We consider a single cell downlink (DL) massive multiple-input multiple-output (MIMO) set up with user clustering based on statistical information. The problem is to design a fully digital two stage beamforming consisting of slow varying channel statistics based outer beamformer (OBF) and an inner beamformer (IBF) accounting for fast channel variations aiming to reduce the complexity involved in the conventional MIMO processing. Two different methods are considered to design the OBF matrix, so as to reduce the size of the effective channel used for IBF design. A group specific two-stage optimization problem with weighted sum rate maximization (WSRM) objective is formulated to find the IBF for fixed OBF. We begin by proposing centralized IBF design were the optimization is carried out for all sub group jointly with user specific inter-group interference constraints. In order to further reduce the complexity, we propose an iterative solution for group-specific beamformer design via the Karush-Kuhn-Tucker (KKT) conditions for fixed inter group interference (IGI) values with per group transmit power constraint. A low complexity heuristic iterative method is also proposed for managing the inter-group interference. In spite of incurring a small loss in performance, the computational complexity can be saved to a large extent with the group specific processing. The sum rate behavior of various proposed schemes are illustrated using numerical simulations.
Padmanabha Ayswarya, Tölli Antti
A4 Article in conference proceedings
Place of publication:
2018 IEEE Global Communications Conference, GLOBECOM 2018
A. Padmanabhan and A. Tölli, “An Iterative Approach for Inter-Group Interference Management in Two-Stage Precoder Design,” 2018 IEEE Global Communications Conference (GLOBECOM), Abu Dhabi, United Arab Emirates, 2018, pp. 1-6. doi: 10.1109/GLOCOM.2018.8647663
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