Abstract
This paper studies the design and analysis of optimal training-based beamforming in uncorrelated multiple-input multiple-output (MIMO) channels with known Gaussian statistics. First, given the response of the MIMO channel to a finite sequence of training vectors, the beamforming vector which maximizes the average received signal-to-noise ratio (SNR) over all channel realizations is found. Secondly, the question of what consists of optimal training for a given amount of training is addressed. Upper and lower bounds for the maximum achievable SNR using beamforming are established. Furthermore, optimal training sequences are conjectured to satisfy the Welch bound. The conjecture is supported by the evidence that such sequences achieve close to the upper bound with moderate to large amount of trainings.
| Original language | English (US) |
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| Title of host publication | CISS 2008, The 42nd Annual Conference on Information Sciences and Systems |
| Pages | 902-907 |
| Number of pages | 6 |
| DOIs | |
| State | Published - Sep 22 2008 |
| Event | CISS 2008, 42nd Annual Conference on Information Sciences and Systems - Princeton, NJ, United States Duration: Mar 19 2008 → Mar 21 2008 |
Other
| Other | CISS 2008, 42nd Annual Conference on Information Sciences and Systems |
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| Country/Territory | United States |
| City | Princeton, NJ |
| Period | 3/19/08 → 3/21/08 |
ASJC Scopus subject areas
- Computer Science Applications
- Information Systems
- Control and Systems Engineering