Uplink performance analysis for millimeter wave cellular networks with clustered users

Muhammad, Nor Aishah and Anwar Apandi, Nur Ilyana and Li, Yonghui and Seman, Norhudah (2020) Uplink performance analysis for millimeter wave cellular networks with clustered users. IEEE Transactions On Vehicular Technology, 69 (6). pp. 6178-6188. ISSN 0018-9545

[img] Text
UPLINK PERFORMANCE ANALYSIS FOR MILLIMETER WAVE.PDF
Restricted to Registered users only

Download (1MB)

Abstract

The upcoming wireless cellular networks will make use of higher segments of the frequency spectrum, i.e., millimeter wave (MMW) bands, for enabling extremely high data rates to support content-rich applications. In this paper, we investigate the uplink performance of MMW cellular networks with clustered users. By modeling the locations of users as a Poisson Cluster Process (PCP), we derive tractable expressions to evaluate the signal to interference-and-noise-ratio (SINR) coverage probability for two user association strategies, i.e., the closest selection (CS) strategy, where the nearest LoS BS serves the user and the strongest-selection (SS) strategy, where the user communicates with the BS that provides the most significant received signal among all BSs. Numerical results are provided to validate the accuracy of the analytical model under various system parameters. The results show that regarding SINR coverage probability, the SS strategy outperforms the CS strategy in the environment with dense blockages. The results also demonstrate that the moderate fractional power control (FPC) factors should be used at the low SINR thresholds, while full FPC is optimal for the high SINR thresholds

Item Type: Article
Uncontrolled Keywords: Millimeter Wave Communications, Wireless Cellular Networks, Stochastic Geometry, Poisson Cluster Process
Divisions: Faculty of Electrical Engineering > Department of Mechatronics Engineering
Depositing User: Norfaradilla Idayu Ab. Ghafar
Date Deposited: 13 May 2022 11:07
Last Modified: 13 May 2022 11:07
URI: http://eprints.utem.edu.my/id/eprint/24768
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item