On noise modeling for power line communications

Bert, Luca Di; Caldera, Peter; Schwingshackl, David; Tonello, Andrea M.

doi:10.1109/isplc.2011.5764408

Cited by 78 publications

(46 citation statements)

References 6 publications

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“…This paper explores an experimental adaptation of IPv6 over LoWPAN (6LoWPAN) features in PLC networks for monitoring and control applications within the HEMS. Since impulsive noise [29,30] has been shown to be the most dominant inhibitor in PLC systems [31,32], its effects are investigated in a wide range of scenarios, such as application data size and the number of smart appliances. Lastly, we highlight the fundamental consequences of 6LoPLC in HEMS applications and the variability of performance under the influence of impulsive noise.…”

Section: Introductionmentioning

confidence: 99%

Experimental Study of 6LoPLC for Home Energy Management Systems

et al. 2016

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Ubiquitous connectivity is already transforming residential dwellings into smart homes. As citizens continue to embrace the smart home paradigm, a new generation of low-rate and low-power communication systems is required to leverage the mass market presented by energy management in homes. Although Power Line Communication (PLC) technology has evolved in the last decade, the adaptation of PLC for constrained networks is not fully charted. By adapting some features of IEEE 802.15.4 and IPv6 over Low-power Wireless Personal Area Network (6LoWPAN) into power lines, this paper demonstrates a low-rate, low-power PLC system over the IPv6 network (referred to as 6LoPLC), for Home Energy Management System (HEMS) applications. The overall idea is to provide a framework for assessing various scenarios that cannot be easily investigated with the limited number of evaluation hardware available. In this respect, a network model is developed in NS-3 (Version 21) to measure several important characteristics of the designed system and then validated with experimental results obtained using the Hanadu evaluation kits. Following the good agreement between the two, the NS-3 model is utilised to investigate more complex scenarios and various use-cases, such as the effects of impulsive noise, the number of nodes and packet size on the latency and Bit Error Rate (BER) performances. We further demonstrate that for different network and application configurations, optimal data sizes exist. For instance, the results reveal that in order to guarantee 99% system reliability, the HEMS application data must not exceed 64 bytes. Finally, it is shown that with impulsive noise in a HEMS network comprising 50 appliances, provided the size of the payload does not exceed 64 bytes, monitoring and control applications incur a maximum latency of 238.117 ms and 248.959 ms, respectively; both of which are within acceptable limits.

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Section: Introductionmentioning

confidence: 99%

Experimental Study of 6LoPLC for Home Energy Management Systems

et al. 2016

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“…So far, the proposed models are either empirically derived (e.g., [6]) or formally derived (e.g., [7] and [8]). Furthermore, some of the proposals return to a variant or combination of the popular noise model based on Middleton's approach (e.g., [9] and [10]). The Middleton's class A model [11] has been commonly adopted as a practical way to represent noise in a PLC scenario.…”

Section: Introductionmentioning

confidence: 99%

On the Use of Alpha-Stable Distributions in Noise Modeling for PLC

Laguna-Sanchez

Lopez‐Guerrero

2015

IEEE Trans. Power Delivery

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Power-line communication (PLC) deals with the challenge of transmitting data over a channel impaired by background and impulsive noises. In this paper, we provide evidence that the marginal distribution of the noise found in PLC systems exhibits some statistical properties that can be well captured by using -stable distribution. Motivated by this result, we present a practical application of the -stable model to synthesize noise in the power line. Furthermore, we also show that this family of distributions is a suitable alternative in order to model the PLC background noise that is commonly assumed as Gaussian. Finally, we study the performance of an orthogonal frequency-division multiplexing communication system under both kinds of background noise (i.e., Gaussian and -stable). From these experiments, we conclude that if highly impulsive background traffic is mistakenly assumed as Gaussian in evaluation studies, the system performance is largely overestimated.Index Terms--stable noise model, orthogonal frequency-division multiplexing (OFDM) performance, power-line communication (PLC), PLC noise modeling.

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“…1, we consider PLC with the number of subchannels N = 1024, subchannel spacing B = 19.043 kHz, the target data rate (R Q/T ) of 100 Mbps and noise spectral density used in [8]. A frequency response of the channel is given by (1) with M = 15 and all channel parameters found in [6].…”

Section: Numerical Resultsmentioning

confidence: 99%

“…A inter-arrival time between occurrences of impulsive noise can be modeled by an exponential distribution while an impulse duration can be modeled with a two-term Gaussian model. The model of impulsive noise is detailed in [8].…”

Section: Numerical Resultsmentioning

confidence: 99%

Minimum-energy bit allocation over powerline OFDM channels

Kas-udom

Santipach

2013

2013 10th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technolo

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Abstract-We propose two bit allocations for a powerline OFDM channel to minimize a total transmission energy. The first is the optimal bit allocation derived for a deterministic channel model. The optimal number of bits allotted for each subchannel depends on channel gains, required data rate and transmission duration. For the second allocation, an equal number of bits is transmitted on a subchannel whose ratio between a noise power and squared channel gain is less than certain threshold. This onoff threshold-based bit allocation is also analyzed for a random channel model for which the closed-form expression for the total energy consumption is obtained in a large system limit. Numerical examples show that the optimal bit allocation could results in 83% reduction in transmission energy, compared to a uniform bit allocation and that the on-off allocation performs close to the optimum when a transmission time is short.

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On noise modeling for power line communications

Cited by 78 publications

References 6 publications

Experimental Study of 6LoPLC for Home Energy Management Systems

Experimental Study of 6LoPLC for Home Energy Management Systems

On the Use of Alpha-Stable Distributions in Noise Modeling for PLC

Minimum-energy bit allocation over powerline OFDM channels

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