Journal
IEEE TRANSACTIONS ON COMMUNICATIONS
Volume 69, Issue 3, Pages 1707-1722Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCOMM.2021.3053021
Keywords
Array signal processing; Optimization; Radio frequency; Channel estimation; Precoding; Complexity theory; Adaptive arrays; Massive MIMO; large-scale antenna arrays; low-complexity; limited RF chains; hybrid beamforming; adaptive algorithms; joint iterative optimization
Funding
- U.K. Engineering and Physical Sciences Research Council (EPSRC) [EP/P008402/2, EP/R001588/1]
- EPSRC [EP/P008402/2] Funding Source: UKRI
Ask authors/readers for more resources
This paper proposes a joint iterative optimization based hybrid beamforming technique for massive MU-MIMO systems, which achieves the global optimum solution for the system sum-rate maximization with low complexity and fast convergence, without the need for real-time channel state information. Simulation results demonstrate the superior performance of the proposed technique compared to existing techniques.
This paper proposes a joint iterative optimization based hybrid beamforming technique for massive MU-MIMO systems. The proposed technique jointly and iteratively optimizes the transmitter precoders and combiners, aiming to approach the global optimum solution for the system sum-rate maximization problem. The proposed technique develops an adaptive algorithm exploiting the stochastic gradients (SG) of the local beamformers and provides low-complexity closed-form solutions. Furthermore, an efficient adaptive scheme is developed based on the proposed adaptive algorithm and the closed-form solutions. The proposed algorithm requires the signal-to-interference-plus-noise ratio (SINR) feedback from each user and a limited size transition vector to be exchanged between the transmitter and receivers at each step to update beamformers locally. Analytic result shows that the proposed adaptive algorithm achieves low-complexity when the array size is large and is able to converge within a small number of iterations. Simulation result shows that the proposed technique is able to achieve superior performance comparing to the existing state-of-art techniques. In addition, the knowledge of instantaneous channel state information (CSI) is not required as the channels are also adaptively estimated with each coherence time which is a practical assumption since the CSI is usually unavailable or have time-varying nature in real-time applications.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available