Mitigating adjacent channel interference in vehicular communication systems

Almeida, João; Alam, Muhammad; Ferreira, Joaquim; Oliveira, Arnaldo S. R.

doi:10.1016/j.dcan.2016.03.001

Cited by 16 publications

(11 citation statements)

References 15 publications

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“…Recently, a number of research programs targeted at increasing road safety and traffic efficiency have been started. EV communications are the subject of one of the works mentioned above, which is [15]. If the user is looking for the most recent research on vehicular communication, look no further than T-VNets [16].…”

Section: Related Workmentioning

confidence: 99%

Internet of Things-Based Intelligent Ontology Model for Safety Purpose Using Wireless Networks

Shakya

Sundar

Kushwaha

et al. 2022

Wireless Communications and Mobile Computing

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Intelligent transportation systems (ITS) are a newer trend in technology that improve the safety and performance in transportation systems. The exchange of information is considered as one of the key elements for ITS since it involves communication between vehicles and other components of ITS on road. On other hand, the data collections via Internet of Things (IoT) sensors play a major role for data collection and transmission between the vehicles and road segments in ITS. The data collection provides the current traffic and weather conditions that is considered necessary for driving in traffic. However, energy savings is one of the predominant objectives of electric vehicle (EV) while it is connected with ITS. In this research, we propose an ontology-based architecture for EVs using the data collected from IoT sensor network, which is intended to improve the overall driving experience. The system uses IoT sensor data to execute a range of activities in order to ensure the driver safety and comfort while on the road. The simulation is conducted on an Eclipse SUMO simulator, and the performance is reported. The results of simulation shows that the proposed intelligent model on making decisions along with weather and traffic conditions is reported efficient than existing ITS models.

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Section: Related Workmentioning

confidence: 99%

Internet of Things-Based Intelligent Ontology Model for Safety Purpose Using Wireless Networks

Shakya

Sundar

Kushwaha

et al. 2022

Wireless Communications and Mobile Computing

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“…High-level management scheme: A manager can change the operating service channel and use a different SCH when the interference level increases [29]. Active channel management would allow more vehicles to be served with lower interference.…”

Section: B Scalabilitymentioning

confidence: 99%

CAD3: Edge-facilitated Real-time Collaborative Abnormal Driving Distributed Detection

Alhilal

Braud

Sut

et al. 2021

2021 IEEE 41st International Conference on Distributed Computing Systems (ICDCS)

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Speeding, slowing down, and sudden acceleration are the leading causes of fatal accidents on highways. Anomalous driving behavior detection can improve road safety by informing drivers who are in the vicinity of dangerous vehicles. However, detecting abnormal driving behavior at the city-scale in a centralized fashion results in considerable network and computation load, that would significantly restrict the scalability of the system. In this paper, we propose CAD3, a distributed collaborative system for road-aware and driver-aware anomaly driving detection. CAD3 considers a decentralized deployment of edge computation nodes on the roadside and combines collaborative and context-aware computation with low-latency communication to detect and inform nearby drivers of unsafe behaviors of other vehicles in real-time. Adjacent edge nodes collaborate to improve the detection of abnormal driving behavior at the city-scale. We evaluate CAD3 with a physical testbed implementation. We emulate realistic driving scenarios from a real driving data set of 3,000 vehicles, 214,000 trips, and 18 million trajectories of private cars in Shenzhen, China. At the microscopic (road) level, CAD3 significantly improves the accuracy of detection and lowers the number of potential accidents caused by false negatives up to four times and 24 times as compared to distributed standalone and centralized models, respectively. CAD3 can scale up to 256 vehicles connected to a single node while keeping the end-to-end latency under 50 ms and a required bandwidth below 5 mbps. At the mesoscopic (driver-trip) level, CAD3 performs stable and accurate detection over time, owing to local RSU interaction. With a dense deployment of edge nodes, CAD3 can scale up to the size of Shenzhen, a megalopolis of 12 million inhabitant with over 2 million concurrent vehicles at peak hours.

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“…The ACI caused by a transmitter depends mainly upon the power amplifier, the coding and modulation scheme, and clipping threshold [26]. In [27], the authors propose a twostage low pass FIR filter method to reduce ACI in V2V communication. However, in order to find out a standard ACI model for single carrier frequency division multiple access (SCFDMA) signal, we did extensive simulations and the result for 1% clipping threshold is shown as blue colored curve in Fig.…”

Section: B Aci Modelmentioning

confidence: 99%

Scheduling and Power Control for V2V Broadcast Communications With Co-Channel and Adjacent Channel Interference

et al. 2019

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This paper investigates how to mitigate the impact of both co-channel interference and adjacent channel interference (ACI) on vehicle-to-vehicle (V2V) broadcast communication by scheduling and power control. The optimal joint scheduling and power control problem, with the objective to maximize the number of connected vehicles, is formulated as a mixed integer programming problem with a linear objective and a quadratic constraint. From the joint formulation, we derive (a) the optimal scheduling problem for fixed transmit powers as a Boolean linear programming problem and (b) the optimal power control problem for a fixed schedule as a mixed integer linear programming problem. Optimal schedules and power values can, for smaller-size instances of the problem, be computed by solving first (a) and then (b). To handle larger-size instances of the problem, we propose heuristic scheduling and power control algorithms with reduced computational complexity. Simulation results indicate that the heuristic scheduling algorithm yields significant performance improvements compared to the baseline block-interleaver scheduler and that performance is further improved by the heuristic power control algorithm. Moreover, the heuristic algorithms perform close to the optimal scheme for small instances of the problem.

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Mitigating adjacent channel interference in vehicular communication systems

Cited by 16 publications

References 15 publications

Internet of Things-Based Intelligent Ontology Model for Safety Purpose Using Wireless Networks

Internet of Things-Based Intelligent Ontology Model for Safety Purpose Using Wireless Networks

CAD3: Edge-facilitated Real-time Collaborative Abnormal Driving Distributed Detection

Scheduling and Power Control for V2V Broadcast Communications With Co-Channel and Adjacent Channel Interference

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