Antenna Array Synthesis Through Particle Swarm Optimization for V2V Communications in Urban Intersections

Becerra, Raimundo; Bolufé, Sandy; Kang, Hojin; Azurdia-Meza, César A.

doi:10.1109/latincom50620.2020.9282295

Cited by 1 publication

(3 citation statements)

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“…It is worth mentioning that in [ 18 ], MSCPSO was used to optimized the parameters of a

antenna array using PSO, and the results of the unknown positions were interpolated. However, the latter was evaluated using different restrictions compared to the ones in this manuscript.…”

Section: Resultsmentioning

confidence: 99%

“…However, the latter was evaluated using different restrictions compared to the ones in this manuscript. In particular, the authors in [ 18 ] restricted the position of the vehicle in the road, but this restriction was discarded in our manuscript since for safety applications, every possible position is important. New results for MSCPSO were hence computed in this manuscript.…”

Section: Resultsmentioning

confidence: 99%

“…For instance, Reference [ 17 ] presented preliminary results on optimizing values for a

antenna array for urban V2V communications using GA, and it was shown to outperform the baseline isotropic antenna. Similarly, in [ 18 ], the values of a

antenna array were optimized by using particle swarm optimization (PSO) and interpolating the results for unknown positions. This method has also been shown to outperform an isotropic antenna.…”

Section: Introductionmentioning

confidence: 99%

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Neuroevolution-Based Adaptive Antenna Array Beamforming Scheme to Improve the V2V Communication Performance at Intersections

Kim

Becerra

Bolufé

et al. 2021

Sensors

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The opportunistic exchange of information between vehicles can significantly contribute to reducing the occurrence of accidents and mitigating their damages. However, in urban environments, especially at intersection scenarios, obstacles such as buildings and walls block the line of sight between the transmitter and receiver, reducing the vehicular communication range and thus harming the performance of road safety applications. Furthermore, the sizes of the surrounding vehicles and weather conditions may affect the communication. This makes communications in urban V2V communication scenarios extremely difficult. Since the late notification of vehicles or incidents can lead to the loss of human lives, this paper focuses on improving urban vehicle-to-vehicle (V2V) communications at intersections by using a transmission scheme able of adapting to the surrounding environment. Therefore, we proposed a neuroevolution of augmenting topologies-based adaptive beamforming scheme to control the radiation pattern of an antenna array and thus mitigate the effects generated by shadowing in urban V2V communication at intersection scenarios. This work considered the IEEE 802.11p standard for the physical layer of the vehicular communication link. The results show that our proposal outperformed the isotropic antenna in terms of the communication range and response time, as well as other traditional machine learning approaches, such as genetic algorithms and mutation strategy-based particle swarm optimization.

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“…It is worth mentioning that in [ 18 ], MSCPSO was used to optimized the parameters of a

antenna array using PSO, and the results of the unknown positions were interpolated. However, the latter was evaluated using different restrictions compared to the ones in this manuscript.…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…For instance, Reference [ 17 ] presented preliminary results on optimizing values for a

antenna array for urban V2V communications using GA, and it was shown to outperform the baseline isotropic antenna. Similarly, in [ 18 ], the values of a

antenna array were optimized by using particle swarm optimization (PSO) and interpolating the results for unknown positions. This method has also been shown to outperform an isotropic antenna.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation