Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran,
Abstract
This paper proposes a new technique to design an optimal Multiple-Input Multiple-Output (MIMO) system, which is used to transmit data between vehicle and Road-Side Unit (RSU) In a vehicular sensor network, under the condition that a dominant Line-of-Sight(LoS) component exists in the channel matrix. Optimization criterion is the rank of the channel matrix and consequently the Shannon’s capacity. We show that by a proper selection of locations of antennas in a Uniform Linear Array (ULA), the capacity can be maximized in many points of the vehicle route. We see that the proposed model is more comprehensive than the previous ones, and it provides the possibility of investigating the capacity under any arbitrary route considered for the movement of the vehicle. The obtained LoS matrix is used in the Rician fading channel model and the performance of the system is evaluated based on the Ergodic and Outage capacity criteria. The results show that by utilizing this optimal design, the capacity in the case of existence of LoS is greater than the capacity of Rayleigh channel, most of the times.
Ali Madadi, M. R., mohammadi, A., & Abdiour, A. (2012). Design and Capacity Analysis of Vehicle-to-Roadside High-Rank LOS MIMO Channels in Vehicular Sensor Networks. Journal of Soft Computing and Information Technology, 1(1), 21-34.
MLA
Mohammad Reza Ali Madadi; Abas mohammadi; Abdolali Abdiour. "Design and Capacity Analysis of Vehicle-to-Roadside High-Rank LOS MIMO Channels in Vehicular Sensor Networks". Journal of Soft Computing and Information Technology, 1, 1, 2012, 21-34.
HARVARD
Ali Madadi, M. R., mohammadi, A., Abdiour, A. (2012). 'Design and Capacity Analysis of Vehicle-to-Roadside High-Rank LOS MIMO Channels in Vehicular Sensor Networks', Journal of Soft Computing and Information Technology, 1(1), pp. 21-34.
VANCOUVER
Ali Madadi, M. R., mohammadi, A., Abdiour, A. Design and Capacity Analysis of Vehicle-to-Roadside High-Rank LOS MIMO Channels in Vehicular Sensor Networks. Journal of Soft Computing and Information Technology, 2012; 1(1): 21-34.
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