Reduced-complexity methods for throughput maximization in MIMO channels

López-Vicario, José; Mecklenbräuker, Christoph F.; Antón-Haro, Carles

doi:10.1109/icc.2004.1313017

Cited by 6 publications

(4 citation statements)

References 8 publications

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“…In the case of V-BLAST schemes, a series of inverse matrices are needed to obtain those vector norms. However, such set of inverse matrices can be efficiently computed by invoking the block matrix inversion lemma and, by doing so, a lower-complexity recursive approach, named the top-down algorithm, was derived by the authors in [13]. For a moderate number of transmit and receive antennas, the additional cost of introducing transmit AS mechanisms (with respect to a scheme with a fixed number of transmit antennas) turns out to be only 1.52% (see Table I).…”

Section: Cross-layer Transmit Antenna Selectionmentioning

confidence: 99%

A cross-layer approach to transmit antenna selection

Vicario

Lagunas

Antón-Haro

2006

IEEE Trans. Wireless Commun.

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Abstract-In this paper, we investigate a cross-layer approach to transmit antenna selection capable of adapting the number of active antennas to varying channel conditions. We address a cross-layer methodology in the sense that the criterion for the selection of antenna subsets is the maximization of link layer throughput which takes into account characteristics both at the physical and link layers. In order to enhance system performance, adaptive modulation is included to jointly perform antenna selection and rate adaptation. Performance assessment is conducted in terms of link layer throughput and transmission delay.

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Section: Cross-layer Transmit Antenna Selectionmentioning

confidence: 99%

A cross-layer approach to transmit antenna selection

Vicario

Lagunas

Antón-Haro

2006

IEEE Trans. Wireless Commun.

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“…Assuming that for (which holds if has full rank), we can rewrite (20) as (21) with the "unbiased distance" (22) The minimization in (21) is known as unbiased MMSE detection [19]; it will hereafter be denoted as (23) The terms "unbiased distance" and "unbiased MMSE detection" reflect the fact that, in contrast to the MMSE estimate , the scaled MMSE estimate is conditionally unbiased given , i.e., or equivalently [19]. In general, the error probability of unbiased MMSE detection (23) is slightly smaller than that of conventional MMSE detection.…”

Section: Data-detection Stagementioning

confidence: 99%

“…This stage is the determination of the most reliabe layer according to (14), with according to (23).…”

Section: Layer-sorting Stagementioning

confidence: 99%

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Dynamic Nulling-and-Canceling for Efficient Near-ML Decoding of MIMO Systems

Seethaler¹,

Artes²,

Hlawatsch³

2006

IEEE Trans. Signal Process.

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Abstract-It is known that conventional nulling-and-canceling (NC) detection for multiple-input/multiple-output (MIMO) systems cannot exploit all of the available diversity, and, thus, its performance is significantly inferior to that of maximum likelihood (ML) detection. Conventional NC employs the layerwise postequalization signal-to-noise ratios (SNRs) as reliability measures for layer sorting. These SNRs are average quantities that do not depend on the received vector. In this paper, we propose the novel dynamic nulling-and-canceling (DNC) technique that uses approximate a posteriori probabilities as measures of layer reliability. The DNC technique is a minimum mean-square error (MMSE) nulling scheme combined with an improved "dynamic" layer sorting rule that exploits the information contained in the current received vector. We calculate the error probability of DNC for a simple special case and show that it is upper bounded by the error probability of conventional NC. Simulation results are presented for spatial multiplexing systems and for systems using linear dispersion codes. It is demonstrated that the DNC technique can yield near-ML performance for a wide range of system sizes and channel SNRs at a fraction of the computational complexity of the sphere-decoding algorithm for ML detection.Index Terms-Equalization, linear dispersion codes, maximum likelihood (ML) detection, multiple-input/multiple-output (MIMO) channels, multiuser detection, nulling and canceling (NC), spatial multiplexing, V-BLAST.

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Near-optimal and optimal reduced complexity algorithms for throughput maximization in underlay CR MIMO systems

Okumu

Dlodlo

2016

2016 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)

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Reduced-complexity methods for throughput maximization in MIMO channels

Cited by 6 publications

References 8 publications

A cross-layer approach to transmit antenna selection

A cross-layer approach to transmit antenna selection

Dynamic Nulling-and-Canceling for Efficient Near-ML Decoding of MIMO Systems

Near-optimal and optimal reduced complexity algorithms for throughput maximization in underlay CR MIMO systems

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