Characterizing the statistical properties of mutual information in mimo channels

Oyman, Özgür; Nabar, R.U.; Bölcskei, Helmut; Paulraj, A.

doi:10.1109/tsp.2003.818153

Cited by 205 publications

(119 citation statements)

References 25 publications

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“…Comparing (4) with (5), we can infer that at high-SNRs the proposed bound becomes exact and equal to which is consistent with the results of [3], [5]. More importantly, this observation is in fundamental contrast with the lower bound in [11], whose tightness degrades as the SNR increases since it is based on a first-order expansion of (4).…”

Section: New Lower Bounds On the Ergodic Capacity Of Rln D-mimo supporting

confidence: 84%

“…More importantly, this observation is in fundamental contrast with the lower bound in [11], whose tightness degrades as the SNR increases since it is based on a first-order expansion of (4). Note that the above high-SNR expression verifies the well-known characteristic of MIMO systems, that is the asymptotically (in terms of SNR) linear capacity increase with the minimum number of antennas [1], [3], [4], [6].…”

Section: New Lower Bounds On the Ergodic Capacity Of Rln D-mimo supporting

confidence: 56%

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A New Lower Bound on the Ergodic Capacity of Distributed MIMO Systems

Matthaiou

Chatzidiamantis

Karagiannidis

2011

IEEE Signal Process. Lett.

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Abstract-We present a novel and analytical lower bound on the ergodic capacity of distributed multiple-input multiple-output (D-MIMO) systems operating in composite Rayleigh/lognormal (RLN) fading and assuming double-sided spatial correlation. The proposed lower bound is applicable for finite number of antennas and remains tight across the entire Signal-to-Noise (SNR) regime. In addition, we perform a detailed low-SNR analysis that provides useful insights into the implications of the system parameters on MIMO capacity.

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Section: New Lower Bounds On the Ergodic Capacity Of Rln D-mimo supporting

confidence: 84%

Section: New Lower Bounds On the Ergodic Capacity Of Rln D-mimo supporting

confidence: 56%

A New Lower Bound on the Ergodic Capacity of Distributed MIMO Systems

Matthaiou

Chatzidiamantis

Karagiannidis

2011

IEEE Signal Process. Lett.

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“…The power offset, which anchors the expansion, is given by (11) in 3-dB units. 4 This performance measure was first introduced in [8], in the context of code-division multiple access (CDMA) with random spreading, where it was shown to be equivalent to the similarly defined measure as function of the energy per information bit (instead of ).…”

Section: High-snr Measuresmentioning

confidence: 99%

High-SNR power offset in multi-antenna communication

Lozano¹,

Tulino

Verdú

International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings.

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Abstract-The analysis of the multiple-antenna capacity in the highregime has hitherto focused on the highslope (or maximum multiplexing gain), which quantifies the multiplicative increase as a function of the number of antennas. This traditional characterization is unable to assess the impact of prominent channel features since, for a majority of channels, the slope equals the minimum of the number of transmit and receive antennas. Furthermore, a characterization based solely on the slope captures only the scaling but it has no notion of the power required for a certain capacity. This paper advocates a more refined characterization whereby, as a function of dB , the high-capacity is expanded as an affine function where the impact of channel features such as antenna correlation, unfaded components, etc., resides in the zero-order term or power offset. The power offset, for which we find insightful closed-form expressions, is shown to play a chief role for levels of practical interest.

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“…Most studies on the effect of channel spatial correlation on the ergodic capacity do not consider channel estimation errors and assume perfect CSI at the receiver (CSIR) [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…Similar studies on MIMO systems found that the channel spatial correlations among both the transmit antennas and the receive antennas can reduce the capacity at high signal to noise ratio (SNR) [7] or for large number of transmit and receive antennas [8].…”

Section: Introductionmentioning

confidence: 99%

Capacity of MIMO systems: Impact of spatial correlation with channel estimation errors

Zhou

Lamahewa

Sadeghi

et al. 2008

2008 11th IEEE Singapore International Conference on Communication Systems

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Abstract-We study the impact of channel spatial correlation on the ergodic capacity of multiple-input multiple-output (MIMO) systems with channel estimation errors in block-fading channels. We consider transmit antenna correlation and use an accurate capacity lower bound to carry out the theoretical analysis for MIMO systems with and without covariance feedback. We show that for non-feedback systems, the capacity increases with channel correlation at low signal-to-noise ratio (SNR). This finding is in contrast to the existing result for non-feedback systems with perfect channel estimation. For covariance feedback systems, we find that the capacity increases with correlation. We also show the robustness of equal power transmission and the optimality of beamforming at low SNR for non-feedback and covariance feedback systems, respectively. Our numerical results validate our analysis and show that the theoretical low SNR analysis can extend to moderate SNR values.

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Characterizing the statistical properties of mutual information in mimo channels

Cited by 205 publications

References 25 publications

A New Lower Bound on the Ergodic Capacity of Distributed MIMO Systems

A New Lower Bound on the Ergodic Capacity of Distributed MIMO Systems

High-SNR power offset in multi-antenna communication

Capacity of MIMO systems: Impact of spatial correlation with channel estimation errors

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