Results 1  10
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99
Optimal channel estimation and training design for twoway relay networks
 IEEE Trans. Commun
, 2009
"... Abstract—In this paper, channel estimation and training sequence design are considered for amplifyandforward (AF)based twoway relay networks (TWRNs) in a timeselective fading environment. A new complexexponential basis expansion model (CEBEM) is proposed to represent the mobiletomobile time ..."
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Cited by 55 (5 self)
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Abstract—In this paper, channel estimation and training sequence design are considered for amplifyandforward (AF)based twoway relay networks (TWRNs) in a timeselective fading environment. A new complexexponential basis expansion model (CEBEM) is proposed to represent the mobiletomobile timevarying channels. To estimate such channels, a novel pilot symbolaided transmission scheme is developed such that a low complex linear approach can estimate the BEM coefficients of the convoluted channels. More essentially, two algorithms are designed to extract the BEM coefficients of the individual channels. The optimal training parameters, including the number of the pilot symbols, the placement of the pilot symbols, and the power allocation to the pilot symbols, are derived by minimizing the channel meansquare error (MSE). The selections of the system parameters are thoroughly discussed in order to guide practical system design. Finally, extensive numerical results are provided to corroborate the proposed studies. Index Terms—Channel estimation, optimal training design, timevarying channel, twoway relay network, basis expansion model. I.
Pilotassisted timevarying channel estimation for OFDM systems
 IN IEEE TRANS. SIGNAL PROCESS
, 2007
"... In this paper, we deal with channel estimation for orthogonal frequencydivision multiplexing (OFDM) systems. The channels are assumed to be timevarying (TV) and approximated by a basis expansion model (BEM). Due to the timevariation, the resulting channel matrix in the frequency domain is no lon ..."
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Cited by 44 (9 self)
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In this paper, we deal with channel estimation for orthogonal frequencydivision multiplexing (OFDM) systems. The channels are assumed to be timevarying (TV) and approximated by a basis expansion model (BEM). Due to the timevariation, the resulting channel matrix in the frequency domain is no longer diagonal, but approximately banded. Based on this observation, we propose novel channel estimators to combat both the noise and the outofband interference. In addition, the effect of a receiver window on channel estimation is also studied. Our claims are supported by simulation results, which are obtained considering Jakes’ channels with fairly high Doppler spreads.
Compressive Estimation of Doubly Selective Channels: Exploiting Channel Sparsity to Improve Spectral Efficiency in Multicarrier Transmissions
"... We consider the estimation of doubly selective wireless channels within pulseshaping multicarrier systems (which include OFDM systems as a special case). A pilotassisted channel estimation technique using the methodology of compressed sensing (CS) is proposed. By exploiting a channel’s delayDopple ..."
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Cited by 37 (1 self)
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We consider the estimation of doubly selective wireless channels within pulseshaping multicarrier systems (which include OFDM systems as a special case). A pilotassisted channel estimation technique using the methodology of compressed sensing (CS) is proposed. By exploiting a channel’s delayDoppler sparsity, CSbased channel estimation allows an increase in spectral efficiency through a reduction of the number of pilot symbols that have to be transmitted. We also present an extension of our basic channel estimator that employs a sparsityimproving basis expansion. We propose a framework for optimizing the basis and an iterative approximate basis optimization algorithm. Simulation results using three different CS recovery algorithms demonstrate significant performance gains (in terms of improved estimation accuracy or reduction of the number of pilots) relative to conventional leastsquares estimation, as well as substantial advantages of using an optimized basis.
Iterative Joint TimeVariant Channel Estimation and MultiUser Detection for MCCDMA
 IEEE Trans. Wireless Commun
, 2006
"... Joint timevariant channel estimation and multiuser detection are key buildingblocks for wireless broadband communication for mobile users at vehicular speed. We propose an iterative receiver for a multicarrier (MC) code division multiple access (CDMA) system in the uplink. Multiuser detection is ..."
