Two-Stage Subspace Constrained Precoding in Massive MIMO Cellular Systems

We propose a subspace constrained precoding scheme that exploits the spatial channel correlation structure in massive MIMO cellular systems to fully unleash the tremendous gain provided by massive antenna array with reduced channel state information (CSI) signaling overhead. The MIMO precoder at each base station (BS) is partitioned into an inner precoder and a Transmit (Tx) subspace control matrix. The inner precoder is adaptive to the local CSI at each BS for spatial multiplexing gain. The Tx subspace control is adaptive to the channel statistics for inter-cell interference mitigation and Quality of Service (QoS) optimization. Specifically, the Tx subspace control is formulated as a QoS optimization problem which involves an SINR chance constraint where the probability of each user's SINR not satisfying a service requirement must not exceed a given outage probability. Such chance constraint cannot be handled by the existing methods due to the two stage precoding structure. To tackle this, we propose a bi-convex approximation approach, which consists of three key ingredients: random matrix theory, chance constrained optimization and semidefinite relaxation. Then we propose an efficient algorithm to find the optimal solution of the resulting bi-convex approximation problem. Simulations show that the proposed design has significant gain over various baselines.Comment: 13 pages, accepted by IEEE Transactions on Wireless Communication

A Generalized Framework on Beamformer Design and CSI Acquisition for Single-Carrier Massive MIMO Systems in Millimeter Wave Channels

In this paper, we establish a general framework on the reduced dimensional channel state information (CSI) estimation and pre-beamformer design for frequency-selective massive multiple-input multiple-output MIMO systems employing single-carrier (SC) modulation in time division duplex (TDD) mode by exploiting the joint angle-delay domain channel sparsity in millimeter (mm) wave frequencies. First, based on a generic subspace projection taking the joint angle-delay power profile and user-grouping into account, the reduced rank minimum mean square error (RR-MMSE) instantaneous CSI estimator is derived for spatially correlated wideband MIMO channels. Second, the statistical pre-beamformer design is considered for frequency-selective SC massive MIMO channels. We examine the dimension reduction problem and subspace (beamspace) construction on which the RR-MMSE estimation can be realized as accurately as possible. Finally, a spatio-temporal domain correlator type reduced rank channel estimator, as an approximation of the RR-MMSE estimate, is obtained by carrying out least square (LS) estimation in a proper reduced dimensional beamspace. It is observed that the proposed techniques show remarkable robustness to the pilot interference (or contamination) with a significant reduction in pilot overhead

Beamspace Aware Adaptive Channel Estimation for Single-Carrier Time-varying Massive MIMO Channels

In this paper, the problem of sequential beam construction and adaptive channel estimation based on reduced rank (RR) Kalman filtering for frequency-selective massive multiple-input multiple-output (MIMO) systems employing single-carrier (SC) in time division duplex (TDD) mode are considered. In two-stage beamforming, a new algorithm for statistical pre-beamformer design is proposed for spatially correlated time-varying wideband MIMO channels under the assumption that the channel is a stationary Gauss-Markov random process. The proposed algorithm yields a nearly optimal pre-beamformer whose beam pattern is designed sequentially with low complexity by taking the user-grouping into account, and exploiting the properties of Kalman filtering and associated prediction error covariance matrices. The resulting design, based on the second order statistical properties of the channel, generates beamspace on which the RR Kalman estimator can be realized as accurately as possible. It is observed that the adaptive channel estimation technique together with the proposed sequential beamspace construction shows remarkable robustness to the pilot interference. This comes with significant reduction in both pilot overhead and dimension of the pre-beamformer lowering both hardware complexity and power consumption.Comment: 7 pages, 3 figures, accepted by IEEE ICC 2017 Wireless Communications Symposiu

Energy Efficiency and Asymptotic Performance Evaluation of Beamforming Structures in Doubly Massive MIMO mmWave Systems

Future cellular systems based on the use of millimeter waves will heavily rely on the use of antenna arrays both at the transmitter and at the receiver. For complexity reasons and energy consumption issues, fully digital precoding and postcoding structures may turn out to be unfeasible, and thus suboptimal structures, making use of simplified hardware and a limited number of RF chains, have been investigated. This paper considers and makes a comparative assessment, both from a spectral efficiency and energy efficiency point of view, of several suboptimal precoding and postcoding beamforming structures for a cellular multiuser MIMO (MU-MIMO) system with large number of antennas. Analytical formulas for the asymptotic achievable spectral efficiency and for the global energy efficiency of several beamforming structures are derived in the large number of antennas regime. Using the most recently available data for the energy consumption of phase shifters and switches, we show that fully-digital beamformers may actually achieve a larger energy efficiency than lower-complexity solutions, as well as that low-complexity beam-steering purely analog beamforming may in some cases represent a good performance-complexity trade-off solution.Comment: Submitted to IEEE Transactions on Green Communications and Networkin