Linear Algebraic Beamforming Design for Multiuser MISO Interference Channels: A Reduction in Search Space Dimension

Area of Science:

• Wireless communication systems
• Signal processing
• Information theory

Background:

• Multiuser multiple-input single-output (MUI-MIMO) interference channels present significant challenges in wireless communication.
• Designing effective beamformers is crucial for optimizing system performance, especially under slowly time-varying block fading conditions.
• Existing optimal schemes can be computationally intensive, necessitating more efficient approaches.

Purpose of the Study:

• To develop a novel method for deriving closed-form solutions for near-optimal transmit beamformers.
• To address beamforming design in both low and high signal-to-noise ratio (SNR) regimes for MUI-MIMO interference channels.
• To enhance the efficiency of beamformer design compared to traditional optimal methods.

Main Methods:

• Leveraging side information from channel correlation between adjacent coding blocks.
• Employing a linear algebraic approach for deriving closed-form beamforming solutions.
• Comparing the efficiency against optimal schemes based on Gaussian input by analyzing search space dimensions.

Main Results:

• The proposed method provides closed-form solutions for effective beamforming in low and high SNR regimes.
• The linear algebraic approach significantly reduces the average number of search space dimensions.
• Computer simulations demonstrate near-optimal performance in terms of average sum-rate.

Conclusions:

• The developed method offers an efficient and effective approach to designing near-optimal transmit beamformers for MUI-MIMO interference channels.
• The technique's reliance on channel correlation and linear algebra provides a practical advantage over computationally complex optimal schemes.
• The findings contribute to improved spectral efficiency and overall system performance in challenging wireless environments.