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Cited by 33 (18 self)
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Joint timevariant channel estimation and multiuser detection are key buildingblocks for wireless broadband communication for mobile users at vehicular speed. We propose an iterative receiver for a multicarrier (MC) code division multiple access (CDMA) system in the uplink. Multiuser detection is implemented through iterative parallel interference cancelation and conditional linear minimum mean square error (MMSE) filtering. MCCDMA is based on orthogonal frequency division multiplexing (OFDM), thus timevariant channel estimation can be performed for every subcarrier individually. The variation of a subcarrier over the duration of a data block is upper bounded by the maximum Doppler bandwidth which is determined by the maximum velocity of the users. We exploit results from the theory of timeconcentrated and bandlimited sequences and apply a Slepian basis expansion for timevariant subcarrier estimation. This approach enables timevariant channel estimation without complete knowledge of the secondorder statistics of the fading process. The square bias of the Slepian basis expansion is one order of magnitude smaller compared to the Fourier basis expansion. The square bias of the basis expansion is the determining factor for the performance of the iterative joint channel estimation and data detection. We present an iterative linear MMSE estimation algorithm for the basis expansion coefficients in a multiuser system. The consistent performance of the iterative receiver using the Slepian basis expansion is validated by simulations for a wide range of velocities.
Design and analysis of MMSE pilotaided cyclicprefixed block transmissions for doubly selective channels
 IEEE TRANS. ON SIGNAL PROCESSING
, 2008
"... This paper considers affine cyclicprefixed blockbased pilotaided transmission (PAT) over the singleantenna doubly selective channel, where the channel is assumed to obey a complexexponential basis expansion model. First, a tight lower bound on the meansquared error (MSE) of pilotaided channel ..."
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Cited by 22 (6 self)
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This paper considers affine cyclicprefixed blockbased pilotaided transmission (PAT) over the singleantenna doubly selective channel, where the channel is assumed to obey a complexexponential basis expansion model. First, a tight lower bound on the meansquared error (MSE) of pilotaided channel estimates is derived, along with necessary and sufficient conditions on the pilot/data pattern that achieves this bound. From these conditions, novel minimumMSE (MMSE) PAT schemes are proposed and upper/lower bounds on their ergodic achievable rates are derived. A pilot/data power allocation technique is also developed. A highSNR asymptotic analysis of the ergodic achievable rate of affine MMSEPAT is then performed which suggests that the channel’s spreading parameters should be taken into account when choosing among affine MMSEPAT schemes. Specifically, we establish that multicarrier MMSEPAT achieves higher rates than singlecarrier MMSEPAT when the channel’s delayspread dominates its Dopplerspread, and vice versa.
Noncoherent Capacity of Underspread Fading Channels
, 2008
"... We derive bounds on the noncoherent capacity of widesense stationary uncorrelated scattering (WSSUS) channels that are selective both in time and frequency, and are underspread, i.e., the product of the channel’s delay spread and Doppler spread is small. For input signals that are peak constrained ..."
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Cited by 19 (3 self)
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We derive bounds on the noncoherent capacity of widesense stationary uncorrelated scattering (WSSUS) channels that are selective both in time and frequency, and are underspread, i.e., the product of the channel’s delay spread and Doppler spread is small. For input signals that are peak constrained in time and frequency, we obtain upper and lower bounds on capacity that are explicit in the channel’s scattering function, are accurate for a large range of bandwidth and allow to coarsely identify the capacityoptimal bandwidth as a function of the peak power and the channel’s scattering function. We also obtain a closedform expression for the firstorder Taylor series expansion of capacity in the limit of large bandwidth, and show that our bounds are tight in the wideband regime. For input signals that are peak constrained in time only (and, hence, allowed to be peaky in frequency), we provide upper and lower bounds on the infinitebandwidth capacity and find cases when the bounds coincide and the infinitebandwidth capacity is characterized exactly. Our lower bound is closely related to a result by Viterbi (1967). The analysis in this paper is based on a discretetime discretefrequency approximation of WSSUS time and frequencyselective channels. This discretization explicitly takes into account the underspread
Minimumenergy bandlimited predictor with dynamic subspace selection for timevariant flatfading channels
, 2007
"... In this paper, we develop and analyze the basic methodology for minimumenergy (ME) bandlimited prediction of sampled timevariant flatfading channels. This predictor is based on a subspace spanned by timeconcentrated and bandlimited sequences. The timeconcentration of these sequences is matched ..."
