Fast matrix inversion updates for massive MIMO detection and precoding

In this letter, methods and corresponding complexities for fast matrix inversion updates in the context of massive multiple-input multiple-output (MIMO) are studied. In particular, we propose an on-the-fly method to recompute the zero forcing (ZF) filter when a user is added or removed from the system. Additionally, we evaluate the recalculation of the inverse matrix after a new channel estimation is obtained for a given user. Results are evaluated numerically in terms of bit error rate (BER) using the Neumann series approximation as the initial inverse matrix. It is concluded that, with fewer operations, the performance after an update remains close to the initial one.info:eu-repo/semantics/acceptedVersio

Adaptive and Iterative Multi-Branch MMSE Decision Feedback Detection Algorithms for MIMO Systems

In this work, decision feedback (DF) detection algorithms based on multiple processing branches for multi-input multi-output (MIMO) spatial multiplexing systems are proposed. The proposed detector employs multiple cancellation branches with receive filters that are obtained from a common matrix inverse and achieves a performance close to the maximum likelihood detector (MLD). Constrained minimum mean-squared error (MMSE) receive filters designed with constraints on the shape and magnitude of the feedback filters for the multi-branch MMSE DF (MB-MMSE-DF) receivers are presented. An adaptive implementation of the proposed MB-MMSE-DF detector is developed along with a recursive least squares-type algorithm for estimating the parameters of the receive filters when the channel is time-varying. A soft-output version of the MB-MMSE-DF detector is also proposed as a component of an iterative detection and decoding receiver structure. A computational complexity analysis shows that the MB-MMSE-DF detector does not require a significant additional complexity over the conventional MMSE-DF detector, whereas a diversity analysis discusses the diversity order achieved by the MB-MMSE-DF detector. Simulation results show that the MB-MMSE-DF detector achieves a performance superior to existing suboptimal detectors and close to the MLD, while requiring significantly lower complexity.Comment: 10 figures, 3 tables; IEEE Transactions on Wireless Communications, 201

A square-root adaptive V-BLAST algorithm for fast time-varying MIMO channels

Abstract — Among the methods that have been proposed for a Multiple-Input Multiple-Output (MIMO) receiver, the V-BLAST algorithm provides a good compromise between transmission rate, achievable diversity, and decoding complexity. In this paper, we derive a new adaptive V-BLAST type equalization scheme for fast time varying, flat fading MIMO channels. The proposed equalizer stems from the Cholesky factorization of MIMO system’s output data autocorrelation matrix and the equalizer’s filters are updated in time using numerically robust unitary Givens rotations. The new square-root algorithm exhibits identical performance to a recently proposed V-BLAST adaptive algorithm, offering at the same time substantially reduced computational complexity. Moreover, as expected due to its squareroot form and verified by simulations, the algorithm exhibits particularly favourable numerical behaviour. I

A square-root adaptive V-BLAST algorithm for fast time-varying MIMO channels

Abstract—Among the methods that have been proposed for a multiple-input multiple-output (MIMO) receiver, the V-BLAST algorithm provides a good compromise between transmission rate, achievable diversity, and decoding complexity. In this letter, we derive a new adaptive V-BLAST-type equalization scheme for fast time-varying, flat-fading MIMO channels. The proposed equalizer stems from the Cholesky factorization of the MIMO system’s output data autocorrelation matrix, and the equalizer filters are updated in time using numerically robust unitary Givens rotations. The new square-root algorithm exhibits identical performance to a recently proposed V-BLAST adaptive algorithm, offering at the same time noticeable reduction in computational complexity. Moreover, as expected due to its square-root form and verified by simulations, the algorithm exhibits particularly favorable numerical behavior. Index Terms—Adaptive equalization, multiple-input multiple-output (MIMO), time-varying channels, V-BLAST