Robust Peer-to-Peer Relay Beamforming: A Probabilistic Approach

Ponukumati, Dhananjaya; Gao, Feifei; Xing, Chengwen

doi:10.1109/lcomm.2012.121912.122144

Cited by 20 publications

(16 citation statements)

References 8 publications

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“…The method in [9] is named as SDR(Semi-Definite Relaxation) ，our proposed method shown in (17) is named as LPM(Lorentz-Positive Map). In the simulations, we compare the performance of these two methods as well as with the perfect CSI case.…”

Section: Numerical Resultsmentioning

confidence: 99%

Multiple Peer-To-Peer Relay Network Robust Beamforming Based on Lorentz-Positive Matrices

Li¹,

Hou²

2016

IJGDC

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Section: Numerical Resultsmentioning

confidence: 99%

Multiple Peer-To-Peer Relay Network Robust Beamforming Based on Lorentz-Positive Matrices

Li¹,

Hou²

2016

IJGDC

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“…However, in most scenarios encountered the channels observed by the relays may lead to performance degradation because of inevitable measurements, estimation procedures and quantization errors in CSI [15] as well as propagation effects. These impairments result in imperfect CSI that can affect most distributed beamforming methods, which either fail to work properly or cannot provide satisfactory performance.…”

Section: A Prior and Related Workmentioning

confidence: 99%

“…In this context, robust distributed beamforming (RDB) techniques are hence in demand to mitigate the channel errors or uncertainties and preserve the relay system performance. The studies in [15], [16], [17], [18] minimize the total relay transmit power under an overall quality of service (QoS) constraint, using either a convex semi-definite programme (SDP) relaxation method or a convex second-order cone programme (SOCP). The works in [15], [16] consider the channel errors as Gaussian random vectors with known statistical distributions between the source to the relay nodes and the relay nodes to the destination, whereas [17] models the channel errors on their covariance matrices as a type of matrix perturbation.…”

Section: A Prior and Related Workmentioning

confidence: 99%

“…The studies in [15], [16], [17], [18] minimize the total relay transmit power under an overall quality of service (QoS) constraint, using either a convex semi-definite programme (SDP) relaxation method or a convex second-order cone programme (SOCP). The works in [15], [16] consider the channel errors as Gaussian random vectors with known statistical distributions between the source to the relay nodes and the relay nodes to the destination, whereas [17] models the channel errors on their covariance matrices as a type of matrix perturbation. The work in [17], [19], [20] presents a robust design, which ensures that the SNR constraint is satisfied in the presence of imperfect CSI by adopting a worst-case design and formulates the problem as a convex optimization problem that can be solved efficiently.…”

Section: A Prior and Related Workmentioning

confidence: 99%

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Distributed Robust Beamforming Based on Low-Rank and Cross-Correlation Techniques: Design and Analysis

Ruan

Lamare

2019

IEEE Trans. Signal Process.

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In this work, we present a novel robust distributed beamforming (RDB) approach based on low-rank and crosscorrelation techniques. The proposed RDB approach mitigates the effects of channel errors in wireless networks equipped with relays based on the exploitation of the cross-correlation between the received data from the relays at the destination and the system output and low-rank techniques. The relay nodes are equipped with an amplify-and-forward (AF) protocol and the channel errors are modeled using an additive matrix perturbation, which results in degradation of the system performance. The proposed method, denoted low-rank and cross-correlation RDB (LRCC-RDB), considers a total relay transmit power constraint in the system and the goal of maximizing the output signal-tointerference-plus-noise ratio (SINR). We carry out a performance analysis of the proposed LRCC-RDB technique along with a computational complexity study. The proposed LRCC-RDB does not require any costly online optimization procedure and simulations show an excellent performance as compared to previously reported algorithms.

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“…One approach is to consider the worst-case based optimization that restricts the channel errors in a certain bounded region [4][5][6] . Another approach is the probabilistic approach, in which QoS is guaranteed in a probabilistic sense [7,8] . The first approach usually employs semi-definite programming relaxation to tackle the problem of infinite constraints due to CSI errors, which can not guarantee a rank-one optimal solution.…”

Section: Introductionmentioning

confidence: 99%

A New Method for Robust Multiple Peer-To-Peer Relay Beamforming

Hou¹,

Du²,

Qi³

et al. 2015

Proceedings of the 4th International Conference on Information Technology and Management Innovation

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This paper focuses on how to design the robust beamforming vectors of multiple peer-to-peer relay networks. In the context of imperfect channel state information at the relays, our goal is to minimize the transmit power at relay nodes subject to the quality of service at each receiver. A method based on real value Lorentz-positive maps and linear matrix inequalities is proposed, which converts the transmit power minimization problem at relay nodes into a convex optimization problem. The proposed method overcomes the disadvantages of traditional methods based on semi-definite programming relaxation, which sometimes result in solutions with rank greater than one. Simulation results show that the solution of the proposed method is consistent with those of conventional method based on semi-definite programming relaxation.

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Robust Peer-to-Peer Relay Beamforming: A Probabilistic Approach

Cited by 20 publications

References 8 publications

Multiple Peer-To-Peer Relay Network Robust Beamforming Based on Lorentz-Positive Matrices

Multiple Peer-To-Peer Relay Network Robust Beamforming Based on Lorentz-Positive Matrices

Distributed Robust Beamforming Based on Low-Rank and Cross-Correlation Techniques: Design and Analysis

A New Method for Robust Multiple Peer-To-Peer Relay Beamforming

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