Noise correlation and its effect on capacity of inhome MIMO power line channels

Rende, Deniz; Nayagam, Arun; Afkhamie, K.H.; Yonge, Larry; Riva, Raffaele; Veronesi, D.; Osnato, Fabio; Bisaglia, P.

doi:10.1109/isplc.2011.5764451

Cited by 25 publications

(19 citation statements)

References 7 publications

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“…The decomposition into parallel and independent streams by means of the SVD illustrates the MIMO gain; instead of having one spatial stream in SISO, two independent spatial streams are available in a 2 × MIMO configuration with ≥ 2 doubling in average the MIMO capacity [9,12,13,21]. This fact is also verified by means of Figure 5; the first spatial stream shows less attenuation compared to the SISO channel; the second stream is slightly higher attenuated compared to SISO.…”

Section: Multiple-input Multiple-output (Mimo) Capabilities Withmentioning

confidence: 76%

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An Overview of the HomePlug AV2 Technology

Yonge

Abad

Afkhamie

et al. 2013

Journal of Electrical and Computer Engineering

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HomePlug AV2 is the solution identified by the HomePlug Alliance to achieve the improved data rate performance required by the new generation of multimedia applications without the need to install extra wires. Developed by industry-leading participants in the HomePlug AV Technical Working Group, the HomePlug AV2 technology provides Gigabit-class connection speeds over the existing AC wires within home. It is designed to meet the market demands for the full set of future in-home networking connectivity. Moreover, HomePlug AV2 guarantees backward interoperability with other HomePlug systems. In this paper, the HomePlug AV2 system architecture is introduced and the technical details of the key features at both the PHY and MAC layers are described. The HomePlug AV2 performance is assessed, through simulations reproducing real home scenarios.

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Section: Multiple-input Multiple-output (Mimo) Capabilities Withmentioning

confidence: 76%

“…This results in a higher spatial correlation of the MIMO-PLC channel than compared to radio MIMO channels. More information about the MIMO-PLC channel characteristics and channel modeling may be found in [6][7][8][9][10][11][12][13][14][15][16][17][18].…”

Section: Multiple-input Multiple-output (Mimo) Capabilities Withmentioning

confidence: 99%

An Overview of the HomePlug AV2 Technology

Yonge

Abad

Afkhamie

et al. 2013

Journal of Electrical and Computer Engineering

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“…2.6]. The resulting overall BB-PLC noise is generally modeled as a non-Gaussian [4]- [9], temporally correlated [8]- [12], non-stationary [9], [13]- [16] process, and MIMO BB-PLC noise components at different output ports are typically assumed to be correlated [2], [3], [20]. The channel impulse response (CIR) in BB-PLC channels is typically modeled as a multipath channel [9], [17] with periodic variations [13], [18], [19], where the channel outputs typically contain crosstalk from other wires [2], [3], [21]- [23].…”

Section: Introductionmentioning

confidence: 99%

On the Capacity of MIMO Broadband Power Line Communications Channels

Shlezinger

Shaked

Dabora

2018

IEEE Trans. Commun.

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Communications over power lines in the frequency range above 2 MHz, commonly referred to as broadband (BB) power line communications (PLC), has been the focus of increasing research attention and standardization efforts in recent years. BB-PLC channels are characterized by a dominant colored non-Gaussian additive noise, as well as by periodic variations of the channel impulse response and the noise statistics. In this work we study the fundamental rate limits for BB-PLC channels by bounding their capacity while accounting for the unique properties of these channels. We obtain explicit expressions for the derived bounds for several BB-PLC noise models, and illustrate the resulting fundamental limits in a numerical analysis.Index terms-Power line communications, MIMO systems, channel capacity. noise. We emphasize that all the works mentioned above, i.e., [7], [10], [26], derived expressions assuming Gaussian noise, while major works have concluded that the noise is non-Gaussian, see, e.g., [4], [8], [9]. We also note the work [28], which derived an approximate expression for the achievable rates when using Gaussian inputs and when using inputs with discrete amplitudes, for memoryless channels with additive GM noise, which were used for modelling communications in the presence of co-channel interference. Finally, we note that the capacity of PLC channels in the narrowband frequency range (0−500 kHz), modeled as additive noise channels in which the CIR is modeled as an LPTV filter and the noise is a cyclostationary Gaussian process, was derived in [29]. To the best of our knowledge, the fundamental limits for BB-PLC channels, accounting for their unique characteristics, including the non-Gaussianity and the temporal correlation of the noise, as well as the periodic variations of the CIR and of the noise statistics, have not been characterized to date. In this work we aim to address this gap. Main Contributions:In this work we study the fundamental rate limits of discrete-time (DT) BB-PLC channels. We consider a general channel model accounting for a wide range of the characteristics of BB-PLC channels, in which the CIR is modeled as an LPTV filter, and the additive noise is modeled as a temporally correlated non-Gaussian cyclostationary process 1 . Accordingly, we characterize an upper bound and two lower bounds on the capacity of these channels. We note that when the noise is not a Gaussian process, obtaining a closed-form expression for the capacity is generally a very difficult task, even for stationary and memoryless channels, and the common approach is to characterize upper and lower bounds on the capacity, see, e.g., [30, Ch. 7.4]. To facilitate the derivation, we first derive bounds on the capacity of a general LTI MIMO channel with additive non-Gaussian stationary noise. Then, we prove that the capacity of BB-PLC channels can be obtained from the capacity of non-Gaussian LTI MIMO channels by properly setting the parameters of the model, and finally we apply the bounds on the capacity of the latter model to ob...

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“…For example, [1] demonstrated a rate improvement by a factor of 2.2 compared to the single-input single-output (SISO) case which uses only two conductors. The authors of [2] studied the effect of noise correlation on the achievable rate and obtained as much as 40% rate increase for a scenario with two transmission and three receiver ports.…”

Section: Introductionmentioning

confidence: 99%

“…For specific realizations of the impedances, the parameters resistance R, resonance frequency, f 0 , and quality factor Q are generated independently and randomly from the uniform distribution on intervals [200, 1800] Ω,[2, 28] MHz, and[5, 25] respectively.…”

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confidence: 99%

Physical layer security in MIMO power line communication networks

Zhuang

Lampe

2014

18th IEEE International Symposium on Power Line Communications and Its Applications

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It has well been established that multiple-input multiple-output (MIMO) transmission using multiple conductors can improve the data rate of power line communication (PLC) systems. In this paper, we investigate whether the presence of multiple conductors could also facilitate the communication of confidential messages by means of physical layer security methods. In particular, this paper focuses on the secrecy capacity of MIMO PLC. Numerical experiments show that multi-conductor PLC networks can enable a more secure communication compared to the single conductor case. On the other hand, we demonstrate that the keyhole property of PLC channels generally diminishes the secure communication capability compared to what would be achieved in a similar wireless communications setting.

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Noise correlation and its effect on capacity of inhome MIMO power line channels

Cited by 25 publications

References 7 publications

An Overview of the HomePlug AV2 Technology

An Overview of the HomePlug AV2 Technology

On the Capacity of MIMO Broadband Power Line Communications Channels

Physical layer security in MIMO power line communication networks

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