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Designing Green C-RAN with limited fronthaul via mixed-integer second order cone programming

机译:通过混合整数二阶锥规划设计具有有限前程的Green C-RAN

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This paper considers the downlink transmission of cloud-radio access networks with limited fronthaul capacity constraint. Unlike the existing approaches where power of fronthaul is a quadratic or linear function of respective variables, we consider a more practical model where the power consumed by fronthaul depends on the rate served by the corresponding remote radio head (RRH). Then, we formulate a joint design of RRH selection, RRH-user association, and transmit beamforming for the problem of energy efficiency maximization. The formulated problem is a mixed-integer nonconvex program, which is generally NP-hard. For this nonconvex program, we leverage successive convex approximation (SCA) method to develop efficient iterative algorithms to find a high performance. Particularly, we iteratively approximate the continuous nonconvex constraints by conic ones so that the problem obtained at each iteration is a mixed-integer second order cone programming (MI-SOCP) for which dedicated solvers are available. To further reduce the computational complexity, an algorithm based on continuous relaxation and post-processing is proposed. Results show that our proposed algorithms converge faster and outperform known solutions.
机译:本文考虑了具有有限前传容量约束的云无线电接入网络的下行链路传输。与现有方法不同,前传功率是各个变量的二次函数或线性函数,我们考虑一种更实用的模型,其中前传所消耗的功率取决于相应远程无线电头端(RRH)的速率。然后,我们针对RRH选择,RRH-用户关联和发射波束形成的联合设计提出了能量效率最大化问题。提出的问题是一个混合整数的非凸程序,通常是NP难的。对于此非凸程序,我们利用连续凸逼近(SCA)方法来开发有效的迭代算法以找到高性能。特别是,我们用圆锥约束迭代地逼近连续的非凸约束,这样在每次迭代中获得的问题就是专用整数求解器可用的混合整数二阶锥规划(MI-SOCP)。为了进一步降低计算复杂度,提出了一种基于连续松弛和后处理的算法。结果表明,我们提出的算法收敛速度更快,并且优于已知的解决方案。

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