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Joint power allocation for multi-cell distributed antenna systems with large-scale CSIT

机译:具有大规模CSIT的多小区分布式天线系统的联合功率分配

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In this paper, the problem of joint power allocation (PA) for the downlink of a multi-cell distributed antenna system (DAS) is addressed. Motivated by practical applications, we focus on a reasonable scenario that only the large-scale channel state information at the transmitter (CSIT) is available. Based on the observation that the capacity-achieving input covariance for each cell is diagonal and that PA optimization is enough to achieve the maximum ergodic sum capacity, we formulate a joint PA optimization problem to maximize the ergodic sum capacity of the system with a total transmit power constraint for each cell. A rather precise closed-form approximation of the ergodic sum capacity is then introduced and taken as the objective function instead so that the original joint PA optimization problem can be simplified. Finally, we propose an iterative PA scheme based on the simplified joint PA optimization problem, in which Signomial Programming (SP) is used. Monte Carlo simulations show that the proposed scheme converges quickly and can offer nearly optimal system ergodic sum capacity. Thus, we refer the proposed PA scheme as a suboptimal one. Moreover, from the simulations we can see that a significant performance gain can be achieved by multi-cell joint PA in DAS with only large-scale CSIT.
机译:本文解决了多小区分布式天线系统(DAS)下行链路的联合功率分配(PA)问题。受实际应用的启发,我们将重点放在一个合理的场景上,即只有发射机(CSIT)上的大规模信道状态信息可用。基于观察到每个单元的容量输入协方差是对角线,并且PA优化足以实现最大遍历总和容量,我们制定了联合PA优化问题,以在总发射量的情况下最大化系统的遍历总容量每个单元的功率约束。然后引入遍历总容量的相当精确的闭合形式近似,并将其作为目标函数,从而可以简化原始的联合PA优化问题。最后,我们提出了一种基于简化联合PA优化问题的迭代PA方案,其中使用了信号编程(SP)。蒙特卡洛仿真表明,所提出的方案收敛迅速,可以提供几乎最佳的系统遍历总容量。因此,我们将提出的PA方案称为次优方案。此外,从仿真中我们可以看到,仅使用大型CSIT,DAS中的多单元联合PA可以实现显着的性能提升。

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