Non-Orthogonal Unicast and Multicast Transmission for Massive MIMO With Statistical Channel State Information
Author(s) -
Li You,
Jiayuan Xiong,
Ke-Xin Li,
Wenjin Wang,
Xiqi Gao
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2879366
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
We investigate non-orthogonal unicast and multicast (NOUM) transmission for massive multiple-input multiple-output systems, where only statistical channel state information of all user terminals is available at the base station. We adopt a weighted sum of the achievable ergodic unicast rate and multicast rate as the design objective. We first show the closed-form eigenvectors of the optimal unicast and multicast transmit covariance matrices, respectively, which reveals the optimality of beam domain transmission and simplifies the large-dimensional matrix-valued NOUM transmission design into a beam domain power allocation problem. Via invoking the concave-convex procedure, we, then, propose an efficient iterative beam domain power allocation algorithm with guaranteed convergence to a stationary point. In addition, we derive the deterministic equivalent of the objective in each iteration to further reduce the optimization complexity. Simulation results show that the proposed NOUM transmission can provide a significant performance gain in terms of the achievable ergodic unicast-multicast rate region over the conventional orthogonal approach.
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