Variational Inference-based Joint Interference Mitigation and OFDM Equalization Under High Mobility

Zhou, Jingrong; Qin, Jiayin; Wu, Yik-Chung

doi:10.1109/lsp.2015.2449658

Cited by 6 publications

(6 citation statements)

References 20 publications

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“…Unlike the quasi-static channels, however, the timevarying channels destroy the subchannel orthogonality, incurring intercarrier interference (ICI) and eventually resulting in a serious degradation in system performance. In order to overcome the ICI effect, various methodologies such as differential coding [5], ICI self-cancellation [6], Doppler diversity [7] and ICI cancellation-based equalization [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24], have been proposed. Among them, the ICI cancellation-based equalization approach is the most promising because of its good performance under the situation of perfect channel estimation.…”

Section: Introductionmentioning

confidence: 99%

“…To circumvent this issue, widely linear (WL) filtering techniques [12][13][14][15] and non-linear equalizers [16][17][18][19][20][21][22][23][24] have been suggested.…”

Section: Introductionmentioning

confidence: 99%

“…As is well known, the maximum likelihood (ML) algorithm is optimal in terms of ICI cancellation for OFDM signal detection, but it requires prohibitively computational complexity. To address this drawback, ML variants with less computations have been proposed [23,24]. In [23], the OFDM signal detection is first formulated as an integer least squares (ILS) problem.…”

Section: Introductionmentioning

confidence: 99%

“…However, since the a posteriori probability of transmitted data vector is estimated via matrix factorization, it is inaccurate when the number of subcarriers becomes large. On the other hand, [24] devises a robust approach under the variational inference framework which achieves a low bit-error-rate (BER) performance even when the non-uniform noise is present.…”

Section: Introductionmentioning

confidence: 99%

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Accurate signal detection for BPSK-OFDM systems in time-varying channels

Huang

Sun

et al. 2017

Digital Signal Processing

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Binary phase shift keying (BPSK) orthogonal frequency division multiplexing (OFDM) has been adopted in the fourth-generation wireless communications. However, the real-valued property of BPSK-OFDM signals has not yet been utilized for channel equalization. In this work, this property is employed to develop a new equalizer based on the minimum mean square error (MMSE) criterion, leading to considerable enhancement in signal detection. In particular, the proposed equalizer is able to achieve 3 dB improvement over the existing MMSE equalizer in large signal-to-noise ratio region, and more robust against channel estimation errors. Moreover, successive detection technique employed in the devised method is able to make use of diversity in time-varying channels, resulting in further performance enhancement. Additionally, the computational complexity of the proposed approach is analyzed. Simulation results are included to illustrate its performance superiority and computational attractiveness.

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Section: Introductionmentioning

confidence: 99%

“…To circumvent this issue, widely linear (WL) filtering techniques [12][13][14][15] and non-linear equalizers [16][17][18][19][20][21][22][23][24] have been suggested.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Accurate signal detection for BPSK-OFDM systems in time-varying channels

Huang

Sun

et al. 2017

Digital Signal Processing

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“…However, in practical situations, the interferer's signals are in general asynchronous. Zhou et al 's work [6] deals with the estimation of noise plus interference power together with successive soft data estimation at each subcarrier. Here, we focus on channel estimation based on pilots.…”

Section: M2 59655 Villeneuve D'ascq Cédex France Full List Of Authomentioning

confidence: 99%

Analysis of the maximum likelihood channel estimator for OFDM systems in the presence of unknown interference

Dermoune

Simon

2017

EURASIP J. Adv. Signal Process.

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This paper is a theoretical analysis of the maximum likelihood (ML) channel estimator for orthogonal frequency-division multiplexing (OFDM) systems in the presence of unknown interference. The following theoretical results are presented. Firstly, the uniqueness of the ML solution for practical applications, i.e., when thermal noise is present, is analytically demonstrated when the number of transmitted OFDM symbols is strictly greater than one. The ML solution is then derived from the iterative conditional ML (CML) algorithm. Secondly, it is shown that the channel estimate can be described as an algebraic function whose inputs are the initial value and the means and variances of the received samples. Thirdly, it is theoretically demonstrated that the channel estimator is not biased. The second and the third results are obtained by employing oblique projection theory. Furthermore, these results are confirmed by numerical results.

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A novel joint channel estimation and equalization algorithm for MIMO-SCFDE systems over doubly selective channels

Xie

Chen

2018

Digital Signal Processing

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Variational Inference-based Joint Interference Mitigation and OFDM Equalization Under High Mobility

Cited by 6 publications

References 20 publications

Accurate signal detection for BPSK-OFDM systems in time-varying channels

Accurate signal detection for BPSK-OFDM systems in time-varying channels

Analysis of the maximum likelihood channel estimator for OFDM systems in the presence of unknown interference

A novel joint channel estimation and equalization algorithm for MIMO-SCFDE systems over doubly selective channels

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