Influence of impulsive noise from lifts on orthogonal frequency‐division multiplexing digital radio mondiale signals

Landa, Iratxe; Díez-Bravo, Ana; Vélez, Manuel; Arrinda, Amaia

doi:10.1049/iet-com.2018.5458

“…Impulsive phenomena, when the noise varies subtly and greatly from the mean in a short period, can jeopardize the performance of solutions and strategies based on the traditional Gaussian approach [62][63][64]. Impulsive noise is present in several scenarios of communication systems, such as powerline communications [81], OFDM in wireless networks [82], and sensor networks [83]. Unlike the Gaussian, the alpha-stable distribution can have infinite variance, so it better represents data with heavy tails [61,84].…”

Section: Impulsive Noise and Alpha-stable Modelmentioning

confidence: 99%

Evaluation of Acoustic Noise Level and Impulsiveness Inside Vehicles in Different Traffic Conditions

Flor

¹

,

Pena

²

,

Oliveira

³

et al. 2022

Sensors

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Recently, the issue of sound quality inside vehicles has attracted interest from both researchers and industry alike due to health concerns and also to increase the appeal of vehicles to consumers. This work extends the analysis of interior acoustic noise inside a vehicle under several conditions by comparing measured power levels and two different models for acoustic noise, namely the Gaussian and the alpha-stable distributions. Noise samples were collected in a scenario with real traffic patterns using a measurement setup composed of a Raspberry Pi Board and a microphone strategically positioned. The analysis of the acquired data shows that the observed noise levels are higher when traffic conditions are good. Additionally, the interior noise presented considerable impulsiveness, which tends to be more severe when traffic is slower. Finally, our results suggest that noise sources related to the vehicle itself and its movement are the most relevant ones in the composition of the interior acoustic noise.

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“…Cognitive Radio Sensor Networks (CRSN) emerged as a new method of addressing the same problems found in conventional networks as a result of some of these noteworthy characteristics of CR. A cognitive radio transceiver and sensing system network (CRSN) is described as a network of closely arranged sensor nodes [12][13][14]. It can detect an event, locate accessible channels, and creatively link to other nodes so that the characteristics may send a signal to a distant sink right away.…”

Section: Introductionmentioning

confidence: 99%

Design of an adaptive CRSN using OFDM

Kandasamy¹,

Ravi²

2022

Wireless Netw

0

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Cognitive Radio (CR) is a novel concept that enables wireless devices to detect and adapt to their surroundings in order to enhance communication quality. The cognitive radio sensor network (CRSN) has proved to be a cost-effective solution to the spectrum constraints that wireless sensor networks (WSN). Optimizing the optimum packet size is regarded to be an essential energy constrained issue to address the practical implementation of CRSN out of all the difficulties. Small packets generate data traffic in device-to-device communication, a flexible way for transferring data in wireless networks, while big packets may cause data bit corruption, requiring retransmission at a greater frequency. This will not allow access from the secondary network to the main network, since it may cause further disturbance. To maximise the WSN's energy efficiency, the optimum packet size for CRSN should be utilised while keeping the same degree of interference as the primary licenced users (PU). The purpose of this article is to examine formulations for small, medium, and large packet sizes in order to determine the optimum packet size for adaptive CRSN. To do so, CR requires a flexible physical layer capable of carrying out the necessary tasks. This article examines the performance of CR systems that use the Orthogonal Frequency Division Multiplexing (OFDM) technique, which is a possible transmission technology for CR. Interference delays are minimised, and the channels are ultimately utilised effectively. This article shows that medium-sized packets are the optimum choice for achieving the greatest performance on the Cognitive Radio Sensor Network (CRSN). The Jellyfish Search Optimization algorithm (JSO) and the hybrid Momentum Search Algorithm (MSA) are hybridised, and results are achieved. This makes it possible to calculate precise packet sizes. The suggested approach decision outperforms existing methods like the Group Sparse Optimization algorithm and the Throughput Maximization Algorithm. The MATLAB / SIMULINK Platform were used to get the results.

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Data Packet Optimization Incognitive Radio Sensor Network Using Ofdm

Kandasamy¹,

Ravi²

2022

Preprint

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Cognitive Radio (CR) is a novel concept that enables wireless devices to detect and adapt to their surroundings in order to enhance communication quality. The cognitive radio sensor network (CRSN) has proved to be a cost-effective solution to the spectrum constraints that wireless sensor networks (WSN). Optimizing the optimum packet size is regarded to be an essential energy constrained issue to address the practical implementation of CRSN out of all the difficulties. Small packets generate data traffic in device-to-device communication, a flexible way for transferring data in wireless networks, while big packets may cause data bit corruption, requiring retransmission at a greater frequency. This will not allow access from the secondary network to the main network, since it may cause further disturbance. To maximise the WSN's energy efficiency, the optimum packet size for CRSN should be utilised while keeping the same degree of interference as the primary licenced users (PU). The purpose of this article is to examine formulations for small, medium, and large packet sizes in order to determine the optimum packet size for adaptive CRSN. To do so, CR requires a flexible physical layer capable of carrying out the necessary tasks. This article examines the performance of CR systems that use the Orthogonal Frequency Division Multiplexing (OFDM) technique, which is a possible transmission technology for CR. Interference delays are minimised, and the channels are ultimately utilised effectively. This article shows that medium-sized packets are the optimum choice for achieving the greatest performance on the Cognitive Radio Sensor Network (CRSN). The Jellyfish Search Optimization algorithm (JSO) and the hybrid Momentum Search Algorithm (MSA) are hybridised, and results are achieved. This makes it possible to calculate precise packet sizes. The suggested approach decision outperforms existing methods like the Group Sparse Optimization algorithm and the Throughput Maximization Algorithm. The MATLAB / SIMULINK Platform were used to get the results.

show abstract

Influence of impulsive noise from lifts on orthogonal frequency‐division multiplexing digital radio mondiale signals

Cited by 3 publications

References 27 publications

Evaluation of Acoustic Noise Level and Impulsiveness Inside Vehicles in Different Traffic Conditions

Evaluation of Acoustic Noise Level and Impulsiveness Inside Vehicles in Different Traffic Conditions

Design of an adaptive CRSN using OFDM

Data Packet Optimization Incognitive Radio Sensor Network Using Ofdm

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