Ahmed Al-Asadi
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Ahmed Al-Asadi has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Hongxiang Li
Department of Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA
1 shared publication - Ibtesam R. K. Al-Saedi
College of Communications Engineering, University of Technology- Iraq, Baghdad, Iraq
1 shared publication - Laith Alzubaidi
Centre for Data Science, Queensland University of Technology, Brisbane, Australia
1 shared publication - Saddam K. Alwane
University of Technology (UOT)
1 shared publication
Latest Publications
- Open Access
Enhanced MIMO CSI Estimation Using ACCPM with Limited Feedback
Multiple Input and Multiple Output (MIMO) is a promising technology to enable spatial multiplexing and improve throughput in wireless communication networks. To obtain the full benefits of MIMO systems, the Channel State Information (CSI) should be acquired correctly at the transmitter side for optimal beamforming design. The analytical centre-cutting plane method (ACCPM) has shown to be an appealing way to obtain the CSI at the transmitter side. This paper adopts ACCPM to learn down-link CSI in both single-user and multi-user scenarios. In particular, during the learning phase, it uses the null space beamforming vector of the estimated CSI to reduce the power usage, which approaches zero when the learned CSI approaches the optimal solution. Simulation results show our proposed method converges and outperforms previous studies. The effectiveness of the proposed method was corroborated by applying it to the scattering channel and winner II channel models.
Open AccessEnhanced MIMO CSI Estimation Using ACCPM with Limited Feedback
Multiple Input and Multiple Output (MIMO) is a promising technology to enable spatial multiplexing and improve throughput in wireless communication networks. To obtain the full benefits of MIMO systems, the Channel State Information (CSI) should be acquired correctly at the transmitter side for optimal beamforming design. The analytical centre-cutting plane method (ACCPM) has shown to be an appealing way to obtain the CSI at the transmitter side. This paper adopts ACCPM to learn down-link CSI in both single-user and multi-user scenarios. In particular, during the learning phase, it uses the null space beamforming vector of the estimated CSI to reduce the power usage, which approaches zero when the learned CSI approaches the optimal solution. Simulation results show our proposed method converges and outperforms previous studies. The effectiveness of the proposed method was corroborated by applying it to the scattering channel and winner II channel models.