On the interference suppression capabilities of cognitive enabled femto cellular networks

M. Z. Shakir, R. Atat, Mohamed-Slim Alouini
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引用次数: 6

Abstract

Cognitive Radios are considered as a standard part of future Heterogeneous mobile network architecture. In this paper, we consider a two tier Heterogeneous network with multiple radio access technologies (RATS) namely; (i) the secondary network which comprises of cognitive enabled femto base stations which are referred to as cognitive-femto BS (CFBS) such that each of the BS are equipped with a single antenna and (ii) the macrocell network which is considered as a primary network. The effectiveness of the cognitive transmission is based on the efficient spectrum sensing algorithms which determine the availability of the spectrum holes. However, it is equally important for the cognitive network to minimize the cross-tier interference particularly during (i) the spectrum sensing and (ii) the cognitive transmission if spectrum is available. By exploiting the cooperation among the CFBS, the multiple CFBS can be considered as a single base station with multiple geographically dispersed antennas. In this context, we proposed a smart network where CFBS collaborates to reduce the cross-tier interference level by directing the main beam toward the desired femtocell mobile user and creating null toward the cross-tier interference. The resultant network is referred to as Smart cognitive-femto network (SCFN) which requires the CFBS to be self-aware such that the CFBS are aware of their surroundings and adapt accordingly to maintain a reliable and efficient communication link. In order to determine the effectiveness of the proposed smart network, we study the interference rejection (or suppression) capabilities of the SCFN. It has been shown that the proposed smart network offers significant performance improvements in interference suppression and signal to interference ratio (SIR) and may be considered as a promising solution to the interference management problems in Heterogeneous network.
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基于认知的femto蜂窝网络干扰抑制能力研究
认知无线电被认为是未来异构移动网络体系结构的标准组成部分。在本文中,我们考虑了具有多种无线接入技术(RATS)的两层异构网络;(i)次要网络,由认知能力的飞频基站组成,这些基站被称为认知飞频基站(CFBS),每个基站都配备一个天线;(ii)被认为是主要网络的宏蜂窝网络。认知传输的有效性基于有效的频谱感知算法,该算法确定了频谱孔的可用性。然而,对于认知网络来说,最小化跨层干扰同样重要,特别是在(i)频谱感知和(ii)频谱可用时的认知传输过程中。通过利用多个循环基站之间的相互协作,多个循环基站可以看作是一个具有多个地理分散天线的基站。在这种情况下,我们提出了一种智能网络,其中CFBS通过将主波束指向所需的femtocell移动用户并创建指向交叉层干扰的null来协同降低交叉层干扰水平。由此产生的网络被称为智能认知-飞向网络(SCFN),它要求CFBS具有自我意识,这样CFBS就能意识到周围环境并相应地进行适应,以保持可靠和有效的通信链路。为了确定所提出的智能网络的有效性,我们研究了SCFN的抗干扰(或抑制)能力。研究表明,所提出的智能网络在干扰抑制和信号干扰比(SIR)方面具有显著的性能改善,可以被认为是解决异构网络干扰管理问题的一种有希望的解决方案。
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