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Based on the cross-layer design, the power-optimization problem of Macro-Femto Heterogeneous Networks (HetNets) has been formulated. The constraints of power and resource block allocation in the physical layer, delay and target data rate in the medium access control layer, urgent queue length in the network layer, and packet error rate in the transport layer, have been considered. The original problem is non-deterministic polynomial time hard, which cannot be solved practically. After the restrictions of upper layers are translated into constraints with physical layer parameters, and the integer restrictions are relaxed, the original problem can be decomposed into convex optimization subproblems. The optimal solutions of resource block allocation and power allocation can be obtained by using the Lagrangian optimization. Simulation results show that the proposed scheme is better than both the round robin algorithm and the max-min one in terms of energy efficiency, throughput and service fairness. The round robin algorithm and the max-min one only focus on the user fairness rather than quality of service fairness. Compared to the round robin scheme (the max-min one), the proposed scheme improves the energy efficiency 58.85% (62.41%), the throughput 19.09% (25.25%), the service fairness 57.69% (35.48%).
Based on the cross-layer design, the power-optimization problem of Macro-Femto Heterogeneous Networks (HetNets) has been formulated. The constraints of power and resource block allocation in the physical layer, delay and target data rate in the medium access control layer , urgent queue length in the network layer, and packet error rate in the transport layer, have been considered. The original problem is non-deterministic polynomial time hard, which can not be solved practically. After the restrictions of upper layers are translated into constraints with physical layer parameters, and the integer restrictions are relaxed, the original problem can be decomposed into convex optimization subproblems. The optimal solutions of resource block allocation and power allocation can be obtained by using the Lagrangian optimization. Simulation results show that the proposed scheme is better than both the round robin algorithm and the max-min one in terms of energy efficiency, throughput and service fairness. The round robin algorithm and the max-min one only focus on the user fairness rather than quality of service fairness. Compared to the round robin scheme (the max-min one), the proposed scheme improves the energy efficiency 58.85% (62.41 %), the throughput 19.09% (25.25%), the service fairness 57.69% (35.48%).