Effect of polynomial interpolations on the estimation performance of a frequency‐selective Rayleigh channel in orthogonal frequency division multiplexing systems

Savaux, Vincent; Djoko-Kouam, Moïse; Louët, Yves; Skrzypczak, Alexandre

doi:10.1049/iet-spr.2014.0053

Cited by 9 publications

(25 citation statements)

References 20 publications

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“…Resource management & Scheduling [25]- [27] V Synchronization [28]- [37] III.A Uplink demodulation [38]- [47] IV.A & IV.B Downlink demodulation [48]- [53] IV.B Energy Saving [54]- [57] V.H & VI.B Positioning [58]- [60] VI.A Challenges & perspectives [17], [20]- [22], [61]- [64] I Release 13 [65]- [77] I to V 3GPP references Release 14 [78]- [85] VI.A Release 15 [86]- [92] I & VI.B…”

Section: Topicsmentioning

confidence: 99%

“…Among the numerous interpolation techniques, we can mention here the 2-D and 2×1-D linear minimum mean square error (LMMSE) interpolation [46], [52], the Kalman interpolation [51], or the polynomial interpolations [50]. Note that in practice, the polynomial interpolations are usually implemented in devices due to their low computational cost, even if they generate interpolation errors [53] that slightly reduce performance.…”

Section: B Receiver Design At the Uementioning

confidence: 99%

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A Tutorial on NB-IoT Physical Layer Design

Kanj¹,

Savaux²,

Guen³

2020

IEEE Commun. Surv. Tutorials

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The Internet of things (IoT) is transforming the whole of society. It represents the next evolution of the Internet and will significantly improve the ability to gather and analyze data, as well as the ability to control devices remotely. In this respect, the usage of connected devices is continuously growing with the expansion of the applications being offered to individuals and industries. To address IoT market needs, many low-power wide-area (LPWA) technologies have been developed, some operating on licensed frequencies (e.g., narrowband-IoT [NB-IoT] and Long-Term Evolution-M [LTE-M]), and others on unlicensed frequencies (e.g., LoRa, Sigfox, etc.). In this paper, we address the Release 13 of the NB-IoT 3rd generation partnership project (3GPP) standardized LPWA technology and provide a tutorial on its physical layer (PHY) design. Specifically, we focus on the characteristics and the scheduling of downlink and uplink physical channels at the NB-IoT base station side and the user equipment (UE) side. The goal is to help readers easily understand the NB-IoT system without having to read all the 3GPP specifications or the state-of-the-art papers that generally describe the system. To this end, each presented concept is followed by examples and concrete use-cases to further aid in the reader's comprehension. Finally, we briefly describe and highlight the new features added to the NB-IoT system in Releases 14 and 15.

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Section: Topicsmentioning

confidence: 99%

Section: B Receiver Design At the Uementioning

confidence: 99%

A Tutorial on NB-IoT Physical Layer Design

Kanj¹,

Savaux²,

Guen³

2020

IEEE Commun. Surv. Tutorials

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“…More details concerning the developments leading to (9) and the s 2 j k value in (10) are provided in [12]. In a more general way, the variance of the global variable j (independently of the position k) denoted by s 2 j is given by…”

Section: Statistics Of the Errors Of Interpolationmentioning

confidence: 99%

“…Thus, theoretical values of the mean square error (MSE) of estimation and BER floor are derived, and match the numerical results. However, Savaux et al [12] is limited to the binary phase shift keying (BPSK) and 4-quadrature amplitude modulation (4-QAM) constellations, whereas higher order constellations are usually used, especially in broadband wireless communications systems.…”

Section: Introductionmentioning

confidence: 99%

“…The remaining of this paper is organised as follows: the system model and the channel estimation using polynomial interpolations are presented in Section 2. The major results from [12] regarding the MSE and BER performances of such systems are reminded in Section 2.4. The analysis of the BER floor achieved by a 16-QAM OFDM signal is undertaken in Section 3.…”

Section: Introductionmentioning

confidence: 99%

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Theoretical bit error floor analysis of 16‐QAM OFDM signal with channel estimation using polynomial interpolation

Savaux

Skrzypczak²,

Louët

2016

IET signal process.

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International audienceThis study deals with a bit error rate (BER) floor performance analysis for orthogonal frequency division multiplexing (OFDM) systems using pilot-aided channel estimation with polynomial interpolations. Such a performance analysis has been previously undertaken in the literature, but is limited to binary phase shift keying and 4-quadrature amplitude modulation (4-QAM) constellations. The main contribution of this study is then to analyse the BER floor achieved by a 16-QAM OFDM signal in a Rayleigh channel. To achieve this, the binary error probability is obtained by carrying out the analysis on maximum significant bits (MSB) and least significant bits (LSB). The MSB leads to the similar results as those obtained in 4-QAM, but very specific developments are required to obtain the error probability of the LSB. Numerical results show that the proposed BER performance analysis is valid for the 16-QAM constellation

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Mean square error analysis and linear minimum mean square error application for preamble‐based channel estimation in orthogonal frequency division multiplexing/offset quadrature amplitude modulation systems

Savaux

Bader

2015

IET Communications

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International audienceIn this paper the performance of different preamble-based channel estimation techniques is analyzed for orthogonalfrequency division multiplexing/offset QAM (OFDM/OQAM) modulation systems. Three pilot allocationmethods, the pair of pilot (POP), the interference cancellation method (ICM), and the interference approximationmethod (IAM) are considered. A theoretical expression of the estimation mean square error (MSE) is performedfor each of them, which considers the selectivity of the channel and the interferences from all the neighboringtime-frequency positions. Moreover, an application of the linear minimum mean square error (LMMSE) estimator inOFDM/OQAM is investigated and an analysis of its MSE performance is provided as well. It is shown that, due tothe intrinsic interference, the MSE of the channel estimation inevitably reaches an error floor whatever the appliedmethod is. Numerical results show that the theoretical MSE assessments match those obtained by simulation. Inaddition to the MSE, the bit error rate (BER) performance for the different channel estimators is depicted

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Effect of polynomial interpolations on the estimation performance of a frequency‐selective Rayleigh channel in orthogonal frequency division multiplexing systems

Cited by 9 publications

References 20 publications

A Tutorial on NB-IoT Physical Layer Design

A Tutorial on NB-IoT Physical Layer Design

Theoretical bit error floor analysis of 16‐QAM OFDM signal with channel estimation using polynomial interpolation

Mean square error analysis and linear minimum mean square error application for preamble‐based channel estimation in orthogonal frequency division multiplexing/offset quadrature amplitude modulation systems

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