Optimised periodic precoder-based blind channel estimation for MIMO-OFDM systems

Gupta, Bhasker; Gupta, Shivani; Singh, Ashutosh Kumar; Joshi, Hem Dutt

doi:10.1080/21681724.2017.1378375

Cited by 4 publications

(3 citation statements)

References 28 publications

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“…One approach to address this issue is to parameterise the unitary matrices that represent the precoders as scalar parameters using Givens rotations [26]. This approach yields a unique set of scalar parameters that completely capture the characteristics of unitary matrices (such as the precoding matrices) using a set of parameters φ k,l and θ k,l , as shown in (10). A unitary matrix V t of size m × m can be decomposed a follows:…”

Section: Precoder Adaptationmentioning

confidence: 99%

“…State-of-the-art approaches to precoder design, targeted for 5G related MIMO applications. Precoder design and use in established 5G channel models like 3GPP SCM, WINNER-II that are suitable for specific scenarios are discussed in [2,3,[5][6][7][8][9][10][11]. More generalised models that incorporate massive MIMO, V2V, HST and mmW small-scale fading models for 5G and beyond 5G applications have also seen research interest lately [12,13].…”

Section: Introductionmentioning

confidence: 99%

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Lattice All-Pass Filter based Precoder Adaptation for MIMO Wireless Channels

Mehta¹,

Bharath²,

Appaiah³

et al. 2023

Preprint

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Modern 5G communication systems employ multiple-input multiple-output (MIMO) in conjunction with orthogonal frequency division multiplexing (OFDM) to enhance data rates, particularly for wideband millimetre wave (mmW) applications. Since these systems use a large number of subcarriers, feeding back the estimated precoder for even a subset of subcarriers from the receiver to the transmitter is prohibitive. Moreover, such frequency domain approaches also do not exploit the predominant line-of-sight component that is present in such channels to reduce feedback. In this work, we view the precoder in the time domain as a matrix all-pass filter, and model the discrete-time precoder filter using a matrix-lattice structure that aids in reducing the overall feedback while still maintaining the desired frequency-phase delay profile. This provides an efficient precoder representation across the subcarriers using fewer coefficients, and is amenable to tracking over time with much lower feedback than past approaches. Compared to frequency domain geodesic interpolation, Givens rotation based parameterisation, and the angle-delay domain approach that depends on approximate discrete-time representation, the proposed approach yields higher achievable rates with a much lower feedback burden. Via extensive simulations over mmW channel models, we confirm the effectiveness of our claims, and show that the proposed approach can reduce the feedback burden by up to 70%.

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Section: Precoder Adaptationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Lattice All-Pass Filter based Precoder Adaptation for MIMO Wireless Channels

Mehta¹,

Bharath²,

Appaiah³

et al. 2023

Preprint

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show abstract

“…In the middle of conventional air-interface methods, Orthogonal Frequency Division Multiplexing (OFDM) systems have recently attracted great interest [8,9]. Nowadays, the strategies of the Multiple Input Multiple Output (MIMO) based OFDM system are the main patterns of future remote communications that have been adopted by the 4th generation of communication standards [10].…”

Section: Introductionmentioning

confidence: 99%

Blind Channel Estimation Using Enhanced Independent Component Analysis for MIMO-OFDM System

2022

IJIES

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Blind Source Separation (BSS) is a process of separating a set of source signals from mixed-signal without the help of information of source signals. In some noisy acoustic surroundings, instinctive class detection is completely dependent on vocalization which remains a stimulating task. To identify the definite classes easily, the source signals have to be detached from the mixed signals and this separation procedure is considered as a substantial pre-processing phase before the detection procedure takes place. This research mainly focuses on the issues of BSS in bio-acoustic mixed signals. Independent Component Analysis (ICA) is current technique in the area of BSS that can discrete the mixed-signal and also utilizes Negentropy as its objective function. However, this method is penetrating to the separation matrix and it cannot diverge. So, the bootstrap ICA procedures with Fast and Robust Bootstrap (FRB) method is developed which is applicable for all the signals. The quality of separated source signals using Enhanced-ICA and other algorithms are compared and evaluated according to MATLAB toolbox metrics. The results show that Enhanced-ICA with negentropy is used for finding a maximum non-gaussianity which achieves the BER performances of 0.00019 which is better than existing Discrete Wavelet Transform based BSS (DWT-BSS) and Modified Newton with Improved Animal Migration Optimization (MN-IAMO).

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