用于LTE HetNet增强微蜂窝范围扩展的上下文感知认知SIMO DL收发器

I. Mrissa, F. Bellili, S. Affes, A. Stephenne
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引用次数: 0

摘要

在宏基站网络中部署小型基站(微基站、飞基站或中继)是增加系统容量的有利解决方案。然而,相对于大蜂窝,小蜂窝的传输能力通常较弱,这就给小蜂窝造成了严重的干扰问题。范围扩展技术是解决这一问题的方法之一。我们的想法是以一种有利的方式偏置来自微蜂窝的接收信号功率,这样我们就可以从宏蜂窝中卸载比实际情况更多的ue。为了提高增程技术的性能,文献中提出了许多解决方案。在本文中,我们设计了一种新的单输入多输出(SIMO)上下文感知认知收发器(CTR),它能够切换到链路级吞吐量方面性能最好的调制解调器。在传统的自适应调制和编码(AMC)的基础上,我们允许上下文感知的CTR在三种不同的导频利用模式中做出最佳选择:传统的决策辅助(DA)或导频辅助,非DA (NDA)或盲,以及带导频的NDA,这是一种新提出的介于DA和NDA模式之间的混合版本。我们还使CTR能够在两种不同的信道识别方案之间做出最佳选择:传统的最小二乘(LS)和新开发的最大似然(ML)估计器。根据导频符号在接收端是否可以被适当利用,我们进一步使CTR能够在两种数据检测模式中做出最佳选择:相干或差分。我们注意到,通过联合使用我们的认知收发器和范围扩展技术,可以实现5^{th}$百分位蜂窝站点吞吐量和平均蜂窝站点吞吐量分别达到$ 48%和$ 42%的可观收益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Context-Aware Cognitive SIMO DL Transceiver for LTE HetNet Enhanced Pico-Cell Range Expansion
Deploying small cells (pico, femto or relays) in a macro-cell network is an advantageous solution to increase system capacity. However, small cells usually transmit with a weaker power compared to macro-cells, this fact causes a serious interference problem for these former. Range Expansion technique is among the solutions proposed to overcome this problem. The idea is to bias the received signal power from pico-cells in an advantage manner so that we have more UEs offloaded from macro-cell than the real case. Many solutions were proposed in the literature to enhance Range Expansion technique performances. In this paper, we design a new single-input multiple-output (SIMO) context-aware cognitive transceiver (CTR) that is able to switch to the best performing modem in terms of link-level throughput. On the top of conventional adaptive modulation and coding (AMC), we allow the context-aware CTR to make best selection among three different pilot-utilization modes: conventional decision-aided (DA) or pilot- assisted, non-DA (NDA) or blind, and NDA with pilot which is a newly proposed hybrid version between the DA and NDA modes. We also enable the CTR to make best selection between two different channel identification schemes: conventional least-square (LS) and newly developed maximum-likelihood (ML) estimators. Depending on whether pilot symbols can be properly exploited or not at the receiver, we further enable the CTR to make best selection among two data detection modes: coherent or differential. We note that a considerable gains reaching $48\%$ and $42\%$ for $5^{th}$ percentile cell-site and average cell-site throughput respectively can be achieved by using jointly our cognitive transceiver with Range Expansion technique.
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