Generalized Channel Inversion Methods for Multiuser MIMO Systems

Sung, Hyun Hwan; Lee, Sang-Rim; Lee, Inkyu

doi:10.1109/tcomm.2009.11.070404

Cited by 248 publications

(168 citation statements)

References 23 publications

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“…We compute the complexity in terms of the required floating point operation (flops) [10]- [11]. The inversion of the n k × n k matrix D k and N r × N t matrix H using Gauss-Jordan elimination requires 4n 3 k /3 flops and 4N 3 t /3 flops, respectively.…”

Section: B Complexity Analysismentioning

confidence: 99%

“…The inversion of the n k × n k matrix D k and N r × N t matrix H using Gauss-Jordan elimination requires 4n 3 k /3 flops and 4N 3 t /3 flops, respectively. According to [11], the search for the optimal perturbation vector within n dimensions requires O(n 6 ) operations. The operator O(·) defines the order of numerical operators and is used to analyze the efficiency of an algorithm, also known as time complexity.…”

Section: B Complexity Analysismentioning

confidence: 99%

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A Constellation Scaling Approach to Vector Perturbation for Adaptive Modulation in MU-MIMO

Masouros

2015

IEEE Wireless Commun. Lett.

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Abstract-It is known that vector perturbation (VP) precoding does not apply to the case where users employ different modulations, while existing solutions for this scenario are suboptimal. In this letter, a joint vector perturbation precoding algorithm is proposed for multiuser MIMO (MU-MIMO) downlink system in the adaptive modulation scenario where different users apply different modulation types. Compared with conventional block diagonalized vector perturbation (BD-VP) and user grouping VP where the search dimension of the perturbation vector is reduced, the proposed algorithm keeps the search dimension unchanged by applying a simple transformation to the VP operation. Our analysis and results show that the proposed algorithm provides an applicable VP solution to the adaptive modulation scenario, with optimal VP performance.

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Section: B Complexity Analysismentioning

confidence: 99%

Section: B Complexity Analysismentioning

confidence: 99%

A Constellation Scaling Approach to Vector Perturbation for Adaptive Modulation in MU-MIMO

Masouros

2015

IEEE Wireless Commun. Lett.

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“…Theorem 1: The precoding and decoding matrices of the SLNR precoding scheme [6], obtained by (4) and (5) respectively, are equivalent to those of RBD [4] and GMI-2 (GMI method 2) [5] schemes under the assumption of the same regularisation parameter and power normalisation procedure.…”

Section: A Equivalence Between Slnr Rbd and Gmi-2 Schemesmentioning

confidence: 99%

“…They are later extended to the case of multi-antenna receivers, e.g. ZF is developed into Block Diagonalisation (BD) [3] precoding, and MMSE is extended to Regularised Block Diagonalisation (RBD) [4] and Generalised MMSE Channel Inversion (GMI) [5] schemes. A precoding scheme based on the maximum signal-to-leakage-plus-noise ratio (SLNR) [6] is another attractive technique which provides an alternative approach to the signal-to-interference-plus-noise ratio (SINR) maximisation problem and supports systems with both singleantenna and multi-antenna receivers.…”

mentioning

confidence: 99%

Equivalent Expressions and Performance Analysis of SLNR Precoding Schemes: A Generalisation to Multi-Antenna Receivers

2013

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Abstract-In this letter, equivalent expressions of transmit precoding solutions based on the maximum signal-to-leakageplus-noise ratio (SLNR) are derived for multiuser MIMO systems with multi-antenna receivers. The performance of the SLNR precoding scheme is also analysed based on this equivalent form. Further, it is shown that the SLNR scheme can be viewed as a generalised channel regularisation technique and the conditions for an equivalence between the SLNR, the Regularised Block Diagonalisation (RBD) and the Generalised MMSE Channel Inversion (GMI method 2) schemes are given. Consequently, the performance analysis in this letter can be extended to the RBD and GMI schemes. This generalises the equivalence between the SLNR and MMSE schemes and its useful implications, from the case of single-antenna to multi-antenna receivers.

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“…Then, applying the transmit combining matrix obtained under an MMSE criterion to the orthonormal vector set, the proposed scheme is able to increase the signal-to-interference-plus-noise ratio (SINR) at each user's receiver. Consequently, the proposed scheme can be considered as an extension of the MMSE based block diagonalization (MMSE-BD) method in [9] and [10] …”

Section: ⅰ Introductionmentioning

confidence: 99%

MMSE Based Nonlinear Precoding for Multiuser MIMO Broadcast Channels with Inter-Cell Interference

Lee¹,

Sung²,

Lee³

2016

The Journal of Korean Institute of Communications and Informati

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In this paper, we investigate a minimum mean-squared error based nonlinear successive precoding method as a practical solution of dirty paper coding for multiuser downlink channels where each user has more than one antenna in the presence of other cell interference (OCI). Unlike conventional zero-forcing (ZF) based methods, the proposed scheme takes the OCI plus noise into account when suppressing the inter-cell multiuser interference, which results in improvement of the received signal-to-interference-plus-noise ratio. Simulation results show that the proposed scheme outperforms conventional methods in terms of sum rate for various OCI configurations.

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Generalized Channel Inversion Methods for Multiuser MIMO Systems

Cited by 248 publications

References 23 publications

A Constellation Scaling Approach to Vector Perturbation for Adaptive Modulation in MU-MIMO

A Constellation Scaling Approach to Vector Perturbation for Adaptive Modulation in MU-MIMO

Equivalent Expressions and Performance Analysis of SLNR Precoding Schemes: A Generalisation to Multi-Antenna Receivers

MMSE Based Nonlinear Precoding for Multiuser MIMO Broadcast Channels with Inter-Cell Interference

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