دانلود رایگان مقاله بهره وری انرژی بر پایه انتخاب سلول مشترک و طرح تخصیص قدرت برای HetNets

Abstract

Heterogeneous networks (HetNets) composed of overlapped cells with different sizes are expected to improve the transmission performance of data service significantly. User equipments (UEs) in the overlapped area of multiple cells might be able to access various base stations (BSs) of the cells, resulting in various transmission performances due to cell heterogeneity. Hence, designing optimal cell selection scheme is of particular importance for it may affect user quality of service (QoS) and network performance significantly. In this paper, we jointly consider cell selection and transmit power allocation problem in a HetNet consisting of multiple cells. For a single UE case, we formulate the energy efficiency of the UE, and propose an energy efficient optimization scheme which selects the optimal cell corresponding to the maximum energy efficiency of the UE. The problem is then extended to multiple UEs case. To achieve joint performance optimization of all the UEs, we formulate an optimization problem with the objective of maximizing the sum energy efficiency of UEs subject to QoS and power constraints. The formulated nonlinear fractional optimization problem is equivalently transformed into two subproblems, i.e., power allocation subproblem of each UE-cell pair, and cell selection subproblem of UEs. The two subproblems are solved respectively through applying Lagrange dual method and Kuhn–Munkres (K-M) algorithm. Numerical results demonstrate the efficiency of the proposed algorithm.

8. Conclusion

In this paper, we jointly study cell selection and power allocation problem of UEs in a HetNet comprised of multiple heterogeneous cells. To achieve energy efficient data transmission, the problem of joint cell selection and power allocation is formulated as a constrained sum energy efficiency maximization problem. We solve the formulated optimization problem for both single user case and multi-user case. For both cases, through transforming the optimization problem equivalently into two subproblems, i.e., power allocation subproblem and cell selection subproblem, and applying iterative method and the K-M algorithm to solve the two subproblems respectively, the optimal cell selection and power allocation strategies are obtained. Numerical results demonstrate that the proposed algorithm offers higher energy efficiency compared with previously proposed algorithms.