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arXiv 1105.4206cs.ITmath.IT
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利用CSI训练和反馈的空间小区间干扰消除

Spatial Intercell Interference Cancellation with CSI Training and Feedback

Jun Zhang, Jeffrey G. Andrews, Khaled B. Letaief

摘要:

我们研究小区间干扰消除(ICIC)与实际的下行链路训练和上行链路信道状态信息(CSI)反馈模型。推导出了这种2小区网络的平均下行链路吞吐量。用户位置对信号干扰比(SIR)和信道估计误差有很大的影响。这促使在低信噪比(SNR)下在传统(单小区)波束成形和ICIC之间自适应地切换,其中ICIC仅在低SIR和准确信道估计的情况下是优选的,并且在高SNR下使用具有优化的训练和反馈的ICIC。对于给定的信道相干时间和固定的训练和反馈开销,我们开发了用于CSI训练的最优数据与导频功率分配以及用于反馈不同信道的CSI的最优反馈资源分配。模拟和有限速率数字反馈被认为是。对于模拟反馈,训练功率优化比反馈优化提供更显著的性能增益;而相反地,对于数字反馈,性能对反馈比特分配比训练功率优化更敏感。我们表明,即使使用低速率反馈和标准训练,ICIC也可以将干扰受限的蜂窝网络转换为噪声受限的网络。

英文摘要:

We investigate intercell interference cancellation (ICIC) with a practical downlink training and uplink channel state information (CSI) feedback model. The average downlink throughput for such a 2-cell network is derived. The user location has a strong effect on the signal-to-interference ratio (SIR) and the channel estimation error. This motivates adaptively switching between traditional (single-cell) beamforming and ICIC at low signal-to-noise ratio (SNR) where ICIC is preferred only with low SIR and accurate channel estimation, and the use of ICIC with optimized training and feedback at high SNR. For a given channel coherence time and fixed training and feedback overheads, we develop optimal data vs. pilot power allocation for CSI training as well as optimal feedback resource allocation to feed back CSI of different channels. Both analog and finite-rate digital feedback are considered. With analog feedback, the training power optimization provides a more significant performance gain than feedback optimization; while conversely for digital feedback, performance is more sensitive to the feedback bit allocation than the training power optimization. We show that even with low-rate feedback and standard training, ICIC can transform an interference-limited cellular network into a noise-limited one.

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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