Least-Squares based channel estimation for MIMO relays

Lioliou, Panagiota; Viberg, Mats

doi:10.1109/wsa.2008.4475542

Cited by 62 publications

(70 citation statements)

References 5 publications

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“…As a result, the effect of the estimator in [7] on the performance of MIMO cooperative networks is not investigated. Finally, in [8] and [9] the authors devise new channel estimators for full-duplex multirelay MIMO cooperative networks, i.e., where all nodes within the network can transmit and receive at the same time. However, the estimators in [8] and [9] are only applicable to the case of single antenna relays and require a total of K + 1 time slots, where K denotes the number of relays in the network, to estimate the network's channels.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous estimation of multi-relay MIMO channels

Mehrpouyan

Blostein

Ottersten

2013

2013 IEEE Global Communications Conference (GLOBECOM)

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Abstract-This paper addresses training-based channel estimation in distributed amplify-and-forward (AF) multi-input multi-output (MIMO) multi-relay networks. To reduce channel estimation overhead and delay, a training algorithm that allows for simultaneous estimation of the entire MIMO cooperative network's channel parameters at the destination node is proposed. The exact Cramér-Rao lower bound (CRLB) for the problem is presented in closedform. Channel estimators that are capable of estimating the overall source-relay-destination channel parameters at the destination are also derived. Numerical results show that while reducing delay, the proposed channel estimators are close to the derived CRLB over a wide range of signal-to-noise ratio values and outperform existing channel estimation methods. Finally, extensive simulations demonstrate that the proposed training method and channel estimators can be effectively deployed in combination with cooperative optimization algorithms to significantly enhance the performance of AF relaying MIMO systems in terms of average-bit-error-rate.

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Section: Introductionmentioning

confidence: 99%

Simultaneous estimation of multi-relay MIMO channels

Mehrpouyan

Blostein

Ottersten

2013

2013 IEEE Global Communications Conference (GLOBECOM)

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“…In [8], an algorithm based on the least-squares (LS) method was developed to estimate the channel matrices of MIMO relay networks. In particular, both the source-relay and the relay-destination channel matrices are estimated from the observed composite source-relay-destination channel matrix.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, both the source-relay and the relay-destination channel matrices are estimated from the observed composite source-relay-destination channel matrix. A drawback from channel estimation using [8] is the scalar ambiguity of the estimated channel matrices. A two-phase channel estimation scheme based on linear minimum meansquared error (LMMSE) was proposed in [9] for two-hop MIMO relay networks.…”

Section: Introductionmentioning

confidence: 99%

“…Then the source-relay channel is estimated at the destination node making use of the relay-destination channel matrix estimated at the first phase. Compared with the approach in [8], there is no scalar ambiguity in this approach.…”

Section: Introductionmentioning

confidence: 99%

“…The source, relay, and destination nodes are equipped with n S , n R , and n D antennas, respectively. We focus on the case where the direct link between the source and destination nodes is sufficiently weak to be ignored [8], [9]. This scenario occurs when the direct link is blocked by an obstacle such as a mountain.…”

Section: Introductionmentioning

confidence: 99%

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Robust channel estimation algorithm for dual-hop MIMO relay channels

Chiong

Rong

Xiang

2012

2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC)

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Abstract-In conventional two-phase channel estimation algorithms for dual-hop multiple-input multiple-output (MIMO) relay systems, the relay-destination channel estimated in the first phase is used for the source-relay channel estimation in the second phase. For these algorithms, the mismatch between the estimated and the true relay-destination channel affects the accuracy of the source-relay channel estimation. In this paper, we investigate the impact of such channel state information (CSI) mismatch on the performance of the two-phase channel estimation algorithm. By explicitly taking into account the CSI mismatch, we develop a robust algorithm to estimate the sourcerelay channel. Numerical examples demonstrate the improved performance of the proposed algorithm.

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2010

Cooperative Communications

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Least-Squares based channel estimation for MIMO relays

Cited by 62 publications

References 5 publications

Simultaneous estimation of multi-relay MIMO channels

Simultaneous estimation of multi-relay MIMO channels

Robust channel estimation algorithm for dual-hop MIMO relay channels

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