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Robust Time Reversal-based Transmit Optimization for Green Heterogeneous Networks

机译:基于鲁棒时间反转的绿色异构网络传输优化

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摘要

Time reversal (TR) beamforming, considered as one of most prominent linear precoders, has showed the feasibility in conventional communications. In this paper, we propose the TR-based transmit optimization for heterogeneous networks (HetNets) where multiple femtocells apply TR precoders over frequency selective channels, with the signal-to-inference-plus-noise ratio (SINR) and interference constraints at single-antenna femtocell user devices. In multi-femtocell network environments, we exhibit that TR outperforms the well-known zero-forcing beamforming. Particularly, we focus on the practical case of imperfect channel estimation at femtocell base stations. The robust optimization methodology is hence devised by taking into account the average effect of channel estimation error (CEE) on system performance. Under the assumption of estimation error in time-varying channels, we derive the exact closed-form expressions of the desired signal, inter-symbol interference (ISI), inter-user interference (IUI), co- and cross-layer interference terms, respectively. These derivations allow us to tackle the proposed robust algorithm by convex optimization techniques. In final, numerical results are shown to confirm the validation of our proposal.
机译:时间反转(TR)波束成形被认为是最著名的线性预编码器之一,它显示了常规通信的可行性。在本文中,我们提出了针对异构网络(HetNets)的基于TR的传输优化方案,在该方案中,多个毫微微小区在频率选择信道上应用TR预编码器,且信噪比(SINR)和干扰限制在单天线毫微微小区用户设备。在多毫微微小区网络环境中,我们展示出TR胜过众所周知的迫零波束成形。特别地,我们集中在毫微微小区基站上不完美的信道估计的实际情况。因此,通过考虑信道估计误差(CEE)对系统性能的平均影响来设计鲁棒的优化方法。在时变信道中存在估计误差的假设下,我们得出所需信号,符号间干扰(ISI),用户间干扰(IUI),共层干扰和跨层干扰项的精确闭式表达式,分别。这些推导使我们能够通过凸优化技术来解决所提出的鲁棒算法。最后,显示了数值结果以确认我们的建议的有效性。

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