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Optimized Asymmetric Cooperation for Downlink Cloud Radio Access Network under per-Base Station Data Transfer Constraint

机译:按基站数据传输约束下的下行链路云无线电接入网络优化的不对称合作

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Using multicell cooperation between several base stations (BSs) connected to a central processor (CP) via finite capacity digital backhaul links, the inter-cell interference, which is known to limit the standard cellular systems, can be mitigated. When all user data is sent to each BS through the CP, which is referred as the full cooperation, the interference can be perfectly eliminated, however, this may cause the capacity of backhaul links to be exceeded. In this study, it is aimed to find the optimal asymmetric cooperation strategy for downlink cloud radio access network (C-RAN) which minimizes the total transmitted power from BSs where each user's signal-to-interference-and-noise ratio (SINR) is lower bounded and the number of user data streams sent by each BS is limited. The original problem is NP-hard and requires a combinatorial search. In this paper, we propose two sub-optimal cooperation methods. The first method is based on iteratively increasing the number of users served by the BSs until all users are chosen, and the second is based on iteratively adding a user data stream to be sent to a BS. We also consider a known method, iterative link removal, which is based on iteratively removing a user data from a BS by starting the full cooperation scheme, and a modified version of this method as a comparison. The simulation results show that the proposed methods can provide better performance in comparison to other methods in the literature.
机译:通过有限容量数字回程链路连接多个基站(BSS)之间的多个基站(BSS)之间的合作,可以减轻群体间干扰,该细胞间干扰可以减轻标准蜂窝系统。当所有用户数据通过CP被称为完全合作的CP时,可以完全消除干扰,但这可能会导致要超出回程链路的容量。在这项研究中,旨在找到用于下行链路云无线电接入网络(C-RAN)的最佳不对称合作策略,这最小化了来自BSS的总传输功率,其中每个用户的信号到干扰和噪声比(SINR)是下限和每个BS发送的用户数据流的数量有限。原始问题是np-clyp,需要组合搜索。在本文中,我们提出了两个次优合作方法。第一方法基于迭代地增加BSS服务的用户数,直到所选择的所有用户,并且第二是基于迭代地添加要发送到BS的用户数据流。我们还考虑一种已知的方法,迭代链路去除,其基于通过启动完整合作方案来迭代地从BS中删除用户数据,以及该方法的修改版本作为比较。仿真结果表明,与文献中的其他方法相比,该方法可以提供更好的性能。

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