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Luca Marinelli

dblp:36/1963 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2006
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Physical-layer communications · 100%
Theoretical computer science
1 paper
Information theory · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications › channel modeling › MIMO channel modeling
correlated MIMO channel
0.112006
Capacity and Character Expansions: Moment-Generating Function and Other Exact Results for MIMO Correlated Channels · IEEE Trans. Inf. Theory 2006
Physical-layer communications
MIMO
0.112006
Capacity and Character Expansions: Moment-Generating Function and Other Exact Results for MIMO Correlated Channels · IEEE Trans. Inf. Theory 2006
Information theory
channel capacity
0.112006
Capacity and Character Expansions: Moment-Generating Function and Other Exact Results for MIMO Correlated Channels · IEEE Trans. Inf. Theory 2006
Information theory › probability theory
moment generating function
0.112006
Capacity and Character Expansions: Moment-Generating Function and Other Exact Results for MIMO Correlated Channels · IEEE Trans. Inf. Theory 2006

Methods — techniques the papers use, named apart from their topics

lie group representation theory · 0.1eigenvalue distribution analysis · 0.1
YearPublicationVenuePosition
2006 Capacity and Character Expansions: Moment-Generating Function and Other Exact Results for MIMO Correlated Channels
abstract
A promising new method from the field of representations of Lie groups is applied to calculate integrals over unitary groups, which are important for multiantenna communications. To demonstrate the power and simplicity of this technique, a number of recent results are rederived, using only a few simple steps. In particular, we derive the joint probability distribution of eigenvalues of the matrix GGdagger, with G a nonzero mean or a semicorrelated Gaussian random matrix. These joint probability distribution functions can then be used to calculate the moment generating function of the mutual information for Gaussian multiple-input multiple-output (MIMO) channels with these probability distribution of their channel matrices G. We then turn to the previously unsolved problem of calculating the moment generating function of the mutual information of MIMO channels, which are correlated at both the receiver and the transmitter. From this moment generating function we obtain the ergodic average of the mutual information and study the outage probability. These methods can be applied to a number of other problems. As a particular example, we examine unitary encoded space-time transmission of MIMO systems and we derive the received signal distribution when the channel matrix is correlated at the transmitter end
Steven H. Simon, Aris L. Moustakas, Luca Marinelli
IEEE Trans. Inf. Theory3