On the Performance of Sliding Window TD-LMMSE Channel Estimation for 5G Waveforms in High Mobility Scenario

Saideh, Michel; Berbineau, Marion; Dayoub, Iyad

doi:10.1109/tvt.2018.2845551

Cited by 10 publications

(5 citation statements)

References 12 publications

(17 reference statements)

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“…Before implementing IFFT, x[n, k] undergoes a transformation process where it is multiplied by the beta carrier (β) in order to provide enhanced robustness to the samples as they are been prepared to propagate through the wireless channel. Possible loss of sub-carrier orthogonality due to pulse shaping at SFB is also minimised from this transformation, since the cyclic prefix of the conventional OFDM transceivers are replaced (in FBMC OFDM-OQAM systems) with well-designed prototype filters that have good localisation properties [133], in noth the frequency and time domains. The beta carrier (β) is mathematically given as:…”

Section: Ofdm-oqam Transceivermentioning

confidence: 99%

Review of Channel Estimation for Candidate Waveforms of Next Generation Networks

et al. 2019

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The advancement in wireless communication applications encourages the use of effective and efficient channel estimation (CE) techniques because of the varying behaviour of the Rayleigh fading channel. In most cases, the emphasis of most proposed CE schemes is to improve the CE performance and complexity for ensuring quality signal reception and improved system throughput. Candidate waveforms whose designs are based on filter bank multi-carrier (FBMC) modulation techniques such as filter bank orthogonal frequency division multiplexing based on offset quadrature amplitude modulation (OFDM-OQAM), universal filtered multicarrier (UFMC) and generalised frequency division multiplexing based on offset quadrature amplitude modulation (GFDM-OQAM) are no exception to the use of these proposed CE techniques in the literature. These schemes are considered as potential waveform candidates for the physical/media access control layer of the emerging fifth generation (5G) networks. Therefore, pinpoint CE techniques represent an important requirement for these waveforms to attain their full potentials. In this regard, this paper reviews the concept of CE as applicable to these waveforms as well as other waveform candidates under consideration in the emerging 5G networks. Since the design of the majority of the waveform candidates is filter based, a review of the general filter design considerations is presented in this paper. Secondly, we review general CE techniques for candidate waveforms of next generation networks and classify some of the studied CE techniques. In particular, we classify the CE schemes used in filter bank OFDM-OQAM and GFDM-OQAM based transceivers and present a performance comparison of some of these CE schemes. Besides, the paper reviews the performances of two linear CE schemes and three adaptive based CE schemes for two FBMC based waveform candidates assuming near perfect reconstruction (NPR) and non-perfect reconstruction (Non-PR) filter designs over slow and fast frequency selective Rayleigh fading channels. The results obtained are documented through computer simulations, where the performances of the studied CE schemes in terms of the normalised mean square error (NMSE) are analysed. Lastly, we summarise the findings of this work and suggest possible research directions in order to improve the potentials of the studied candidate waveforms over Rayleigh fading channels.

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Section: Ofdm-oqam Transceivermentioning

confidence: 99%

Review of Channel Estimation for Candidate Waveforms of Next Generation Networks

et al. 2019

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“…In [11], they use MIMO system which helps to avoid Doppler rate estimation and thereby avoid Doppler rate estimation. Carrier channels, in which the estimation of Doppler rate varies between the packets, make the computation difficult to perform the optimal operations.…”

Section: Introductionmentioning

confidence: 99%

“…Traditional CSI estimation methods [10] sometimes necessitate the use of high-performance computation [11]. As a result, machine learning models are now being used by numerous writers in their CSI estimation work, which is a significant advancement.…”

Section: Introductionmentioning

confidence: 99%

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Machine Learning Empowered Accurate CSI Prediction for Large-Scale 5G Networks

Mageswari¹,

Mohammad²,

Dulam³

et al. 2022

Wireless Communications and Mobile Computing

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Wi-Fi networks rely on channel estimation to ensure their performance. The computational complexity and dependability of fifth generation telecommunication networks have significantly improved using supervised learning. In this paper, we develop a channel estimation model that uses a machine learning approach and the study uses multipath channel simulations for the estimation of channel state information (CSI) over arbitrary transceiver antennas. The simulation is conducted to test the efficacy of the model against various machine learning channel estimation models. The results of simulation show that the proposed model obtains increased channel estimation quality than other methods. Further, the bit error rate is recorded low among other methods using the machine learning model. Thus, it is seen that the proposed method achieves a reduced mismatch rate of 1.26 × 10 − 1.5 than other methodson Doppler frequency during channel estimation, where the mismatch rate is higher in existing methods.

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“…In Table 1 of 5G communication systems, the correlation between Signal-to-Noise Ratio (SNR) and Bit Error Rate (BER) changes according to the modulation waveform and access technique employed [26]. SNR denotes the ratio of signal power to noise power within the communication channel, while BER measures the likelihood of incorrect bit transmission, typically due to noise or interference [27]. As SNR increases, BER generally decreases, indicating improved communication reliability are shown above figure 4 [28].…”

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confidence: 99%

Advanced Nonlinear Channel Estimation Techniques for 5G Wireless Communication Systems

Guntukala Surendher

2024

cana

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In this paper, 5G wireless communication systems requirement, standards and practical challenges are studied thoroughly. Multicarrier modulation schemes for 4G wireless communication systems were applied to 5G wireless communication systems for better suitability. Traditional channel estimation techniques for 4G were applied to 5G wireless communication systems and observed better applicability. An M-estimator method waveforms for 5G in Gaussian and non-Gaussian environments is proposed, studied and analyzed. 5G networks transceiver model both Gaussian and non-Gaussian environments for various multicarrier modulation schemes was studied and analyzed. Comparison of 5G candidate waveforms in terms of excess emissions, peak to average power ratio, Flexibility, complicated and spectral efficiency was done and suitability for 5G systems with Gaussian and non-Gaussian environments was observed. Bit error rate comparisons were performed on all candidate waveforms with respect to SNR. MSE versus SNR simulations for proposed estimator-based channel estimation method in various non-Gaussian channel environments was carried out and studied. In simulations, proposed channel estimation technique was compared with other techniques and the proposed method outperforms in 5G networks in non-Gaussian environments with various candidate multicarrier waveforms.

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On the Performance of Sliding Window TD-LMMSE Channel Estimation for 5G Waveforms in High Mobility Scenario

Cited by 10 publications

References 12 publications

Review of Channel Estimation for Candidate Waveforms of Next Generation Networks

Review of Channel Estimation for Candidate Waveforms of Next Generation Networks

Machine Learning Empowered Accurate CSI Prediction for Large-Scale 5G Networks

Advanced Nonlinear Channel Estimation Techniques for 5G Wireless Communication Systems

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