The Experts below are selected from a list of 11196 Experts worldwide ranked by ideXlab platform
M Kavehrad - One of the best experts on this subject based on the ideXlab platform.
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high frequency characteristics of overhead multiconductor power lines for broadband communications
IEEE Journal on Selected Areas in Communications, 2006Co-Authors: P Amirshahi, M KavehradAbstract:This paper presents a Channel model suitable for multiwire overhead medium voltage lines. This model, incorporating ground admittance, is more appropriate at higher frequencies than predicted by Carson's model of 1926. The proposed model is further used to evaluate the multipath Channel Impulse Response and associated capacity limit in sample power distribution grids for applications in broadband over power lines communications. For a sample grid model, comparison is made to the capacity value predicted based on the Carson's model, and it is demonstrated that the older model underestimates the potential of the overhead lines for broadband transmissions, significantly.
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transmission Channel model and capacity of overhead multi conductor medium voltage power lines for broadband communications
Consumer Communications and Networking Conference, 2005Co-Authors: P Amirshahi, M KavehradAbstract:A Channel model suitable for multi-wire overhead medium-voltage lines is proposed. The model, incorporating ground admittance, is more appropriate for broadband communications. This model is then employed in order to evaluate the multipath Channel Impulse Response and the associated transmission capacity limit in actual overhead medium-voltage power distribution networks for broadband power-line communications applications.
Alexander Duncan - One of the best experts on this subject based on the ideXlab platform.
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joint Channel estimation and impulsive noise mitigation in underwater acoustic ofdm communication systems
IEEE Transactions on Wireless Communications, 2017Co-Authors: Peng Chen, Yue Rong, Sven Nordholm, Alexander DuncanAbstract:Impulsive noise occurs frequently in underwater acoustic (UA) Channels and can significantly degrade the performance of UA orthogonal frequency-division multiplexing (OFDM) systems. In this paper, we propose two novel compressed sensing based algorithms for joint Channel estimation and impulsive noise mitigation in UA OFDM systems. The first algorithm jointly estimates the Channel Impulse Response and the impulsive noise by utilizing pilot subcarriers. The estimated impulsive noise is then converted to the time domain and removed from the received signals. We show that this algorithm reduces the system bit-error-rate through improved Channel estimation and impulsive noise mitigation. In the second proposed algorithm, a joint estimation of the Channel Impulse Response and the impulsive noise is performed by exploiting the initially detected data. Then, the estimated impulsive noise is removed from the received signals. The proposed algorithms are evaluated and compared with existing methods through numerical simulations and on real data collected during a UA communication experiment conducted in the estuary of the Swan River, WA, Australia, during December 2015. The results show that the proposed approaches consistently improve the accuracy of Channel estimation and the performance of impulsive noise mitigation in UA OFDM communication systems.
Juho Lee - One of the best experts on this subject based on the ideXlab platform.
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compressed Channel estimation for 5g nr over millimeter wave spectrum
Vehicular Technology Conference, 2019Co-Authors: Hyoungju Ji, Heechul Yang, Hoondong Noh, Younsun Kim, Juho LeeAbstract:In this paper, a compressed sensing based Channel acquisition is proposed for beyond 5G systems where the singlecarrier waveform is used over the millimeter wave spectrum. The key idea of the proposed technique, 2-dimensional compressed Channel recovery (2D-CCR), is to estimate Channel Impulse Response based on randomly selected time-domain pilot samples transmitted in a localized portion of the bandwidth. As a result of 2D-CCR, Channel information of full bandwidth can be acquired from compressed sensing without having to take the measurement on the entire bandwidth. From the numerical evaluations, it is observed that the proposed scheme outperforms conventional Channel estimation schemes in terms of estimation accuracy.
Lajos Hanzo - One of the best experts on this subject based on the ideXlab platform.
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generic z domain discrete time transfer function estimation for ultra wideband systems
Electronics Letters, 2008Co-Authors: Raja Ali Riaz, Muhammad Fasih Uddin Butt, Sheng Chen, Lajos HanzoAbstract:Generic z-domain discrete-time transfer function estimation is proposed for ultra-wideband Channels, which requires no Channel sounding sequence transmission and hence constitutes a blind technique. This is achieved by estimating the Channel Impulse Response with the aid of the information signalling pulses and then equalising the effects of the Channel by the corresponding inverse system.
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Channel prediction and predictive vector quantization aided Channel Impulse Response feedback for sdma downlink preprocessing
Vehicular Technology Conference, 2008Co-Authors: Du Yang, Lieliang Yang, Lajos HanzoAbstract:Invoking SDMA in the down-link (DL) has the potential of increasing the achievable throughput with the aid of linear transmit preprocessing, provided that the Channel Impulse Responses (CIRs) of all users and all antenna elements are known at the DL transmitter. However, in a frequency division duplex (FDD) system, since these CIRs have to be transmitted by the mobile terminals (MTs) to the base station (BS), they are naturally out-dated. Hence, we proposed a periodical CIR update scheme employing a Channel predictor at the DL transmitter for predicting the CIR taps for each future symbol transmission instant and hence to mitigate the performance degradation imposed by the associated signalling delays. Moreover, a predictive vector quantizer (PVQ) is used at the MTs for compressing the CIRs before their uplink transmission. Compared to a conventional vector quantizer (VQ), PVQ has significantly reduced the CIR feedback bit rate. Hence, with the aid of the same feedback bit rate, the new PVQ scheme can provide more accurate CIR information or support a Channel having a higher Doppler frequency.
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Channel Impulse Response tap prediction for time varying wireless Channels
IEEE Transactions on Vehicular Technology, 2007Co-Authors: J Akhtman, Lajos HanzoAbstract:In this paper, we perform a comparative study of both the achievable performance and the associated computational complexity of two major time-domain prediction strategies proposed for employment in wireless mobile communication systems. Specifically, we investigate the intrinsic design tradeoffs of the so-called stationary robust predictor and the adaptive recursive-least-squares (RLS) predictor. We demonstrate that the RLS predictor outperforms its robust counterpart at a cost of slightly higher computational complexity, and hence, the RLS predictor constitutes a better alternative for employment in wireless transceivers.
M Tuchler - One of the best experts on this subject based on the ideXlab platform.
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iterative Channel estimation for turbo equalization of time varying frequency selective Channels
IEEE Transactions on Wireless Communications, 2004Co-Authors: R Otnes, M TuchlerAbstract:We investigate turbo equalization, or iterative equalization and decoding, as a receiver technology for systems where data is protected by an error-correcting code, shuffled by an interleaver, and mapped onto a signal constellation for transmission over a frequency-selective Channel with unknown time-varying Channel Impulse Response. The focus is the concept of soft iterative Channel estimation, which is to improve the Channel estimate over the iterations by using soft information fed back from the decoder from the previous iteration to generate "extended training sequences" between the actual transmitted training sequences.