Pilot Tone Selection For Channel Estimation In A Mobile Ofdm System *

Negi,; Cioffi, Raffaele

doi:10.1109/icce.1998.678433

Cited by 356 publications

(178 citation statements)

References 4 publications

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“…If the channel span is indeed limited to within L coefficients, in the presence of white noise, the error variance of the re-computed frequency-domain coefficients is the same as if they were estimated directly [3]. While direct estimation in the frequency domain requires all K data symbols, indirect estimation in the time-domain requires only L. If the channel is truly sparse, and only the J significant coefficients out of L are kept, the error variance will be reduced by a factor of L/J [4].…”

Section: Algorithm Overviewmentioning

confidence: 99%

“…. .ĥ L−1 (n) before taking the FFT [3]. This approach befits a minimumphase (causal) channel, in which the strongest time-domain coefficient h 0 (n) is followed by other coefficients.…”

Section: Algorithm Overviewmentioning

confidence: 99%

“…Channel impulse response is often shorter than an OFDM block, and can thus be represented by fewer than K coefficients that it takes to represent its transfer function on the K subcarriers. A certain number L < K coefficients of the time-domain response can be efficiently estimated using L equally-spaced data symbols [3], a method used in [2]. We suggest a slight but important modification to this method to make it applicable to a general underwater channel, where the strongest signal arrival may not be the first one.…”

Section: Introductionmentioning

confidence: 99%

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OFDM for underwater acoustic communications: Adaptive synchronization and sparse channel estimation

Stojanovic

2008

2008 IEEE International Conference on Acoustics, Speech and Signal Processing

119

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A phase synchronization method, which provides non-uniform frequency offset compensation needed for wideband OFDM [1], is coupled with low-complexity channel estimation in the time domain. Sparsing of the channel impulse response leads to an improved performance, while adaptive synchronization supports decision-directed operation and yields low overhead. System performance is demonstrated using experimental data transmitted over a 1 km shallow water channel in the 19 kHz-31 kHz band.

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Section: Algorithm Overviewmentioning

confidence: 99%

“…. .ĥ L−1 (n) before taking the FFT [3]. This approach befits a minimumphase (causal) channel, in which the strongest time-domain coefficient h 0 (n) is followed by other coefficients.…”

Section: Algorithm Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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OFDM for underwater acoustic communications: Adaptive synchronization and sparse channel estimation

Stojanovic

2008

2008 IEEE International Conference on Acoustics, Speech and Signal Processing

119

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“…현재 유망한 채널 추정 기술로서 주파수 영역에서 수행되는 파일럿 심 볼 기반 채널 추정 기법 [2,3] 이 존재하는데, 이 방법은 구현이 쉽기 때문에 많이 사용되고 있다. 파일럿의 범 위가 전체 스펙트럼을 차지하는 경우, 파일럿들이 균 등하게 배치되는 빗 형태 방식이 지금까지 최적이라 고 알려져 있다 [4] . …”

Section: ⅰ 서 론unclassified

Pilot Assisted Channel Frequency Response Estimation for an OFDM System with a Comb-Type Pilot Pattern

Kim

Yoon

2014

The Journal of Korea Information and Communications Society

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The pilot assisted channel frequency response (CFR) estimation schemes for an OFDM-based system with virtual subcarriers are analyzed under the assumption that pilot symbols are located according to a comb-type pattern in the OFDM block. In particular, as the minimum mean square error (MMSE) based scheme aiming to directly predict the channel impulse response and the MMSE based scheme aiming to suppress the leakage have not been clearly compared, by proving that the mean square errors (MSEs) of the latter scheme is always larger than that of the former scheme, this paper shows that the former scheme is superior to the latter scheme.Moreover, the impact of the number of pilots on the performances of the MMSE and least-square based channel estimation schemes are investigated. The performance analyses of the presented schemes are confirmed by computer simulation.

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“…The ratio of the total power of the distinctively spaced pilot tones ξ 0 to that of the uniformly spaced ones ξ 1 is set to ξ 0 : denoted by C can be defined as C = D ∪ U, where D ∩ U = φ. In order to recover the channel exactly by exploiting the proposed training sequence, the number of the non-zero pilot tones N C should be no less than the multipath delay spread of the channel L [16].…”

Section: Training Sequence Constructionmentioning

confidence: 99%

Frequency Offset Estimation for OFDM Systems with a Novel Frequency Domain Training Sequence

Jiang¹

2006

IEICE Transactions on Communications

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SUMMARY A novel frequency domain training sequence and the corresponding carrier frequency offset (CFO) estimator are proposed for orthogonal frequency division multiplexing (OFDM) systems over frequency-selective fading channels. The proposed frequency domain training sequence comprises two types of pilot tones, namely distinctively spaced pilot tones with high energies and uniformly spaced ones with low energies. Based on the distinctively spaced pilot tones, integer CFO estimation is accomplished. After the subcarriers occupied by the distinctively spaced pilot tones and their adjacent subcarriers are nulled for the sake of interference cancellation, fractional CFO estimation is executed according to the uniformly spaced pilot tones. By exploiting a predefined lookup table making the best of the structure of the distinctively spaced pilot tones, computational complexity of the proposed CFO estimator can be decreased considerably. With the aid of the uniformly spaced pilot tones generated from Chu sequence with cyclically orthogonal property, the ability of the proposed estimator to combat multipath effect is enhanced to a great extent. Simulation results illustrate the good performance of the proposed CFO estimator.

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Pilot Tone Selection For Channel Estimation In A Mobile Ofdm System *

Cited by 356 publications

References 4 publications

OFDM for underwater acoustic communications: Adaptive synchronization and sparse channel estimation

OFDM for underwater acoustic communications: Adaptive synchronization and sparse channel estimation

Pilot Assisted Channel Frequency Response Estimation for an OFDM System with a Comb-Type Pilot Pattern

Frequency Offset Estimation for OFDM Systems with a Novel Frequency Domain Training Sequence

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