Training Sequence Design for MIMO Channels: An Application-Oriented Approach
Dimitrios Katselis, Cristian R. Rojas, Mats Bengtsson, Emil, Bj\"ornson, Xavier Bombois, Nafiseh Shariati, Magnus Jansson, H{\aa}kan, Hjalmarsson

TL;DR
This paper develops a flexible framework for designing training sequences in MIMO channels, optimizing for various performance metrics beyond traditional MSE minimization, and demonstrates its advantages through simulations.
Contribution
It introduces a general training sequence design framework for MIMO systems that considers application-specific performance metrics, not just MSE minimization.
Findings
Proposed framework can minimize training energy with quality constraints.
Optimized sequences improve performance for different MIMO applications.
Numerical simulations show superiority over existing methods.
Abstract
In this paper, the problem of training optimization for estimating a multiple-input multiple-output (MIMO) flat fading channel in the presence of spatially and temporally correlated Gaussian noise is studied in an application-oriented setup. So far, the problem of MIMO channel estimation has mostly been treated within the context of minimizing the mean square error (MSE) of the channel estimate subject to various constraints, such as an upper bound on the available training energy. We introduce a more general framework for the task of training sequence design in MIMO systems, which can treat not only the minimization of channel estimator's MSE, but also the optimization of a final performance metric of interest related to the use of the channel estimate in the communication system. First, we show that the proposed framework can be used to minimize the training energy budget subject to a…
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Taxonomy
TopicsAdvanced Wireless Communication Techniques · Advanced MIMO Systems Optimization · Antenna Design and Optimization
