Transmit Antenna Selection with Optimum Combining for Aggregate Interference in Cognitive Underlay Radio Network
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- 作者：Vaibhav Hendre ; M. Murugan ; Madhukar Deshmukh…
- 关键词：Aggregate interference ; Bit error rate (BER) ; Cognitive radio (CR) ; Optimum combining (OC) ; Transmit antenna selection (TAS)
- 刊名：Wireless Personal Communications
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：92
- 期：3
- 页码：1071-1088
- 全文大小：
- 刊物类别：Engineering
- 刊物主题：Communications Engineering, Networks; Signal,Image and Speech Processing; Computer Communication Networks;
- 出版者：Springer US
- ISSN：1572-834X
- 卷排序：92
文摘
Transmit antenna selection (TAS) is most popular technique in underlay cognitive radio (CR) networks as they increase the capacity of secondary users with less hardware requirements. In this paper, a new scenario of CR ad-hoc network topology is proposed in which apart from primary users, there are multiple number of secondary users which are assumed to be distributed as homogeneous spatial Poisson point process (PPP) and are trying to use the primary spectrum in underlay mode. These multiple secondary transmitters generate the aggregate interference and can degrade the performance of secondary receiver. Here this aggregate interference is estimated and its impact on performance of secondary receiver under unconstrained mode of operation is presented. Further, to enhance the performance of secondary receivers in this scenario, single TAS technique based on maximizing the received signal to interference noise ratio by using optimum combining (OC) method is proposed. Furthermore, in this work the design of end to end Simulink based environment for secondary trans–receiver system with advancements in channel design and estimation is proposed. The bit error rate (BER) analysis is presented and verified for image data for single TAS-OC technique for unconstrained mode in underlay CR network in Rician fading channel. The BER performance is also presented for different number of secondary interference sources which are located at fixed distance in one case and they are assumed to be distributed as PPP in another case.