On Limits of Wireless Communications in a Fading Environment when UsingMultiple Antennas
Wireless Personal Communications: An International Journal
Random matrix theory and wireless communications
Communications and Information Theory
Introduction to Space-Time Wireless Communications
Introduction to Space-Time Wireless Communications
Characterizing the statistical properties of mutual information in MIMO channels
IEEE Transactions on Signal Processing
On the capacity of multiple-antenna systems in Rician fading
IEEE Transactions on Wireless Communications
Capacity of MIMO Rician channels
IEEE Transactions on Wireless Communications
Capacity of a mobile multiple-antenna communication link in Rayleigh flat fading
IEEE Transactions on Information Theory
On the capacity of spatially correlated MIMO Rayleigh-fading channels
IEEE Transactions on Information Theory
Outage mutual information of space-time MIMO channels
IEEE Transactions on Information Theory
General Capacity Bounds for Spatially Correlated Rician MIMO Channels
IEEE Transactions on Information Theory
On the Ergodic Capacity of Rank-1 Ricean-Fading MIMO Channels
IEEE Transactions on Information Theory
On the monotonicity of the generalized Marcum and Nuttall Q-functions
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Mutual information statistics and beamforming performance analysis of optimized LoS MIMO systems
IEEE Transactions on Communications
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In a fading environment, the statistical distribution of the mutual information of a multiple-input multiple-output (MIMO) system depends on the joint distribution of the eigenvalues of a Wishart matrix, and is quite complex in general. We obtain here simple expressions for the distributions of the determinant and the trace of a Wishart matrix. Based on the obtained distributions, we derive some simple and tight bounds on the complementary cumulative distribution function (CCDF) of the mutual information of a MIMO system in Rician fading environments. The bounds obtained on the CCDF of mutual information provide further insights into the channel mutual information, and show the effects of the system parameters on the mutual information distribution explicitly. In addition, results for the Rayleigh channels are obtained as a special case.