Continual Learning-Based Fast Beamforming Adaptation in Downlink MISO Systems

Zhou, Huan; Xia, Wenchao; Zhao, Haitao; Zhang, Jun; Ni, Yiyang; Zhu, Hongbo

doi:10.1109/lwc.2022.3216330

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…In literature [18], an adaptation beamforming called method is addressed, the advantage of which is its satisfying performance in a time-varying environment without large computation. In literature [19], an efficient beamforming method called based is proposed for dealing with all kinds of complicated situation, which obtains better result with low complexity.…”

Section: Introductionmentioning

confidence: 99%

A Novel Adaptive Beamforming Scheme for Array Signal Data Processing

Shi

Yan

Hou

et al. 2023

Preprint

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When the desired signal data exists in the array received data or the steering vector has a mismatch problem, the current traditional adaptive beamformers will suffer from the effect of the desired signal cancellation phenomenon, resulting in a sharp decline in performance. To address the occurrence of desired signal cancellation, an improved matrix projection-based efficient beamforming method is proposed. Firstly, based on spatial partitioning technology, a significant projection matrix for interference-plus-noise space (INS) is constructed. Secondly, using the constructed key projection matrix, the sample data covariance matrix is projected into the INS to achieve the goal of suppressing the desired signal data information. Finally, the weight data vector is calculated by Capon beamformer. The proposed algorithm does not require iterative search for the optimal solution, which has the advantage of a small amount of calculation. Simulation experiments have verified that the proposed method has significant advantages in suppressing the desired data signals. Especially when the desired data signal has a large power, the signal-to-interference-plus-noise ratio (SINR) of the proposed algorithm is better than that of the compared algorithms under the conditions of random directionality errors or local scattering errors between the desired signal and interference.

show abstract

Section: Introductionmentioning

confidence: 99%

A Novel Adaptive Beamforming Scheme for Array Signal Data Processing

Shi

Yan

Hou

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

Lifelong Learning for AoI and Energy Tradeoff Optimization in Satellite-Airborne-Terrestrial Edge Computing Networks

Wu,

Lorenzo,

Liu

2023

2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

View full text Add to dashboard Cite

A novel adaptive beamforming scheme for array signal data processing

Shi,

Yan,

Hou

et al. 2023

J Wireless Com Network

View full text Add to dashboard Cite

When the desired signal data exists in the array received data or the steering vector has a mismatch problem, the current traditional adaptive beamformers will suffer from the effect of the desired signal cancelation phenomenon, resulting in a sharp decline in performance. To address the occurrence of desired signal cancelation, an improved matrix projection-based efficient beamforming method is proposed. Firstly, based on spatial partitioning (SP) technology, a significant projection matrix for interference-plus-noise space (INS) is constructed. Secondly, using the constructed key projection matrix, the sample data covariance matrix is projected into the INS to achieve the goal of suppressing the desired signal data information. Finally, the weight data vector is calculated by Capon beamformer. The proposed algorithm does not require an iterative search for the optimal solution, which has the advantage of a small amount of calculation. Simulation experiments have verified that the proposed method has significant advantages in suppressing the desired data signals. Especially when the desired data signal has large power, the signal-to-interference-plus-noise ratio (SINR) of the proposed algorithm is better than that of the compared algorithms under the conditions of random directionality errors or local scattering errors between the desired signal and interference.

show abstract

Continual Learning-Based Fast Beamforming Adaptation in Downlink MISO Systems

Cited by 3 publications

References 15 publications

A Novel Adaptive Beamforming Scheme for Array Signal Data Processing

A Novel Adaptive Beamforming Scheme for Array Signal Data Processing

Lifelong Learning for AoI and Energy Tradeoff Optimization in Satellite-Airborne-Terrestrial Edge Computing Networks

A novel adaptive beamforming scheme for array signal data processing

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