Channel modeling based on comprehensive measurements for DVB-T mobile applications

Bug, Steffen; Wengerter, C.; Gaspard, I.; Jakoby, Rolf

doi:10.1109/imtc.2001.928878

Cited by 7 publications

(11 citation statements)

References 5 publications

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“…The soft GA's basic parameters were the same as those specified in Table 12, except that the mutation scheme was fixed to BQM, while the population size and the number of generations were fixed to X ¼ 500 and Y ¼ 5, respectively. The specific TC code configuration and the parameters of the 8-path dispersive fading channel model of [332] used in the simulations are summarized in Table 14. Channel estimation was assumed to be perfect.…”

Section: B Examplementioning

confidence: 99%

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

2007

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Section: B Examplementioning

confidence: 99%

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

2007

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“…In this section, we present our simulation results for both the Sample-Spaced and the Fractionally-Spaced RC-MMSE CIR estimation schemes advocated in the context of both OFDM and MC-CDMA systems communicating over eight-path dispersive Rayleigh fading channel characterized in [7]. The framevarient fading channel characterized by Bug's channel model [7] were encountered at OFDM symbol-normilized Doppler frequency of F d = 0.01.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The framevarient fading channel characterized by Bug's channel model [7] were encountered at OFDM symbol-normilized Doppler frequency of F d = 0.01.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…For forward error correction (FEC) we use 1 2 -rate turbo coding [9] employing two constraint-length K = 3 Recursive Systematic Convolutional (RSC) component codes and a 124-bit WCDMA code interleaver [8]. The octally represented generator polynomials of (7,5) were used.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…We employed the eight-path Rayleigh-fading Bug channel model characterised in [7], using the delay spread of τrms = 1µs and the OFDM-symbol-normalized Doppler frequency of FD = 0.01. Figure 3(a) demonstrates the NMSE exhibited by the DDCE scheme of Figure 2 employing both the SS-CIR estimator described in Section III-B and the FS-CIR estimator derived in Section III-C in the context of both the OFDM and the MC-CDMA systems considered.…”

Section: Simulation Resultsmentioning

confidence: 99%

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Sample-spaced and fractionally-spaced cir estimation aided decision directed channel estimation for OFDM and MC-CDMA

Akhtman

Hanzo

VTC-2005-Fall. 2005 IEEE 62nd Vehicular Technology Conference, 2005.

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Abstract-The achievable performance of decision-directed channel estimation (DDCE) is analysed in the context of both OFDM and MC-CDMA systems. Two different estimation methods suitable for both OFDM and MC-CDMA systems are considered, which employ samplespaced (SS) as well as fractionally-spaced (FS) a posteriori channel impulse response (CIR) estimators. The performance of both estimation methods is compared and it is shown that the DDCE scheme employing the FS-CIR estimator outperforms its SS-CIR estimator-based counterpart. Furthermore, the FS-CIR estimator-based method exhibits higher robustness to various channel parameters such as the channel's root mean square delay spread. Finally, it is shown that the MC-CDMA system employing the channel estimation scheme advocated outperforms its OFDM counterpart.

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Sampling Frequency Offset Estimation for Pilot-Aided OFDM Systems in Mobile Environment

Zhao

2010

Wireless Pers Commun

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In orthogonal frequency division multiplexing (OFDM) systems, most of the conventional sampling frequency offset (SFO) estimation methods work under the assumption of time-invariant or slow time-variant channels. In mobile environment, the time-variant channel significantly degrades the accuracy of SFO estimation. To solve the problem, we first analyze the properties of time-variant channels. If terminal moves within some tens of the wavelength of radio frequency (RF) signal, channel path delay almost remains unchanged. For most practical OFDM systems, our analysis indicates that channel path delay can be regarded as unchanged during the interval of some tens of OFDM symbols in time-variant channels. Based on the analysis, we propose a novel SFO estimation method for pilot-aided OFDM systems. Different from the conventional methods, the proposed method estimates SFO by detecting the variation of the symbol timing error caused by SFO. The detection is finished by implementing correlation between the channel impulse responses (CIRs) estimated by different OFDM symbols. Performance of the proposed method is simulated and compared with that of two conventional post-FFT methods. Numerical results show that, the proposed SFO estimation method performs better than the conventional methods not only in time-variant channels, but also at low SNRs and large residual carrier frequency offsets (CFOs).

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Channel modeling based on comprehensive measurements for DVB-T mobile applications

Cited by 7 publications

References 5 publications

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

Sample-spaced and fractionally-spaced cir estimation aided decision directed channel estimation for OFDM and MC-CDMA

Sampling Frequency Offset Estimation for Pilot-Aided OFDM Systems in Mobile Environment

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