2 January 2019

Dynamic RF Chain Selection for Energy Efficient and Low Complexity Hybrid Beamforming in Millimeter Wave MIMO Systems

Kaushik, A., Thompson, J., Vlachos, E., Tsinos, C., Chatzinotas, S.

IEEE Transactions on Green Communications and Networking

Abstract

This paper proposes a novel architecture with a framework that dynamically activates the optimal number of radio frequency (RF) chains used to implement hybrid beam- forming in a millimeter wave (mmWave) multiple-input and multiple-output (MIMO) system. We use fractional programming to solve an energy efﬁciency maximization problem and exploit the Dinkelbach method (DM)-based framework to optimize the number of active RF chains and data streams. This solution is updated dynamically based on the current channel conditions, where the analog/digital (A/D) hybrid precoder and combiner matrices at the transmitter and the receiver, respectively, are designed using a codebook-based fast approximation solution called gradient pursuit (GP). The GP algorithm shows less run time and complexity while compared to the state-of-the- art orthogonal matching pursuit (OMP) solution. The energy and spectral efﬁciency performance of the proposed frame- work is compared with the existing state-of-the-art solutions, such as the brute force (BF), the digital beamformer, and the analog beamformer. The codebook-free approaches to design the precoders and combiners, such as alternating direction method of multipliers (ADMMs) and singular value decompo- sition (SVD)-based solution are also shown to be incorporated into the proposed framework to achieve better energy efﬁciency performance.

Type 2

Publication IEEE Transactions on Green Communications and Networking

DOI 10.1109/tgcn.2019.2931613

Date January 2019

Research 6G UAVs

Key Contributions

Proposing a novel hybrid beamforming architecture with dynamic RF chain selection to optimize energy efficiency.
Introducing a fractional programming framework based on the Dinkelbach method to determine the optimal number of active RF chains.
Developing a low-complexity codebook-based gradient pursuit (GP) algorithm for hybrid precoder design, outperforming state-of-the-art methods like OMP.
Demonstrating significant improvements in energy efficiency and reduced computational complexity compared to brute-force and fully digital beamforming approaches.

Performance comparison of energy efficiency across different hybrid beamforming techniques under varying SNR conditions.

This figure demonstrates that the proposed dynamic RF chain selection framework achieves superior energy efficiency compared to conventional hybrid beamforming methods, particularly at higher SNR levels.

Convergence behavior and bit error rate performance of the proposed Dinkelbach method-based optimization framework.

The results show rapid convergence of the optimization algorithm and significantly lower bit error rates compared to benchmark methods, validating the effectiveness of the proposed approach.

Power consumption analysis of the proposed framework versus conventional hybrid beamforming approaches across different SNR values.

The proposed dynamic RF chain selection reduces power consumption by up to 30% compared to fully-connected hybrid beamforming, especially at moderate SNR levels.

Computational complexity comparison of the proposed gradient pursuit algorithm versus state-of-the-art methods.

The proposed framework achieves substantially lower computational complexity (reduced by 40-60%) while maintaining comparable performance to more complex optimization techniques.

Research 6G UAVs