Journal Article10.1002/ETT.2828
Heterogeneous next-generation wireless network interference model-and its applications
Nurul Huda Mahmood,Ferkan Yilmaz,Mohamed-Slim Alouini,Geir E. Oien +3 more
- 01 May 2014
- Vol. 25, Iss: 5, pp 563-575
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TL;DR: A generalised framework for the interference analysis of such a next-generation system is presented, built around a model developed for the statistical representation of the interference at the primary receivers, which is then used to evaluate various performance measures of the primary system.
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Abstract: Next-generation wireless systems facilitating better utilisation of the scarce radio spectrum have emerged as a response to inefficient and rigid spectrum assignment policies. These are comprised of intelligent radio nodes that opportunistically operate in the radio spectrum of existing primary systems, yet unwanted interference at the primary receivers is unavoidable. In order to design efficient next-generation systems and to minimise the adverse effect of their interference, it is necessary to realise how the resulting interference impacts the performance of the primary systems. In this work, a generalised framework for the interference analysis of such a next-generation system is presented where the next-generation transmitters may transmit randomly with different transmit powers. The analysis is built around a model developed for the statistical representation of the interference at the primary receivers, which is then used to evaluate various performance measures of the primary system. Applications of the derived interference model in designing the next-generation network system parameters are also demonstrated. Such approach provides a unified and generalised framework, the use of which allows a wide range of performance metrics can be evaluated. Findings of the analytical performance analyses are confirmed through extensive computer-based Monte-Carlo simulations. Copyright © 2014 John Wiley & Sons, Ltd.
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Citations
Full duplex communications in 5G small cells
Nurul Huda Mahmood,Marta Gatnau Sarret,Gilberto Berardinelli,Preben Mogensen +3 more
- 01 Jun 2017
TL;DR: The findings explicitly quantify how the gains from full duplex communication depend on the traffic profile and the inter-cell interference coupling, and make it an attractive potential technology component for the fifth generation dense small cell cellular system.
On the performance of one stage massive random access protocols in 5G systems
Nurul Huda Mahmood,Nuno K. Pratas,Thomas Jacobsen,Preben Mogensen +3 more
- 01 Sep 2016
TL;DR: A framework for the analysis of the one-stage massive access protocol is proposed in this paper, which allows to model and evaluate its performance with respect to important performance metrics for mMTC services.
Analysis of device-to-device communications with exclusion regions underlaying 5G networks
Xiaohui Xu,Haibo Wang,Hao Feng,Chengwen Xing +3 more
- 01 Jan 2015
TL;DR: Numerical results show that adopting ERs could both decrease the OP of cellular users and increase the network ASE, and a proper ER radius can be selected by network operators according to their target OP, D2D users' density, and the communication distance of D1D users.
22
Discrete-Time Markov Chain Analysis of Energy Efficiency in a CR Network Regarding Primary and Secondary Traffic With Primary User Returns
TL;DR: A new analytical framework is proposed in which the EE and collision probability are formulated and the traffic behaviors of PU and a general SU traffic are considered, and suitable values for sensing and transmission times are obtained to maximize the EE under collision and queue stability constraints.
16
•Proceedings Article
Throughput Analysis of Full Duplex Communication with Asymmetric Traffic in Small Cell Systems
Nurul Huda Mahmood,Gilberto Berardinelli,Preben Mogensen,Frank Frederiksen +3 more
- 11 Oct 2015
TL;DR: The potential throughput gains of full duplex communication over conventional half duplex transmission in a small cell network with asymmetric traffic conditions are investigated using network analysis tools from stochastic geometry and the findings are confirmed through computer-based Monte-Carlo simulations.
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