WiMAX urban coverage based on the Lee model and the Deygout diffraction method

Galván-Tejada, Giselle M.

doi:10.1109/iceee.2010.5608571

Cited by 9 publications

(2 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At present, signal propagation models include the Okumura-Hata model [15], COST-231 Hata model [16], LEE model [17], CCIR model [18], Egli model [19], Longley-Rice Model [20], and Kriging model [21]. The parameters in the Okumura Data model are easy to obtain and use.…”

Section: Introductionmentioning

confidence: 99%

“…The COST-231 Hata model can be used to estimate the path loss of cellular communication in urban environments [16]. The LEE model is suitable for measuring data, and the main parameters are easy to obtain and adjust, with high accuracy, a simple algorithm, and fast calculation [17]. The work in [20] used the Longley Rice model to predict the wireless signal propagation of rural railways, and the predicted results were compared with the measurement results using actual instruments.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Path Loss and Auxiliary Communication Analysis of VANET in Tunnel Environments

Jin

et al. 2023

Symmetry

View full text Add to dashboard Cite

Vehicular ad hoc network (VANET) communications face severe fading problems due to the signal reflections and diffractions within tunnels. Unlike the open road, the space of a tunnel is very limited, so VANET communication performance in a tunnel is seriously affected. In the process of signal transmission, the reflected signal is symmetrical with the incident signal after it is reflected by the road and the wall. In this paper, we establish a mathematical model of path loss for V2V (Vehicle-to-Vehicle) communication based on the principle of signal reflection symmetry in tunnels and considering several factors, such as the tunnel surface and the color of the tunnel wall. In addition, we use cooperative communication to form a virtual multiple-input multiple-output (V-MIMO) system, to improve the communication quality in tunnels. In the proposed system, the OBU (On-Board-unit) and RSU (Road-Side-Unit) share each other’s antennas, so that wireless cooperative communication can be employed, without increasing the number of antennas in a one-way tunnel. Therefore, this multipath fading internal electromagnetic wave propagation model can be used to improve performance. A deep reinforcement learning algorithm was used to solve the pairing problem to obtain a more accurate OBU and RSU pair, to form a V-MIMO system. Here, the RSU is regarded as an agent and interacts with the OBU in the tunnel. The optimal strategy was learned in a real-time changing simulation environment, and the experiment verified the convergence of the algorithm. The simulation results showed that, compared with the Q-learning based scheme, the optimal matching algorithm based on V-MIMO and a DQN (Deep Q-network) could effectively reduce the probability of transmission outages and improve the communication efficiency in tunnels.

show abstract