An enhanced channel estimation technique with adaptive pilot spacing for OFDM system

Rezgui, Cherif; Grayaa, Khaled

doi:10.1109/isncc.2016.7746098

Cited by 6 publications

(2 citation statements)

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“…On the one hand, channel interpolation in time or frequency domain is an important aspect of the pilot symbol aided channel estimators in Orthogonal Frequency Division Multiplexing (OFDM) communication systems [158]. Various interpolation techniques have been adopted to improve the estimation accuracy of channel state information (CSI) and reduce the bit error rate (BER), such as linear interpolation, cubic interpolation, spline interpolation, polynomial interpolation, adaptive polar linear interpolation, its enhanced version, two-dimensional (2D) adaptive filtering, matrix factorization, and others [159]- [163]. In [7], the authors demonstrated that the misleading frequency interpolation caused by noise (or mal-estimation of DMC) leads to performance degradation.…”

Section: A Communicationsmentioning

confidence: 99%

A Survey of Dense Multipath and Its Impact on Wireless Systems

Jiang¹,

Wang²,

Miao

et al. 2022

IEEE Open J. Antennas Propag.

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In recent years wireless propagation channel research has paid considerable attention to dense multipath, which is an indispensable part of propagation channels and may significantly contribute to the received power in variety of environments and frequency bands. Mathematical representation of dense multipath is different from that of specular components (SCs) due to its distinct propagation mechanism and impact on system performance. Therefore, accurate understanding and modeling of dense multipath together with SCs are important for parametric channel estimation and for reliable simulation in wireless applications. This paper first presents a systematic survey of studies of dense multipath in terms of different representations, channel modeling approaches and estimation methods. Thereafter, a comprehensive review of the characteristics and impact of dense multipath on performance of communication, localization and sensing systems is provided. Finally, open research topics are discussed.INDEX TERMS Channel estimation, channel modeling, characteristics, communication, dense multipath.

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Section: A Communicationsmentioning

confidence: 99%

A Survey of Dense Multipath and Its Impact on Wireless Systems

Jiang¹,

Wang²,

Miao

et al. 2022

IEEE Open J. Antennas Propag.

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“…Orthogonal Frequency Division Multiplexing has been a great focus of interest in designing to generate waveforms for the next-generation 5G wireless network [1]. The main components of 5G radio which are New Radio (NR) and Long Term Evolution (LTE) prefer Cyclic Prefix OFDM (CP-OFDM) to do modulation best fitted.…”

Section: Introductionmentioning

confidence: 99%

Effect of DNN Approximation for Channel Estimation and Signal Detection on OFDM Applications

Çalışır¹

2022

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This paper offers a deep learning approximation to realize channel estimation and signal detection that creates the main communication structure skeleton for the orthogonal frequency-division multiplexing (OFDM) system known as an efficient modulation type on 5G. This letter offers an application of deep learning to handle the wireless OFDM channels' end-to-end conduct. First, channel state information (CSI) is predicted explicitly that differs from existing OFDM receivers, then detected the transmitted symbols utilizing the predicted CSI. In the end, CSI is predicted by the suggested deep learning approximation indirectly and transmitted symbols are directly recovered. The structure of the designed receiver occurs of a layer of DNN and soft decisions, which resolves the issues channel estimation error, time delay, and limitation of decoding between users in classic detection techniques. In the simulation results, it is observed that the receiver has powerful stability on the power distribution of user, not only convenient for the linear channel, but also for nonlinear channel when enhancement the number of users, also detection can be well on the receiver. Generally, the efficiency of the modulation system decreases with the features of the multipath channel utilized for transmission. Channel estimation and detection of symbols utilize to reduce the impacts of the channel, which needs high computation and bandwidth conventionally. This paper is used deep neural networks (DNN) for detecting the signal, in this way much effort in detecting the channel is prevented. The proposed method saves priceless bandwidth via used CP in OFDM with a big increase in SNR.

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