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Register a new userRobust Precoder Design for 3D Massive MIMO Downlink with A Posteriori Channel Model
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An-An Lu
Publication date
2020
fields
Informatics Engineering
and research's language is
English
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In this paper, we investigate the robust linear precoder design for three dimensional (3D) massive multi-input multi-output (MIMO) downlink with uniform planar array (UPA) and imperfect channel state information (CSI). In practical massive MIMO with UPAs, the number of antennas in each column or row is usually limited. The straightforward extension of the conventional DFT based beam domain channel model widely used in massive MIMO with uniform linear arrays (ULAs) can not apply. To overcome this issue, we establish a new beam domain channel model by using sampled steering vectors. Then, a novel method to obtain the beam domain channel power matrices and the instantaneous beam domain channel coefficients is proposed, and an a posteriori beam domain channel model which includes the channel aging and the spatial correlation is established. On the basis of the a posteriori channel model, we consider the robust precoder design with the expected weighted sum-rate maximization under a total power constraint. By viewing the power constraint as a Riemannian manifold, we transform the constrained optimization problem into an unconstrained optimization problem on the Riemannian manifold. Then, we derive an iterative algorithm to obtain the optimal precoders by setting the Riemannian gradient of the objective function to zero. Furthermore, we propose a low complexity robust precoder design by replacing the expected rates in the objective function with their upper bounds. Simulation results show that the proposed precoders can achieve significant performance gain than the widely used regularized zero forcing (RZF) precoder and signal to leakage noise ratio (SLNR) precoder.
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In this paper, the design of robust linear precoders for the massive multi-input multi-output (MIMO) downlink with imperfect channel state information (CSI) is investigated. The imperfect CSI for each UE obtained at the BS is modeled as statistical CSI under a jointly correlated channel model with both channel mean and channel variance information, which includes the effects of channel estimation error, channel aging and spatial correlation. The design objective is to maximize the expected weighted sum-rate. By combining the minorize-maximize (MM) algorithm with the deterministic equivalent method, an algorithm for robust linear precoder design is derived. The proposed algorithm achieves a stationary point of the expected weighted sum-rate maximization problem. To reduce the computational complexity, two low-complexity algorithms are then derived. One for the general case, and the other for the case when all the channel means are zeros. For the later case, it is proved that the beam domain transmission is optimal, and thus the precoder design reduces to the power allocation optimization in the beam domain. Simulation results show that the proposed robust linear precoder designs apply to various mobile scenarios and achieve high spectral efficiency.
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