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Title: Performance study of an underlay cognitive radio network in the presence of co-channel interference
Authors: Hussein, Jamal Ahmed
Issue Date: 2017
Publisher: Newcastle University
Abstract: Massive innovation in all aspects of the wireless communication network has been witnessed over the last few decades. The demand for data throughput is continuously growing, as such, the current regulations for allocating frequency spectrum are not able to respond to this exponential growth. Cognitive radio (CR), has been proposed as a solution to this problem. One of the possible scenarios of the implementation of CR is underlay cognitive radio. In this thesis the performance of an underlay cognitive radio network (UCRN) in the presence of the co-channel interference (CCI) is assessed. Firstly, the impact of CCI on the dual-hop cooperative UCRN is investigated over Rayleigh fading channels. In order to do this, the exact outage probability (OP), average error probability (AEP) and the ergodic capacity (EC) are studied. In addition, simple and asymptotic expressions for the OP and AEP are derived. Furthermore, the optimal power allocation is investigated to enhance the network performance. Moreover, the performance of a multi-user scenario is studied by considering the opportunistic SNR-based selection technique. Secondly, the effect of both primary network interference and CCI on the dual-hop UCRN over Rayleigh fading channels are studied. The equivalent signal-to-interference-plus-noise ratio (SINR) for this network scenario is obtained by considering multi-antenna schemes at all receiver nodes. The different signal combinations at the receiver nodes are investigated and compared, such as selection combining (SC) and maximum ratio combining (MRC) techniques. Then, the equivalent probability density function (PDF) and cumulative distribution function (CDF) of the network’s equivalent SINR are derived and discussed. Furthermore, expressions for the exact OP, AEP, and EC are derived and reviewed. In addition, asymptotic OP expressions are obtained for different case scenarios to gain an insight into the network parameters. Thirdly, multiple-input multiple-output (MIMO) UCRN is investigated under the influence of primary transmitter interference and CCI over Rayleigh fading channels. The transmit antenna selection and maximum ratio combining (TAS/MRC) techniques are considered for examining the performance of the secondary network. At first the equivalent SINR for the system is derived, then the exact and approximate expressions for the OP are derived and discussed. Fourthly, considering Nakagami-m fading channels, the performance of the UCRN is thoroughly studied with the consideration of the impact of primary network interference and CCI. The equivalent SINR for the secondary system is derived. Then, the system equivalent PDF and CDF are derived and discussed. Furthermore, the OP and AEP performances are investigated. Finally, for the cases mentioned above, numerical examples in conjunction with MatLab Monte Carlo simulations are provided to validate the derived results. The results show that CCI is one of the factors that severely reduces the UCRN performance. This can be more observable when the CCI power increases linearly with the transmission power of the secondary transmitter nodes. Furthermore, it was found that in a multi-user scenario the opportunistic SNR-based selection technique consideration can improve the performance of the network. Moreover, adaptive power allocation is found to give better results than equal power allocation. In addition, cooperative communication can be considered to be an effective way to combat the impact of transmission power limitation of the secondary network and interference power constraint. The multi-antenna schemes are another important consideration for enhancing the overall performance. In fact, despite the interference from the CCI and primary user sources, the multi-antennas scheme does not lose its advantage in the UCRN performance improvement
Description: PhD Thesis
Appears in Collections:School of Electrical and Electronic Engineering

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