MIMO Relaying With Linear Processing for Multiuser Transmission in Fixed Relay Networks

Chae, Chan-Byoung; Tang, Taiwen; Heath, Robert W.; Cho, Sunghyun

doi:10.1109/tsp.2007.907821

Cited by 289 publications

(223 citation statements)

References 36 publications

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“…Compared to DF, AF is less complex. For this reason, some of previous works in fixed relay networks only consider AF approach for simplicity [10], [11]. However, we will mainly consider the DF protocol in order to robustify the link reliability and improve the system performance.…”

Section: Soft Decode-and-forward Protocolmentioning

confidence: 99%

“…In practical systems, only a few fixed relays are available in each cell, consequently, each fixed relay will need to support multiple users. This motivates point-to-multipoint relaying solutions [8]- [10], where the relay forwards data to and from multiple users. This paper focuses on the point-to-multipoint fixed relay, which has received less attention compared to the point-to-point solution.…”

Section: Introductionmentioning

confidence: 99%

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Advanced linear processing for 2-hop fixed MIMO relaying

Xiao

Sellathurai

Cowan

2010

2010 International Conference on Signal Processing and Communications (SPCOM)

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Abstract-In this paper, we consider a 2-hop downlink pointto-multipoint fixed relay systems and propose a novel linear processing strategy at the base station and relay station to improve the reliability of the source-relay and relay-to-destination links. When coupled with a soft-decode-and-forward protocol, the proposed scheme leads to significant performance gain compared to the conventionl solutions for fixed relay networks.

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Section: Soft Decode-and-forward Protocolmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Advanced linear processing for 2-hop fixed MIMO relaying

Xiao

Sellathurai

Cowan

2010

2010 International Conference on Signal Processing and Communications (SPCOM)

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“…The optimization of the source precoder, relay precoder, and receiver via minimization of the sum of the source and relay powers subject to a quality-of-service (QoS) constraint was studied in [16] for single relay networks and in [17] for multirelay networks. The case of multiuser MIMO relay networks was studied in [18], [19]. An excellent reference on precoder design for MIMO relay networks is [20].…”

Section: Introductionmentioning

confidence: 99%

Joint Source-Relay Optimization for Fixed Receivers in Multi-Antenna Multi-Relay Networks

Ikhlef

Schober

2014

IEEE Trans. Wireless Commun.

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Additional information: Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Abstract-We jointly optimize the source and relay precoders for multi-antenna multi-relay networks employing a prefixed receiver. Prefixed receivers are of practical interest since they enable low complexity at the end-user's receiver as well as backward compatibility. To compute the source and relay precoders, we consider two different criteria. The objective of the first criterion is to maximize the worst stream signal-to-interference-plusnoise ratio (SINR) at the output of the receiver subject to source and relay transmit power constraints. Under the second criterion, we minimize the source and relay transmit powers subject to a certain quality-of-service constraint. Both optimization problems are non-convex. To solve them, we propose iterative alternating algorithms, where, in each iteration, we compute the precoders alternately, i.e., for each precoder optimization, we fix all the precoders except the one which is optimized. For both criteria, we formulate the optimization problem for the computation of the source precoder as a second order cone programming (SOCP) problem, for which the optimal solution can be found using interior point algorithms. For each relay precoder, we formulate the optimization problem as a semidefinite relaxation (SDR) problem for which ready-to-use solvers exist. If the solution to the SDR problem is not of rank one, matrix rankone decomposition or randomization is applied. We also provide sufficient conditions for the convergence of the proposed iterative alternating algorithms to a fixed point. Simulation results show that the performance of the proposed algorithms is close to the performance achieved if the source, relay, and receiver filters are jointly optimized.Index Terms-Cooperative relaying, multiple-input multipleoutput, joint optimization of source and relays, prefixed receivers.

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“…In multiuser MIMO-aided DL relaying most research concentrated on the scenario, where only a single receive antenna is used at each MS [10,11]. Furthermore, it was typically assumed that the BS knows the DL CSI [10,11].…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, it was typically assumed that the BS knows the DL CSI [10,11]. However, it would be rather challenging to inform the BS of the CSI between the RS and each MS, especially for highvelocity MSs.…”

Section: Introductionmentioning

confidence: 99%

Block diagonalisation-based multiuser multiple input multiple output-aided downlink relaying

Liu

et al. 2012

IET Commun.

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A novel block diagonalisation (BD)-based Multiuser multiple input multiple output (MU-MIMO)-aided relaying scheme is proposed for downlink transmissions, which does not require any channel state information at the base station (BS) and decomposes a MU-MIMO-aided relaying system into several parallel single-user MIMO-assisted relaying schemes. Furthermore, based on the proposed algorithm the optimal linear processing matrix designed for the maximum achievable capacity is derived, which significantly outperforms the so-called naive weighting matrix. Nomenclature

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MIMO Relaying With Linear Processing for Multiuser Transmission in Fixed Relay Networks

Cited by 289 publications

References 36 publications

Advanced linear processing for 2-hop fixed MIMO relaying

Advanced linear processing for 2-hop fixed MIMO relaying

Joint Source-Relay Optimization for Fixed Receivers in Multi-Antenna Multi-Relay Networks

Block diagonalisation-based multiuser multiple input multiple output-aided downlink relaying

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