A PDF Estimation-Based Iterative MIMO Signal Detection With Unknown Interference

Veselinović, N.; Matsumoto, Tad; Juntti, Markku

doi:10.1109/lcomm.2004.832731

Cited by 2 publications

(2 citation statements)

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“…Interestingly, the optimal value of k 0 that minimizes BER is shown to be rather insensitive to the change of the other parameters. Moreover, it is shown in [20] that for LM = 1, the optimal parameter k 0 also does not depend on the signal-to-noise ratio [21]. From Figure 3, it can be seen that k 0 ≈ 2 is a good choice for a wide range of situations.…”

Section: (πσ 2 ) Lm E −( X(k)−ti) H ( X(k)−ti)/σ 2 (44)mentioning

confidence: 92%

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Iterative PDF Estimation-Based Multiuser Diversity Detection and Channel Estimation with Unknown Interference

Veselinović

Matsumoto

Juntti

2005

EURASIP J. Adv. Signal Process.

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The equivalent diversity order of multiuser detector employing multiple receive antennas and minimum mean squared error (MMSE) processing for frequency-selective channels is decreased if it aims at suppressing unknown cochannel interference (UCCI) while detecting multiple users' signals. This is an unavoidable consequence of linear processing at the receiver. In this paper, we propose a new multiuser signal detection scheme with the aim to preserve the detector's diversity order by taking into account the structure of the UCCI. We use the fact that the structure of the UCCI appears in the probability density function (PDF) of the UCCI plus noise, which can be characterized as multimodal Gaussian. A kernel smoothing PDF estimation based receiver is derived. The PDF estimation can be based on training symbols only (noniterative PDF estimation) or on training symbols as well as feedback from the decoder (iterative PDF estimation). It is verified through simulations that the proposed receiver significantly outperforms the conventional covariance estimation in channels with low frequency selectivity. The iterative PDF estimation significantly outperforms the noniterative PDF estimation-based receiver with minor training overhead.

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Section: (πσ 2 ) Lm E −( X(k)−ti) H ( X(k)−ti)/σ 2 (44)mentioning

confidence: 92%

“…In [21], the authors have derived a new receiver that can preserve the diversity gain by estimating the PDF of the UCCI plus noise. The signal processing algorithm shown in [22] is used in the first iteration and the kernel-based PDF estimation [20,23] is applied for the following iterations.…”

Section: Introductionmentioning

confidence: 99%