Linear Combining of Nonlinear Preprocessors for OFDM-Based Power-Line Communications

Juwono, Filbert H.; Guo, Qinghua; Chen, Yifan; Xu, Lingyun; Huang, Defeng; Wong, Kit Po

doi:10.1109/tsg.2015.2403953

Cited by 29 publications

(26 citation statements)

References 18 publications

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“…Particularly, although communication signals are transmitted at high frequencies (ie, in the MHz band), power cables are designed to transfer low‐frequency power signals. To this end, a great amount of effort has been put on analyzing the performance of PLC systems as well as on presenting new transmission and reception schemes …”

Section: Introductionmentioning

confidence: 99%

“…The background noise includes both colored and narrowband components. Despite the paramount impact of noise in the performance of PLC systems, its non‐Gaussian nature has been overlooked in several studies, where, for the sake of simplicity, the background noise has been described as an additive white Gaussian process . Interestingly, experimental results have revealed that the envelope of the background noise follows a Nakagami‐ m distribution .…”

Section: Introductionmentioning

confidence: 99%

“…To this end, a great amount of effort has been put on analyzing the performance of PLC systems [4][5][6][7][8][9][10][11][12][13][14][15][16] as well as on presenting new transmission and reception schemes. 17,18 In general, the additive channel noise in PLC is classified into two categories: the background noise and the impulsive noise. 4,16 The impulsive noise is of short duration, has a high power spectral density, and is commonly represented by a Poisson or Middleton Class A distribution.…”

Section: Introductionmentioning

confidence: 99%

“…Despite the paramount impact of noise in the performance of PLC systems, its non-Gaussian nature has been overlooked in several studies, where, for the sake of simplicity, the background noise has been described as an additive white Gaussian process. 18 Interestingly, experimental results have revealed that the envelope of the background noise follows a Nakagami-m distribution. 4 Due to the fact that Nakagami-m contains the half Gaussian, the Rayleigh, and the Gaussian distribution as special cases, it has been proven to be a robust and general model for the description of the noise particularities in PLC systems.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Error performance of power line communications in the presence of Nakagami‐m background noise

Papanikolaou

Ntouni

Boulogeorgos

et al. 2018

Trans Emerging Tel Tech

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This paper studies the error performance of power line communication (PLC) systems, in the presence of background noise with Nakagami‐m distributed envelope and uniformly distributed phase. In this sense, we present closed‐form expressions for the symbol error rate (SER) of PLC systems using binary pulse amplitude modulation and generalize the analysis to accommodate the M‐ary pulse amplitude modulation. In addition, novel closed‐form expressions for the SER upper bound of rectangular quadrature amplitude modulation PLC systems are derived. Interestingly, these expressions can be considered as tight SER approximations in the high–signal‐to‐noise ratio region and, thus, can efficiently evaluate the operational bound of a PLC system.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Error performance of power line communications in the presence of Nakagami‐m background noise

Papanikolaou

Ntouni

Boulogeorgos

et al. 2018

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…19 Nonlinear preprocessing techniques that include clipping, nulling (blanking), hybrid clipping/blanking, and deep clipping are typically used at the transmitter of OFDM systems to reduce the peak-to-average power ratio but can also be used at the receiver of communication systems when the channel is affected by impulsive noise (IN) such as in the case of PLC. [20][21][22][23] The signal clipping method involves limiting the possible amplitude values of a waveform to a specified threshold value T c . Clipping has been used successfully for combating IN in multicarrier systems operating over noisy environments such as terrestrial digital video broadcasting 24,25 as well as the PLC channel.…”

mentioning

confidence: 99%

Time diversity scheme and adaptive signal clipping with blanking applied to G3 systems for narrowband power‐line communications

Rivard

Cheng

2019

Int J Communication

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Summary In this paper, an investigation into the behavior of modern narrowband power‐line communication systems when concatenated with both a fountain code named Luby transform code and a combination of nonlinear preprocessing techniques called signal clipping with blanking is presented. The new systems can be used in applications such as the automatic meter reading component of smart grid technology. Testing is performed on a range of systems provided by the G3 standard and the results show that a bit error rate improvement can be achieved with the correct encoder/decoder settings. The recommended settings include an adaptive technique that uses Gaussian elimination for Luby transform code decoding and code rates that depend on the system specifications used. From there, it is shown that a further improvement is achieved when both the Luby transform code and adaptive signal clipping/blanking based on signal power are combined. It is found that these modifications present a complexity trade‐off, which is higher on the receiver side. This added complexity can be well‐tolerated in automatic meter‐reading systems because of the star topology and asymmetric nature of the network, which has a centralized agent acting as a receiver that collects data from various transmitter nodes.

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An intelligent impulsive noise mitigation with deep learning method

Yang,

Qian,

Wang

et al. 2024

Int Journal of Mech Sys Dyn

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To enable message transmission among sensors and equipment, power line communication (PLC) is a widely adopted smart grid. However, due to the occurrence of impulsive noise (IN), reliable transmissions over PLC channels in the smart grid are challenging. Therefore, in this paper, we propose an adaptive noise mitigation scheme to clip the IN with the sliding window‐based method, where the altitude of the received signal in the current time slots is obtained by computing the average altitude of signals in the previous and next time slots. To detect the states of IN and dynamically estimate the power threshold of signals for the IN mitigation scheme, we develop an intelligent algorithm based on the long short‐term memory network. To prevent the useful signals from being eliminated as IN signals, we propose the accelerated proximal gradient method (APGM) based on tone reservation to reduce the peak‐to‐average power ratio (PAPR) for the transmitting signals with low computational complexity. In addition, the closed‐form expression of the bit error rate (BER) is derived for the proposed sliding window‐based IN mitigation scheme according to the probability density function of the IN. Simulation results demonstrate that the proposed IN mitigation scheme achieves a better BER performance than the conventional IN mitigation schemes. In addition, the APGM aided by IN mitigation can further improve BER performance due to the PAPR reduction.

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Linear Combining of Nonlinear Preprocessors for OFDM-Based Power-Line Communications

Cited by 29 publications

References 18 publications

Error performance of power line communications in the presence of Nakagami‐m background noise

Error performance of power line communications in the presence of Nakagami‐m background noise

Time diversity scheme and adaptive signal clipping with blanking applied to G3 systems for narrowband power‐line communications

An intelligent impulsive noise mitigation with deep learning method

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