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arXiv 1503.08436cs.ITmath.IT
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剩余传输RF损伤对基于训练的MIMO系统的影响

Impact of Residual Transmit RF Impairments on Training-Based MIMO Systems

Xinlin Zhang, Michail Matthaiou, Mikael Coldrey, Emil Björnson

摘要:

射频损伤是无线通信系统中普遍存在的一个问题,它严重限制了多输入多输出系统的性能。虽然我们可以诉诸补偿计划,以减轻这些损害的一部分,一定数量的剩余损害总是持续存在。在本文中,我们考虑了一个基于训练的点对点MIMO系统的剩余发射射频损伤(RTRI)使用空间复用传输。具体来说,我们推导出一个新的线性信道估计所提出的模型,并显示RTRI创建一个估计误差地板在高信噪比(SNR)制度。此外,我们推导出封闭形式的信号噪声干扰比(SINR)分布的表达式,以及分析表达式的各态历经可实现的迫零率,最大比合并,最小均方误差接收机,分别。此外,我们优化了各态历经的可实现的速率相对于训练序列的长度,并证明了有限维系统与RTRI一般需要更多的训练在高信噪比比那些与理想的硬件。最后,我们将我们的分析扩展到大规模的MIMO配置,并推导出确定性等价的遍历可达速率。结果表明,通过部署大型接收天线阵列,由于RTRI的额外的训练要求可以被消除。事实上,在接收天线数量足够大的情况下,具有RTRI的系统甚至可能比具有理想硬件的系统需要更少的训练。

英文摘要:

Radio-frequency (RF) impairments, which intimately exist in wireless communication systems, can severely limit the performance of multiple-input multiple-output (MIMO) systems. Although we can resort to compensation schemes to mitigate part of these impairments, a certain amount of residual impairments always persists. In this paper, we consider a training-based point-to-point MIMO system with residual transmit RF impairments (RTRI) using spatial multiplexing transmission. Specifically, we derive a new linear channel estimator for the proposed model, and show that RTRI create an estimation error floor in the high signal-to-noise ratio (SNR) regime. Moreover, we derive closed-form expressions for the signal-to-noise-and-interference ratio (SINR) distributions, along with analytical expressions for the ergodic achievable rates of zero-forcing, maximum ratio combining, and minimum mean-squared error receivers, respectively. In addition, we optimize the ergodic achievable rates with respect to the training sequence length, and demonstrate that finite dimensional systems with RTRI generally require more training at high SNRs than those with ideal hardware. At last, we extend our analysis to large-scale MIMO configurations, and derive deterministic equivalents of the ergodic achievable rates. It is shown that, by deploying large receive antenna arrays, the extra training requirements due to RTRI can be eliminated. In fact, with sufficiently large number of receive antennas, systems with RTRI may even need less training than systems with ideal hardware.

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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