Low-Complexity and Full-Diversity MIMO Detection Based on Condition Number Thresholding

Mäurer, Johannes; Matz, Gerald; Seethaler, D.

doi:10.1109/icassp.2007.366472

Cited by 54 publications

(40 citation statements)

References 6 publications

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“…In order to gain a better insight on the overall performance of the proposed algorithm, the individual contributions of dealing with imperfect orthogonalization (using Mod.1 procedure) and imperfect nearest neighbor quantization (using Bit error rate LR−ZF [12] LR−MMSE [12] LR−AUG−ZF [13] LRdecimp (LR−ZF) [14] LRdecimp (LR−MMSE) [14] LRdecimp (LR−AUG−ZF) [14] Prop. ILR detector ML (sphere decoder) Mod.2 procedure) are of interest.…”

Section: Ieee 14th Workhop On Signal Processing Advances In Wirelessmentioning

confidence: 99%

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Lattice reduction aided detection in large-MIMO systems

Singhal

Datta

Chockalingam

2013

2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

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Abstract-Lattice reduction (LR) aided detection algorithms are known to achieve the same diversity order as that of maximumlikelihood (ML) detection at low complexity. However, they suffer SNR loss compared to ML performance. The SNR loss is mainly due to imperfect orthogonalization and imperfect nearest neighbor quantization. In this paper, we propose an improved LR-aided (ILR) detection algorithm, where we specifically target to reduce the effects of both imperfect orthogonalization and imperfect nearest neighbor quantization. The proposed ILR detection algorithm is shown to achieve near-ML performance in large-MIMO systems and outperform other LR-aided detection algorithms in the literature. Specifically, the SNR loss incurred by the proposed ILR algorithm compared to ML performance is just 0.1 dB for 4-QAM and < 0.5 dB for 16-QAM in 16 × 16 V-BLAST MIMO system. This performance is superior compared to those of other LR-aided detection algorithms, whose SNR losses are in the 2 dB to 9 dB range.

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Section: Ieee 14th Workhop On Signal Processing Advances In Wirelessmentioning

confidence: 99%

“…In [12], it has been proved that for a channel matrix with bounded condition number, the zero-forcing (ZF) detector achieves the same diversity order as that of the maximumlikelihood (ML) detector. Lattice reduction transforms the channel matrix into another matrix with near-orthogonal columns, and hence with a better condition number.…”

Section: Introductionmentioning

confidence: 99%

Lattice reduction aided detection in large-MIMO systems

Singhal

Datta

Chockalingam

2013

2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

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“…In SISO-OFDM systems, the subcarrier channel norm is a measure of channel quality. However, for MIMO-OFDM systems, the norm of the channel matrix, ( ), H  of the th  subcarrier is not a good measure of channel quality [15]- [16]. The condition number of the channel matrix of a MIMO-OFDM subcarrier provides a good measure of the quality of the subcarrier, especially for suboptimal receivers at high signal-to-noise ratio (SNR) [17].…”

Section: Introductionmentioning

confidence: 99%

Bandwidth-Efficient Selective Retransmission for MIMO-OFDM Systems

Muhammad¹,

Kiani²,

Saqib³

et al. 2015

ETRI J

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In this work, we propose an efficient selective retransmission method for multiple-input and multipleoutput (MIMO) wireless systems under orthogonal frequency-division multiplexing (OFDM) signaling. A typical received OFDM frame may have some symbols in error, which results in a retransmission of the entire frame. Such a retransmission is often unnecessary, and to avoid this, we propose a method to selectively retransmit symbols that correspond to poor-quality subcarriers. We use the condition numbers of the subcarrier channel matrices of the MIMO-OFDM system as a quality measure. The proposed scheme is embedded in the modulation layer and is independent of conventional hybrid automatic repeat request (HARQ) methods. The receiver integrates the original OFDM and the punctured retransmitted OFDM signals for more reliable detection. The targeted retransmission results in fewer negative acknowledgements from conventional HARQ algorithms, which results in increasing bandwidth and power efficiency. We investigate the efficacy of the proposed method for optimal and suboptimal receivers. The simulation results demonstrate the efficacy of the proposed method on throughput for MIMO-OFDM systems.

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“…To the best of the authors' knowledge, the first MIMO adaptive scheme for the receive side was recently presented in [13]. The authors therein, however, considered only the common case of Rayleigh channels and hence the formulation of a generalized framework is infeasible; the proposed scheme relaxes the constraint of Rayleigh fading to account for the commonly experienced Ricean propagation and, consequently, it includes the model of [13] as a special case.…”

Section: Introductionmentioning

confidence: 99%

“…A similar concept of adaptive MIMO transmission has been investigated by various research groups during recent years (the interested readers are referred to [9]- [11] among others) and essentially goes back to the fundamental diversity-multiplexing tradeoff [12]. To the best of the authors' knowledge, the first MIMO adaptive scheme for the receive side was recently presented in [13]. The authors therein, however, considered only the common case of Rayleigh channels and hence the formulation of a generalized framework is infeasible; the proposed scheme relaxes the constraint of Rayleigh fading to account for the commonly experienced Ricean propagation and, consequently, it includes the model of [13] as a special case.…”

Section: Introductionmentioning

confidence: 99%

Reduced Complexity Detection for Ricean MIMO Channels Based on Condition Number Thresholding

Matthaiou

Laurenson

Wang

2008

2008 International Wireless Communications and Mobile Computing Conference

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Abstract-In this paper, a novel adaptive detection scheme for the case of Multiple-Input Multiple-Output (MIMO) Ricean channels with two transmit and receive antenna elements is presented. Our prime aim is to reduce the extensive complexity of Maximum-Likelihood (ML) detectors by developing an adaptive scheme which switches between a ML and a much simpler ZeroForcing (ZF) detector depending on the instantaneous spatial conditions. The kernel of the adaptive detector (AD) is a harddecision criterion based on the condition number of the MIMO correlation matrix. It is demonstrated that the proposed scheme offers a remarkable reduction in terms of complexity along with a satisfactory performance when specifically designed antenna arrays are employed.

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Low-Complexity and Full-Diversity MIMO Detection Based on Condition Number Thresholding

Cited by 54 publications

References 6 publications

Lattice reduction aided detection in large-MIMO systems

Lattice reduction aided detection in large-MIMO systems

Bandwidth-Efficient Selective Retransmission for MIMO-OFDM Systems

Reduced Complexity Detection for Ricean MIMO Channels Based on Condition Number Thresholding

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