Novel noise variance and SNR estimation algorithm for wireless MIMO OFDM systems

Boumard, Sandrine

doi:10.1109/glocom.2003.1258454

Cited by 93 publications

(72 citation statements)

References 7 publications

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“…The estimation of the number of multipath gains and associated time delays has been proposed in [6], where pilot symbols are also needed, and channel multipath power and noise variance are required. In [7], a noise variance and SNR estimator that uses training symbols is developed for multiple antenna OFDM systems. Except for these contributions, to the best of our knowledge, In this letter, we develop noise-variance and PDP estimators for OFDM systems over multipath fading channels; the key is to use the fact that the cyclic prefix contains the repeated samples which will introduce a special correlation structure on the received samples.…”

Section: Introductionmentioning

confidence: 99%

Power delay profile and noise variance estimation for OFDM

Cui

Tellambura

2006

IEEE Commun. Lett.

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Abstract-In this letter, we present cyclic-prefix (CP) based noise-variance and power-delay-profile estimators for Orthogonal Frequency Division Multiplexing (OFDM) systems. Signal correlation due to the use of the CP is exploited without requiring additional pilot symbols. A heuristic estimator and a class of approximate maximum likelihood (ML) estimators are proposed. The proposed algorithms can be applied to both unitary and non-unitary constellations. These algorithms can be readily used for applications such as minimum mean-square error (MMSE) channel estimation.

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Section: Introductionmentioning

confidence: 99%

Power delay profile and noise variance estimation for OFDM

Cui

Tellambura

2006

IEEE Commun. Lett.

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“…NMSE of the average SNR in channel (b) and (c) channels: (a) AWGN channel, (b) a 3-tap time-invariant fading channel with a root mean square delay spread τ rms = 2 samples and (c) a 3-tap time-invariant fading channel with a τ rms = 10 samples. Parameters for considered channels are taken from [6]. The number of independent trials is set to N t = 100000 assuring the high confidence interval of the estimates.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…In [6], Boumard proposed a second-order moment-based SNR estimator for 2 × 2 MIMO OFDM system in slow varying channel in both time and frequency domain. In [5], Ren et al derived its corresponding SISO version keeping the presumption that the channel is time-invariant and that two identical preambles are used for SNR estimation, i.e.…”

Section: B Boumard's Estimatormentioning

confidence: 99%

Preamble-Based SNR Estimation in Frequency Selective Channels for Wireless OFDM Systems

Zivkovic

Mathar

2009

VTC Spring 2009 - IEEE 69th Vehicular Technology Conference

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Abstract-Orthogonalfrequency division multiplexing (OFDM) offers high data rates and robust performance in frequency selective channels by link adaptation utilizing information about the channel quality. A crucial parameter required for adaptive transmission is the signal-to-noise ratio (SNR). In this paper, we propose a novel SNR estimation algorithm for wireless OFDM systems based on the reuse of the synchronization preamble. The periodic structure of the preamble is utilized for the computationally efficient SNR estimation algorithm, based on the second-order moments of received preamble samples. The performance of the proposed algorithm is compared with the MMSE algorithm and two preamble-based algorithms found in the literature. It is shown that the proposed algorithm is robust against frequency selectivity and may therefore be used for subchannel SNR estimation.

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“…Yang pertama adalah estimasi derau dengan menggunakan bantuan data atau data-aided [3] dan yang kedua adalah estimasi derau tanpa bantuan data atau non data-aided [4][5]. Estimasi derau dengan bantuan data artinya adalah algoritma estimasi derau ini membutuhkan bantuan data tambahan seperti sinyal transmisi ataupun urutan data pilot yang dikirimkan di awal transmisi.…”

Section: Jurnal Infotel Vol 8 No 2 November 2016unclassified

Untitled

Farahiyah¹

2016

INFOTEL

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Abstrak -Tiga algoritma estimasi derau tanpa informasi sinyal transmisi dibandingkan hasil performanya. Ketiga algoritma estimasi tersebut yaitu Maximum Likelihood Estimator, algoritma estimasi berdasarkan Cyclic Prefix dan algoritma estimasi dengan metode Forward Consecutive Mean Excision (FCME). Perbandingan dilakukan dengan menggunakan masukan sinyal Digital Video Broadcasting -Terrestrial (DVB-T) dan dengan melakukan variasi nilai signal-to-noise-ratio (SNR) dan jumlah simbol Orthogonal frequency division multiplexing (OFDM). Performa dari ketiganya diukur dengan pengukuran error yang lazim digunakan, yaitu NormalizedMean-Square-Error (NMSE). Cyclic Prefix-Estimator dan Maximum Likelihood-Estimator memiliki performa yang stabil terhadap perubahan SNR, sedangkan FCME-estimator memiliki performa yang berfluktuasi terhadap perubahan SNR. Penambahan jumlah simbol juga menghasilkan performa yang membaik pada ketiganya. Performa dari ketiganya menunjukkan bahwa Maximum Likelihood-Estimator memiliki NMSE yang paling kecil. Artinya bahwa estimator ini memiliki tingkat akurasi yang tinggi. Kata kunci -Estimasi, derau, DVB-T, tanpa sinyal tambahanAbstract -The comparison of the performance of three algorithms of blind noise estimation without a priori information about transmitted signal is conducted in this research. The three estimators are maximum likelihood estimator, estimator based on cyclic prefix and estimator based on Forward consecutive mean excision (FCME). The comparison is done with the input DVB-T signal and with varied SNR and time observation. The performance of the three estimators are measured with NMSE. Cyclic prefix-estimator and Maximum likelihood-estimator has a stable performance against SNR, while FCME estimator has a fluctuative result. The number of simbol has an impact for three estimators, thus the performances are getting better as the number of simbol is inCognitive Radio easing. The comparison shows that maximum likelihood-estimator has the best performances of all. It means that this estimator has high accuracy.

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Novel noise variance and SNR estimation algorithm for wireless MIMO OFDM systems

Cited by 93 publications

References 7 publications

Power delay profile and noise variance estimation for OFDM

Power delay profile and noise variance estimation for OFDM

Preamble-Based SNR Estimation in Frequency Selective Channels for Wireless OFDM Systems

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