TY - JOUR
T1 - Rician K-Factor-Based Analysis of XLOS Service Probability in 5G Outdoor Ultra-Dense Networks
AU - Chergui, Hatim
AU - Benjillali, Mustapha
AU - Alouini, Mohamed-Slim
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2018/10/9
Y1 - 2018/10/9
N2 - In this letter, we introduce the concept of Rician K-factor-based radio resource and mobility management for fifth generation (5G) ultra-dense networks (UDN), where the information on the gradual visibility between the new radio node B (gNB) and the user equipment (UE)—dubbed X-line-of-sight (XLOS)—would be required. We therefore start by presenting the XLOS service probability as a new performance indicator; taking into account both the UE serving and neighbor cells. By relying on a lognormal K-factor model, a parametric expression of the XLOS service probability in a 5G outdoor UDN is derived, where the link between network parameters and the availability of a XLOS condition is established. The obtained formula is given in terms of the multivariate Fox H-function, wherefore we develop a fast graphical processing unit (GPU)-enebled MATLAB code. Residue theory is then applied to infer the relevant asymptotic behavior and show its practical implications. Finally, numerical results are provided for various network configurations, and underpinned by extensive Monte-Carlo simulations.
AB - In this letter, we introduce the concept of Rician K-factor-based radio resource and mobility management for fifth generation (5G) ultra-dense networks (UDN), where the information on the gradual visibility between the new radio node B (gNB) and the user equipment (UE)—dubbed X-line-of-sight (XLOS)—would be required. We therefore start by presenting the XLOS service probability as a new performance indicator; taking into account both the UE serving and neighbor cells. By relying on a lognormal K-factor model, a parametric expression of the XLOS service probability in a 5G outdoor UDN is derived, where the link between network parameters and the availability of a XLOS condition is established. The obtained formula is given in terms of the multivariate Fox H-function, wherefore we develop a fast graphical processing unit (GPU)-enebled MATLAB code. Residue theory is then applied to infer the relevant asymptotic behavior and show its practical implications. Finally, numerical results are provided for various network configurations, and underpinned by extensive Monte-Carlo simulations.
UR - http://hdl.handle.net/10754/629969
UR - https://ieeexplore.ieee.org/document/8486668
UR - http://www.scopus.com/inward/record.url?scp=85054692732&partnerID=8YFLogxK
U2 - 10.1109/LWC.2018.2874654
DO - 10.1109/LWC.2018.2874654
M3 - Article
SN - 2162-2337
VL - 8
SP - 428
EP - 431
JO - IEEE Wireless Communications Letters
JF - IEEE Wireless Communications Letters
IS - 2
ER -