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Cited by 15 (11 self)
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In this paper, we develop and analyze the basic methodology for minimumenergy (ME) bandlimited prediction of sampled timevariant flatfading channels. This predictor is based on a subspace spanned by timeconcentrated and bandlimited sequences. The timeconcentration of these sequences is matched to the length of the observation interval and the bandlimitation is determined by the support of the Doppler power spectral density of the fading process. Slepian showed that discrete prolate spheroidal (DPS) sequences can be used to calculate the ME bandlimited continuation of a finite sequence. We utilize this property to perform channel prediction. We generalize the concept of timeconcentrated and bandlimited sequences to a bandlimiting region consisting of disjoint intervals. For a fading process with constant spectrum over its possibly discontiguous support we prove that the ME bandlimited predictor is identical to a reducedrank maximumlikelihood predictor which is a close approximation of a Wiener predictor. In current cellular communication systems the timeselective fading process is highly oversampled. The essential dimension of the subspace spanned by timeconcentrated and bandlimited sequences is in the order of two to five only. The prediction error mainly depends on the support of the Doppler spectrum. We exploit this fact to propose lowcomplexity timevariant flatfading channel predictors using dynamically selected predefined subspaces. The subspace selection is based on a probabilistic bound on the reconstruction error. We compare the performance of the ME bandlimited predictor with a predictor based on complex exponentials. For a prediction horizon of one eights of a wavelength the numerical simulation
On Doubly Dispersive Channel Estimation for PilotAided PulseShaped MultiCarrier Modulation
, 2006
"... In this paper, we propose several methods for the pilotaided estimation of significant ICI coefficients resulting from pulseshaped multicarrier modulation (PSMCM) over DD channels. Specifically, we outline Wiener and reducedrank (RR) Wiener estimation schemes that leverage statistical channel s ..."
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Cited by 14 (3 self)
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In this paper, we propose several methods for the pilotaided estimation of significant ICI coefficients resulting from pulseshaped multicarrier modulation (PSMCM) over DD channels. Specifically, we outline Wiener and reducedrank (RR) Wiener estimation schemes that leverage statistical channel structure, as well as deterministic leastsquares (LS) schemes based on basis expansion modeling (BEM). We then report the results of a numerical study which suggests that RR Wiener estimation outperforms LS estimation based on polynomial and oversampled complex exponential BEM, even under significant statistical mismatch. In addition, the RR Wiener estimator is computationally cheaper than the LSBEM techniques. These findings have implications on the practical design of PSMCM channel estimation schemes.
E.: Integrating the Content and
 Process of Strategic MIS Planning with Competitive Strategy. Decision Sciences 22 (5
, 1991
"... We review here the recent success in quantum annealing, i.e., optimization of the cost or energy functions of complex systems utilizing quantum fluctuations. The concept is introduced in successive steps through the studies of mapping of such computationally hard problems to the classical spin glass ..."
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Cited by 12 (0 self)
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We review here the recent success in quantum annealing, i.e., optimization of the cost or energy functions of complex systems utilizing quantum fluctuations. The concept is introduced in successive steps through the studies of mapping of such computationally hard problems to the classical spin glass problems. The quantum spin glass problems arise with the introduction of quantum
Joint TwofoldIterative Channel Estimation and Multiuser . . .
, 2008
"... This paper presents an iterative receiver for ..."