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arXiv cs/0610077cs.ITmath.IT
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具有块对角化和有限速率反馈的MIMO广播信道

MIMO Broadcast Channels with Block Diagonalization and Finite Rate Feedback

Niranjay Ravindran, Nihar Jindal

摘要:

块对角化是用于多天线广播(下行链路)信道的线性预编码技术,其涉及到向每个接收器传输多个数据流,使得在任何接收器处都不经历多用户干扰。这种低复杂度的方案仅与容量相差几dB,但确实需要在发射机处非常准确的信道知识,这在衰落场景中可能非常难以获得。我们考虑一个有限的反馈系统,其中每个接收机知道它的信道完美,但发射机只提供了有限数量的信道反馈比特从每个接收机。使用随机矢量量化参数,我们量化的吞吐量损失由于不完善的信道知识作为反馈水平的函数。信道知识的质量必须提高成比例的SNR,以防止干扰的限制,我们表明,缩放反馈位的数量与系统SNR的线性是足够的,以保持有界的速率损失。最后,我们研究了一个简单的标量量化方案,可以实现与矢量量化相同的缩放行为。

英文摘要:

Block diagonalization is a linear precoding technique for the multiple antenna broadcast (downlink) channel that involves transmission of multiple data streams to each receiver such that no multi-user interference is experienced at any of the receivers. This low-complexity scheme operates only a few dB away from capacity but does require very accurate channel knowledge at the transmitter, which can be very difficult to obtain in fading scenarios. We consider a limited feedback system where each receiver knows its channel perfectly, but the transmitter is only provided with a finite number of channel feedback bits from each receiver. Using a random vector quantization argument, we quantify the throughput loss due to imperfect channel knowledge as a function of the feedback level. The quality of channel knowledge must improve proportional to the SNR in order to prevent interference-limitations, and we show that scaling the number of feedback bits linearly with the system SNR is sufficient to maintain a bounded rate loss. Finally, we investigate a simple scalar quantization scheme that is seen to achieve the same scaling behavior as vector quantization.

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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