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Computer Science > Networking and Internet Architecture

arXiv:2306.17455v1 (cs)
[Submitted on 30 Jun 2023 ]

Title: Clipping noise cancellation receiver for the downlink of massive MIMO OFDM system

Title: 大规模MIMO OFDM系统下行链路的剪切噪声消除接收机

Authors:Marcin Wachowiak, Pawel Kryszkiewicz
Abstract: Massive multiple-input multiple-output (mMIMO) technology is considered a key enabler for the 5G and future wireless networks. In most wireless communication systems, mMIMO is employed together with orthogonal frequency-division multiplexing (OFDM) which exhibits a high peak-to-average-power ratio (PAPR). While passing the OFDM signal through one of the common RF front-ends of limited linearity, significant distortion of the transmitted signal can be expected. In mMIMO systems, this problem is still relevant as in some channels the distortion component is beamformed in the same directions as the desired signal. In this work, we propose a multi-antenna clipping noise cancellation (MCNC) algorithm for the downlink of the mMIMO OFDM system. Computer simulations show it can remove nonlinear distortion even under severe nonlinearity. Next, a simplified version of the algorithm is proposed. It was observed that for the direct visibility channels, its performance is only slightly degraded with respect to the MCNC algorithm.
Abstract: 大规模多输入多输出(mMIMO)技术被认为是5G及未来无线网络的关键使能技术。 在大多数无线通信系统中,mMIMO与正交频分复用(OFDM)一起使用,OFDM具有较高的峰均功率比(PAPR)。 当将OFDM信号通过一个有限线性的常见射频前端时,可以预期传输信号会出现显著失真。 在mMIMO系统中,这个问题仍然相关,因为在某些信道中,失真分量会被波束成形到与期望信号相同的方向。 在本工作中,我们提出了一种多天线削波噪声消除(MCNC)算法,用于mMIMO OFDM系统的下行链路。 计算机仿真表明,即使在严重的非线性情况下,该算法也可以消除非线性失真。 接下来,提出了一种该算法的简化版本。 观察到对于直视信道,其性能相对于MCNC算法仅略有下降。
Comments: accepted to IEEE Transactions on Communications
Subjects: Networking and Internet Architecture (cs.NI) ; Information Theory (cs.IT)
Cite as: arXiv:2306.17455 [cs.NI]
  (or arXiv:2306.17455v1 [cs.NI] for this version)
  https://doi.org/10.48550/arXiv.2306.17455
arXiv-issued DOI via DataCite

Submission history

From: Pawel Kryszkiewicz [view email]
[v1] Fri, 30 Jun 2023 08:00:58 UTC (4,319 KB)
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