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arXiv 0811.4630cs.ITmath.IT
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多用户MIMO-OFDM下行链路的信道状态预测、反馈和调度

Channel State Prediction, Feedback and Scheduling for a Multiuser MIMO-OFDM Downlink

Hooman Shirani-Mehr, Daniel N. Liu, Giuseppe Caire

摘要:

我们考虑MIMO-OFDM无线系统的下行链路,其中基站(BS)具有M个天线,并且服务于K个单天线用户终端(UT),其中K大于或等于M。用户从公共下行链路导频符号估计他们的信道向量并反馈预测,BS使用该预测来计算下一时隙的线性波束成形矩阵并根据比例公平调度(PFS)算法选择要服务的用户。我们考虑一个现实的物理信道模型作为标准化的基准和一些替代方案的信道估计和预测方案。我们表明,基于ESPRIT的参数化方法能够准确地预测信道,即使对于相对较高的用户移动性。然而,存在一类信道,其特征在于大的多普勒扩展(高移动性)和集群的角扩展,预测是本质上困难的,所有考虑的方法失败。我们提出了一个修改后的PFS,考虑到“可预测性”状态的UT,并显着优于经典PFS的预测误差的存在。本文的主要结论是,只要对不可预测的用户进行适当的处理,多用户MIMO下行链路即使在存在高移动性用户的情况下也能产生非常好的性能

英文摘要:

We consider the downlink of a MIMO-OFDM wireless systems where the base-station (BS) has M antennas and serves K single-antenna user terminals (UT) with K larger than or equal to M. Users estimate their channel vectors from common downlink pilot symbols and feed back a prediction, which is used by the BS to compute the linear beamforming matrix for the next time slot and to select the users to be served according to the proportional fair scheduling (PFS) algorithm. We consider a realistic physical channel model used as a benchmark in standardization and some alternatives for the channel estimation and prediction scheme. We show that a parametric method based on ESPRIT is able to accurately predict the channel even for relatively high user mobility. However, there exists a class of channels characterized by large Doppler spread (high mobility) and clustered angular spread for which prediction is intrinsically difficult and all considered methods fail. We propose a modified PFS that take into account the "predictability" state of the UTs, and significantly outperform the classical PFS in the presence of prediction errors. The main conclusion of this work is that multiuser MIMO downlink yields very good performance even in the presence of high mobility users, provided that the nonpredictable users are handled appropriately

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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