首页> 外文会议>2015 IEEE China Summit amp; International Conference on Signal and Information Processing >Joint base station selection and beamforming in uplink SIMO networks with per-user power constraints
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Joint base station selection and beamforming in uplink SIMO networks with per-user power constraints

机译:具有按用户功率限制的上行SIMO网络中的联合基站选择和波束成形

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摘要

Consider an uplink SIMO network consisting of multiple base stations (BSs) and multiple users, where each user has an individual transmit power constraint, and the BSs are allowed to cooperate in data receiving. To guarantee fairness among users and avoid heavy burden of backhaul data exchange, we maximize the minimum S-INR based on joint BS selection and beamforming. We formulate this problem from the perspective of sparse beamforming. However, the scaling ambiguity of the receive beamformers will make the sparse constraints trivial. Inspired by the observation that the transmit beamformer is immune to the scaling ambiguity, we apply the duality theorem to the uplink max-min problem under per-user power constraints, and reformulate it as an equivalent downlink problem. An iterative two-stage algorithm is then developed to solve the sparse beamforming problem efficiently. The effectiveness of the proposed algorithm is demonstrated by numerical simulations.
机译:考虑由多个基站(BS)和多个用户组成的上行链路SIMO网络,其中每个用户都有各自的发射功率约束,并且允许BS在数据接收中进行协作。为了保证用户之间的公平并避免回程数据交换的沉重负担,我们基于联合的BS选择和波束成形来最大化最小S-INR。我们从稀疏波束成形的角度提出这个问题。但是,接收波束形成器的缩放模糊性将使稀疏约束变得微不足道。受到观察,即发射波束成形器不受缩放歧义的影响,我们将对偶定理应用于每个用户功率约束下的上行链路最大-最小问题,并将其重新表述为等效的下行链路问题。然后,开发了一种迭代的两阶段算法来有效地解决稀疏波束形成问题。数值仿真证明了该算法的有效性。

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