Quantize and Forward Cooperative Communication: Channel Parameter Estimation

Avram, Iancu; Aerts, Nico; Bruneel, Herwig; Moeneclaey, Marc

doi:10.1109/twc.2012.010312.110595

Cited by 31 publications

(38 citation statements)

References 20 publications

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“…The source is assumed to broadcast BPSK symbols that are quantized at the relay on QPSK symbols. The quantization of the samples at the relay is performed without knowledge of the SR channel as described in [7], [12].…”

Section: Numerical Resultsmentioning

confidence: 99%

“…The corresponding transition probabilities are obtained as function of the SR channel parameters h r and E s /N r using the techniques described in [7], [12]. Because some transition probabilities can be very small at high SNR values, the use of IS is required for obtaining meaningfull results within reasonable simulation times.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…While this is useful for obtaining various information-theoretical results, the situation of imperfect CSI presents new challenges that need to be tackled. Channel parameter estimation for QF has been discussed in [10], [11] for a protocol in which the relay estimates the source-relay (SR) channel and forwards the estimate to the destination, while [12] describes a QF system in which all channel parameters are estimated at the destination. In [12], the SR channel is abstracted to be a discrete channel, characterized by a finite set of transition probabilities.…”

Section: Introductionmentioning

confidence: 99%

“…Channel parameter estimation for QF has been discussed in [10], [11] for a protocol in which the relay estimates the source-relay (SR) channel and forwards the estimate to the destination, while [12] describes a QF system in which all channel parameters are estimated at the destination. In [12], the SR channel is abstracted to be a discrete channel, characterized by a finite set of transition probabilities. In doing so, the estimation of the SR channel is greatly simplified, and the computational complexity at the destination is reduced.…”

Section: Introductionmentioning

confidence: 99%

“…In doing so, the estimation of the SR channel is greatly simplified, and the computational complexity at the destination is reduced. In this contribution, the modified Cramer-Rao bound (MCRB) is obtained using a similar channel model as in [12]. Compaired to the unmodified Cramer-Rao bound (CRB), the MCRB is a looser and computationally less complex bound that coincides with the CRB in the high signal-to-noise (SNR) limit [13], [14].…”

Section: Introductionmentioning

confidence: 99%

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The modified Cramer-Rao bound for channel estimation in quantize-and-forward cooperative systems

Avram

Moeneclaey

2013

2013 IEEE Wireless Communications and Networking Conference (WCNC)

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Abstract-The quantize-and-forward (QF) cooperative protocol can effectively be used to combat fading in systems using half-duplex relay terminals. While the outage behavior of the QF protocol has been extensively investigated, few research has been performed on the impact of imperfect channel estimates. In this contribution, a lower bound (LB) on the estimation error is obtained for a one-hop relaying channel with data quantization at the relay. To this purpose the modified Cramer-Rao (MCRB) bound is calculated, which, compared to the true Cramer-Rao bound (CRB), is a looser and computationally less complex bound that converges to the CRB in the high signal-to-noise ratios. By using a general system model for the relay channel, the obtained results can be utilized to benchmark a wide variety of systems.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: Numerical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The modified Cramer-Rao bound for channel estimation in quantize-and-forward cooperative systems

Avram

Moeneclaey

2013

2013 IEEE Wireless Communications and Networking Conference (WCNC)

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New Technology Compensation of Restriction Noise at the Analog-to-Digital Conversion of the TV Broadcasting Luminance Signal

Mammadov

Ismailov

Muradzadeh

2023

Lecture Notes in Mechanical Engineering

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Amplify–Quantize–Forward Relay Channel With Quadrature Amplitude Modulation

Jin

2022

IEEE Access

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This paper considers an amplify-quantize-forward (AQF) relay channel with M -ary quadrature amplitude modulation, where the relay implements amplification for the received signal and a uniform quantization for each of real and imaginary parts of the amplified version. Two step-size determinant methods for the uniform quantization affected by the power constraint at the relay are proposed by deriving the power and the mean square error for the quantized signal. Given the step size for the quantization, the maximum-likelihood detection is presented, and a linear combining detection called equivalent maximum ratio combining is proposed to reduce the detection complexity in the AQF relay channel. The simulation results confirm the superiority of the proposed quantization methods and detection algorithms.

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Quantize and Forward Cooperative Communication: Channel Parameter Estimation

Cited by 31 publications

References 20 publications

The modified Cramer-Rao bound for channel estimation in quantize-and-forward cooperative systems

The modified Cramer-Rao bound for channel estimation in quantize-and-forward cooperative systems

New Technology Compensation of Restriction Noise at the Analog-to-Digital Conversion of the TV Broadcasting Luminance Signal

Amplify–Quantize–Forward Relay Channel With Quadrature Amplitude Modulation

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