Propagation channel models for 5G mobile networks. Simulation and measurements of 5G propagation channel models for indoor and outdoor environments covering both LOS and NLOS Scenarios
End of Embargo2020-10-31
SupervisorAbd-Alhameed, Raed A.
Line of Sight (LOS)
Non-Line of Sight (NLOS)
Shooting and Bouncing Ray (SBR)
The University of Bradford theses are licenced under a Creative Commons Licence.
InstitutionUniversity of Bradford
DepartmentFaculty of Engineering and Informatics
MetadataShow full item record
AbstractAt present, the current 4G systems provide a universal platform for broadband mobile services; however, mobile traffic is still growing at an unprecedented rate and the need for more sophisticated broadband services is pushing the limits on current standards to provide even tighter integration between wireless technologies and higher speeds. This has led to the need for a new generation of mobile communications: the so-called 5G. Although 5G systems are not expected to penetrate the market until 2020, the evolution towards 5G is widely accepted to be the logical convergence of internet services with existing mobile networking standards leading to the commonly used term “mobile internet” over heterogeneous networks, with several Gbits/s data rate and very high connectivity speeds. Therefore, to support highly increasing traffic capacity and high data rates, the next generation mobile network (5G) should extend the range of frequency spectrum for mobile communication that is yet to be identified by the ITU-R. The mm-wave spectrum is the key enabling feature of the next-generation cellular system, for which the propagation channel models need to be predicted to enhance the design guidance and the practicality of the whole design transceiver system. The present work addresses the main concepts of the propagation channel behaviour using ray tracing software package for simulation and then results were tested and compared against practical analysis in a real-time environment. The characteristics of Indoor-Indoor (LOS and NLOS), and indoor-outdoor (NLOS) propagations channels are intensively investigated at four different frequencies; 5.8 GHz, 26GHz, 28GHz and 60GHz for vertical polarized directional, omnidirectional and isotropic antennas patterns. The computed data achieved from the 3-D Shooting and Bouncing Ray (SBR) Wireless Insite based on the effect of frequency dependent electrical properties of building materials. Ray tracing technique has been utilized to predict multipath propagation characteristics in mm-wave bands at different propagation environments. Finally, the received signal power and delay spread were computed for outdoor-outdoor complex propagation channel model at 26 GHz, 28 GHz and 60GHz frequencies and results were compared to the theoretical models.
NotesThe full text will be available at the end of the embargo, 31st October 2020.
Showing items related by title, author, creator and subject.
Shedding light on the variability of optical skin properties: finding a path towards more accurate prediction of light propagation in human cutaneous compartmentsMignon, Charles; Tobin, Desmond J.; Zeitouny, M.; Uzunbajakava, N.E. (2018-01)Finding a path towards a more accurate prediction of light propagation in human skin remains an aspiration of biomedical scientists working on cutaneous applications both for diagnostic and therapeutic reasons. The objective of this study was to investigate variability of the optical properties of human skin compartments reported in literature, to explore the underlying rational of this variability and to propose a dataset of values, to better represent an in vivo case and recommend a solution towards a more accurate prediction of light propagation through cutaneous compartments. To achieve this, we undertook a novel, logical yet simple approach. We first reviewed scientific articles published between 1981 and 2013 that reported on skin optical properties, to reveal the spread in the reported quantitative values. We found variations of up to 100-fold. Then we extracted the most trust-worthy datasets guided by a rule that the spectral properties should reflect the specific biochemical composition of each of the skin layers. This resulted in the narrowing of the spread in the calculated photon densities to 6-fold. We conclude with a recommendation to use the identified most robust datasets when estimating light propagation in human skin using Monte Carlo simulations. Alternatively, otherwise follow our proposed strategy to screen any new datasets to determine their biological relevance.
Probability Distribution of Rician K-Factor in Urban, Suburban and Rural Areas Using Real World Captured DataAbd-Alhameed, Raed A.; Jones, Steven M.R.; Noras, James M.; Zhu, Shaozhen (Sharon); Ghazaany, Tahereh S.; Van Buren, T.; Wilson, J.; Suggett, T.; Marker, S. (2014-07)The Rician K-factor of the vehicle-to-vehicle (V2V) wireless propagation channel is estimated using a moment-based method on the envelope of measured pulse data. The measurements were carried out under vehicle-to-vehicle wireless communication channel condition with car rooftop antenna heights at one end of the link and very low antenna height at the other end. Data captured from typical urban, suburban and rural areas are analyzed and the K-factor probability density function is generated for each scenario to give an insight into the V2V channel behavior. For all three areas, the majority of K values are found to be within the range of -10 to +10 dB. The K-factor distributions are close to normal with mean values of 1.8, 2.6 and 3 dB respectively for urban, suburban and rural area.
Malware Propagation Modelling in Peer-to-Peer Networks: A ReviewMusa, Ahmad S.; Al-Mohannadi, Hamad; Alhamar, J. (2018)Peer-to-Peer (P2P) network is increasingly becoming the most important means of trading content throughout the last years due to the constant evolvement of the cyber world. This popularity made the P2P network susceptible to the spread of malware. The detection of the cause of malware propagation is now critical to the survival of P2P networks. This paper offers a review of the current relevant mathematical propagation models that have been proposed to date to predict the propagation behavior of a malware in a P2P network. We analyzed the models proposed by researchers and experts in the field by evaluating their limitations and a possible alternative for improving the analysis of the expected behavior of a malware spread.