Enhancing UAV Communication Performance: Analysis Using Interference Based Geometry Stochastic Model and Successive Interference Cancellation

Abstract

AbstractThe reliability and transmission quality in any wireless communication network is paramount. Unmanned Aerial Vehicle (UAV) communication networks are no exception to this fact. Hence, the need to investigate various communication technologies that will improve and be able to support the various applications of the UAV communication network. Correlated based stochastic models (CBSM) have been used to assess theoretical performances in UAV communication networks. CBSM has insufficient precision in a practical system. Geometry based stochastic channel models (GBSM) on the other hand, displays realistic channel features. These realistic channel features include pathloss, angle of arrival (AoA), angle of departure (AoD), etc. GBSM is better and ideal for channel modeling. This paper analyses the UAV communication networks in terms of their reliability and quality in transmission. MIMO-OFDM technology has been proposed to improve the UAV communication network. In this UAV network, the transmitters are modeled as cylindrical array (CA) because of its attribute of good regulation in 3-D space among others. A 3-D GBSM is proposed in the analysis. Also, an interference model has been presented in the UAV communication network. Results from this research show that MIMO-OFDM improves the reliability and quality of the UAV communication network. Generally, the capacity and BER increased with increasing number of antennas and SINR. However, beyond SINR of 25dB, we observed an irreducible error floor, that is, BER remained constant with increasing SINR. Successive Interference Cancellation (SIC) was therefore employed to minimize the irreducible error floor in the UAV communication network. This increased the average capacity and BER to about 25bits/s/Hz and \(10^{-8}\) respectively. KeywordsUAV communication networksMIMO-OFDMCylindrical arrayCBSMGBSMSuccessive interference cancellation