly used to provide high data rates for
users with high quality of service (QoS) requirements, while the high power
node (HPN) is deployed to guarantee the seamless coverage and serve users with
low QoS requirements. To mitigate the inter-tier interference and improve EE
performances in H-CRANs, characterizing user association with RRH/HPN is
considered in this paper, and the traditional soft fractional frequency reuse
(S-FFR) is enhanced. Based on the RRH/HPN association constraint and the
enhanced S-FFR, an energy-efficient optimization problem with the resource
assignment and power allocation for the orthogonal frequency division multiple
access (OFDMA) based H-CRANs is formulated as a non-convex objective function.
To deal with the non-convexity, an equivalent convex feasibility problem is
reformulated, and closedform expressions for the energy-efficient resource
allocation solution to jointly allocate the resource block and transmit power
are derived by the Lagrange dual decomposition method. Simulation results
confirm that the H-CRAN architecture and the corresponding resource allocation
solution can enhance the energy efficiency significantly.
