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Uplink Low Power Based Radio Resource Management in Wireless Heterogeneous Networks

机译:无线异构网络上行链路低功耗基于无线电资源管理

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Due to the rapid rise of energy consumption and limited battery power of wireless user equipment (UE), low power communication becomes very important. Heterogeneous network deployment can significantly reduce regional power consumption. For heterogeneous network scenarios, this paper proposes an uplink low-power resource allocation scheme considering battery power limitation and user QoS requirements. Based on the assumption that each user has access to at most one base station (BS), the scheme is modeled as a mixed integer nonlinear programming (MINLP) problem. Since each user has access to one BS at most, the transmitting power matrix from the UE to the BSs (UE-to-BS matrix) is a sparse matrix. The MINLP problem can be transformed into an optimization problem searching sparse solution. In this paper, the reweighted L1 norm is introduced as a penalty function to remove the integer constraint and to regulate the sparsity of the UE-to-BS transmitting power matrix. In order to obtain the optimal resource allocation scheme, a reweighted L1 norm penalty based radio resource management (RRM) algorithm is proposed. Simulation results show that the reweighted L1 norm penalty based RRM algorithm has good convergence performance and the results are very close to optimal solutions. The proposed resource management scheme can prolong the working time of low-energy users and guarantee the QoS requirements of UE in the system.
机译:由于能耗的快速上升和无线用户设备的电池电量有限(UE),低功率通信变得非常重要。异构网络部署可以显着降低区域功耗。对于异构网络场景,本文提出了考虑电池电量限制和用户QoS要求的上行链路低功耗资源分配方案。基于每个用户可以访问到大多数基站(BS)的假设,该方案被建模为混合整数非线性编程(MINLP)问题。由于每个用户最多可以访问一个BS,因此来自UE到BSS(UE-TO-BS矩阵)的发送功率矩阵是稀疏矩阵。 MinLP问题可以转换为搜索稀疏解决方案的优化问题。在本文中,将重新重量的L1规范作为惩罚功能引入以去除整数约束,并调节UE-To-BS发送功率矩阵的稀疏性。为了获得最佳资源分配方案,提出了一种基于重量的L1规范惩罚的无线电资源管理(RRM)算法。仿真结果表明,重新重量的L1规范惩罚的RRM算法具有良好的收敛性能,结果非常接近最佳解决方案。所提出的资源管理方案可以延长低能源用户的工作时间,并保证系统中UE的QoS要求。

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