Characterizing the statistical properties of mutual information in mimo channels

2003 ◽  
Vol 51 (11) ◽  
pp. 2784-2795 ◽  
Author(s):  
O. Oyman ◽  
R.U. Nabar ◽  
H. Bolcskei ◽  
A.J. Paulraj
Keyword(s):  
Mutual Information ◽  
Statistical Properties ◽  
Mimo Channels

Capacity Analysis for Correlated Multi-Hop MIMO Channels under Colored Noise

2015 ◽  
Vol 1 ◽  
pp. 41
Author(s):  
Nguyen N. Tran ◽  
Ha X. Nguyen
Keyword(s):  
Computational Complexity ◽  
Mutual Information ◽  
Closed Form Solution ◽  
Optimal Solution ◽  
Form Solution ◽  
Maximization Problem ◽  
Capacity Analysis ◽  
Mimo Channels ◽  
Average Mutual Information ◽  
Channel Output

A capacity analysis for generally correlated wireless multi-hop multi-input multi-output (MIMO) channels is presented in this paper. The channel at each hop is spatially correlated, the source symbols are mutually correlated, and the additive Gaussian noises are colored. First, by invoking Karush-Kuhn-Tucker condition for the optimality of convex programming, we derive the optimal source symbol covariance for the maximum mutual information between the channel input and the channel output when having the full knowledge of channel at the transmitter. Secondly, we formulate the average mutual information maximization problem when having only the channel statistics at the transmitter. Since this problem is almost impossible to be solved analytically, the numerical interior-point-method is employed to obtain the optimal solution. Furthermore, to reduce the computational complexity, an asymptotic closed-form solution is derived by maximizing an upper bound of the objective function. Simulation results show that the average mutual information obtained by the asymptotic design is very closed to that obtained by the optimal design, while saving a huge computational complexity.

Ergodic Mutual Information Analysis for Multi-Keyhole MIMO Channels

2011 ◽  
Vol 10 (6) ◽  
pp. 1754-1763 ◽  
Author(s):  
Caijun Zhong ◽  
Shi Jin ◽  
Kai-Kit Wong ◽  
Matthew R. McKay
Keyword(s):  
Mutual Information ◽  
Information Analysis ◽  
Mimo Channels ◽  
Mutual Information Analysis

Capacity of the Class of MIMO Channels With Incomplete CDI—Properties of Mutual Information for a Class of Channels

2009 ◽  
Vol 55 (8) ◽  
pp. 3725-3734 ◽  
Author(s):  
Charalambos D. Charalambous ◽  
Stojan Z. Denic ◽  
Costas Constantinou
Keyword(s):  
Mutual Information ◽  
Mimo Channels

Applying spatial mutual information to AIS data

2021 ◽  
pp. 1-11
Author(s):  
Bruce A. McArthur ◽  
Anthony W. Isenor
Keyword(s):  
Mutual Information ◽  
Movement Patterns ◽  
Random Variable ◽  
Statistical Properties ◽  
Spatial Dependency ◽  
New Interpretation ◽  
Reporting Data ◽  
Attribute Value

Abstract This paper examines a new interpretation for spatial mutual information based on the mutual information between an attribute value and a spatial random variable. This new interpretation permits the measurement of variations in spatial mutual information over the domain, not only answering the question of whether a spatial dependency exists and the strength of that dependency, but also allowing the identification of where such dependencies exist. Using simulated and real vessel reporting data, the properties of this new interpretation of spatial mutual information are explored. The utility of the technique in detecting spatial boundaries between regions of data having different statistical properties is examined. The technique is shown to successfully identify vessel traffic boundaries, crossing points between traffic lanes, and transitions between regions having differing vessel movement patterns.

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