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  1. null (Ed.)
    Due to the dense deployment of a small base station (SBS), wired backhauling is not always available, nor it is efficient. Therefore mmWaves are introduced to serve as backhauling links that offer high backhauling throughput and low CAPEX. However, mmWaves suffer from a high attenuation rate as the distance between SBSs and a macro base station (MBS) increases, which can severely degrade the system performance. Therefore, it is more efficient to use some SBSs to aggregate from different SBSs to MBS. On the other hand, densely deployed SBSs with wireless backhauling can cause high energy consumption in the system. In this work, we present a new network model in which SBSs are able to harvest energy from a renewable source and utilize it for backhauling and their associate UEs. A mathematical Optimization problem is formulated to solve UEs association, dynamic sleeping, backhauling, and transmission power. Moreover, due to the complexity of the formulated problem, a heuristic algorithm is introduced. Namely, a heuristic backhauling and dynamic sleeping (HBDS) algorithm is introduced to decomposes the formulated problem into two parts and solve it iteratively. Finally, computer simulation results that demonstrate the model’s performance are presented for comparison between optimal solution and HBDS, which shows that HBDS has better computation efficiency with minimum performance difference. 
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