Multiuser Transmit Beamforming via Regularized Channel Inversion: A Large System Analysis

Nguyen, Van‐Dinh; Evans, Jamie

doi:10.1109/glocom.2008.ecp.176

Cited by 99 publications

(96 citation statements)

References 12 publications

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“…After some algebraic manipulations we obtain (44). Note that for τ 2 = 0 and α = α ⋆• , (44) is identical to the asymptotic SINR derived in [3] and for the inter-cell interference-free system in [13]. For β = 1, equation (44) simplifies to γ…”

Section: Sum Rate Maximizing Regularizationmentioning

confidence: 71%

“…This work extends the results in [1]- [3] by applying novel results from the field of large dimensional random matrices. In particular we consider a general channel with per-user correlation and imperfect CSIT.…”

Section: Introductionmentioning

confidence: 77%

“…The quadratic equation (43) has exactly one distinct real root (40), which completes the proof. Notice that for perfect CSIT (τ = 0) we have α ⋆• = 1/(βρ), which corresponds to the RZF precoder derived in [1], [3]. As mentioned in [1], for large M the RZF precoder is identical to the minimum mean square error (MMSE) precoder in [6].…”

Section: Sum Rate Maximizing Regularizationmentioning

confidence: 99%

“…and in (a) we applied the matrix inversion lemma [9, Lemma 2.2] twice together with (3). For M large, we apply [10, Lemma 2.7] and obtain…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Deterministic Equivalent for the SINR of Regularized Zero-Forcing Precoding in Correlated MISO Broadcast Channels with Imperfect CSIT

Wagner

Couillet

Debbah

et al. 2011

2011 IEEE International Conference on Communications (ICC)

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Abstract-This paper considers the MISO broadcast channel with different spatial correlations of the user vector channels. The base station implements regularized zero-forcing (RZF) precoding based on an imperfect channel estimation. We derive a deterministic equivalent of the signal-to-interference plus noise ratio (SINR) by applying novel results from the field of large dimensional random matrices. Based on this deterministic equivalent, we compute the sum rate maximizing RZF precoder which is given in closed form for independent and identically distributed channels. Simulations show that the accuracy of the approximated SINR extends well into finite dimensions.

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Section: Sum Rate Maximizing Regularizationmentioning

confidence: 71%

Section: Introductionmentioning

confidence: 77%

Section: Sum Rate Maximizing Regularizationmentioning

confidence: 99%

“…and in (a) we applied the matrix inversion lemma [9, Lemma 2.2] twice together with (3). For M large, we apply [10, Lemma 2.7] and obtain…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Deterministic Equivalent for the SINR of Regularized Zero-Forcing Precoding in Correlated MISO Broadcast Channels with Imperfect CSIT

Wagner

Couillet

Debbah

et al. 2011

2011 IEEE International Conference on Communications (ICC)

View full text Add to dashboard Cite

show abstract

“…We note that the value of the regularization parameter ξ ⋆• that maximizes the secrecy sum-rate differs from the value ξ ⋆• ns = β/ρ that maximizes the sum-rate without secrecy requirements [28].…”

Section: Large-system Resultsmentioning

confidence: 99%