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HighSNR power offset in multiantenna communication
 IEEE Transactions on Information Theory
, 2005
"... Abstract—The analysis of the multipleantenna capacity in the high regime has hitherto focused on the high slope (or maximum multiplexing gain), which quantifies the multiplicative increase as a function of the number of antennas. This traditional characterization is unable to assess the impact of ..."
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Cited by 91 (18 self)
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Abstract—The analysis of the multipleantenna capacity in the high regime has hitherto focused on the high slope (or maximum multiplexing gain), which quantifies the multiplicative increase as a function of the number of antennas. This traditional characterization is unable to assess the impact of prominent channel features since, for a majority of channels, the slope equals the minimum of the number of transmit and receive antennas. Furthermore, a characterization based solely on the slope captures only the scaling but it has no notion of the power required for a certain capacity. This paper advocates a more refined characterization whereby, as a function of �f, the high capacity is expanded as an affine function where the impact of channel features such as antenna correlation, unfaded components, etc., resides in the zeroorder term or power offset. The power offset, for which we find insightful closedform expressions, is shown to play a chief role for levels of practical interest. Index Terms—Antenna correlation, channel capacity, coherent communication, fading channels, high analysis, multiantenna arrays, Ricean channels.
Mutual information and eigenvalue distribution of MIMO Ricean channels
 in Proc. Int. Symp. Information Theory and Its Applications (ISITA’04
, 2004
"... This paper presents an explicit expression for the marginal probability density distribution of the unordered eigenvalues of a noncentral Wishart matrix HH † where H can represent a multipleinput multipleoutput channel obeying the Ricean law. By integrating over this marginal density distribution, ..."
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Cited by 17 (3 self)
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This paper presents an explicit expression for the marginal probability density distribution of the unordered eigenvalues of a noncentral Wishart matrix HH † where H can represent a multipleinput multipleoutput channel obeying the Ricean law. By integrating over this marginal density distribution, the corresponding ergodic mutual information is characterized also in explicit form. 1.
Delayspread distribution for multimode fiber with strong mode coupling
 IEEE Photon. Technol. Lett
, 2012
"... Abstract — In the strong mode coupling regime, the delay spread of multimode fiber is statistically the same as the difference between the maximum and minimum eigenvalues of a Gaussian unitary ensemble. We study the delayspread distribution using three methods: 1) numerical evaluation of the Fredho ..."
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Cited by 2 (2 self)
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Abstract — In the strong mode coupling regime, the delay spread of multimode fiber is statistically the same as the difference between the maximum and minimum eigenvalues of a Gaussian unitary ensemble. We study the delayspread distribution using three methods: 1) numerical evaluation of the Fredholm determinant; 2) numerical integration based on the Andréief identity; and 3) approximation based on the Tracy–Widom distribution. Results obtained using the Fredholm determinant and the Andréief identity are virtually indistinguishable. The approximation based on the Tracy–Widom distribution is sufficiently accurate for most engineering purposes when the number of modes is at least 12. In a digital equalizer, a memory length of four to five times the groupdelay standard deviation is sufficient to ensure that the delay spread will exceed the equalizer memory length with a probability of less than 10−4–10−6. Index Terms — Delay spread, modedivision multiplexing, multimode fiber, random matrices.
Linear propagation effects in modedivision multiplexing systems
 J. Lightw. Technol
, 2014
"... Abstract—In this paper, we review linear propagation effects in a multimode fiber (MMF) and their impact on performance and complexity in longhaul modedivision multiplexing (MDM) systems. We highlight the many similarities to wireless multiinput multioutput (MIMO) systems. Modedependent loss a ..."
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Abstract—In this paper, we review linear propagation effects in a multimode fiber (MMF) and their impact on performance and complexity in longhaul modedivision multiplexing (MDM) systems. We highlight the many similarities to wireless multiinput multioutput (MIMO) systems. Modedependent loss and gain (MDL), analogous to multipath fading, can reduce average channel capacity and cause outage in narrowband systems. Modal dispersion (MD), analogous to multipath delay spread, affects the complexity of MIMO equalization, but has no fundamental effect on performance. Optimal MIMO transmission uses a basis of the Schmidt modes, which may be obtained by a singular value decomposition of the MIMO channel. In the special case of a unitary channel (no MDL), an optimal basis is the set of principal modes, which are eigenvectors of a group delay operator, and are free of signal distortion to first order. We present a concatenation rule for the accumulation of MD along a multisection link. We review mode coupling in MMF, including physical origins, models, and regimes of weak and strong coupling. Strong mode coupling is a key to overcoming challenges in MDM systems. Strong coupling reduces the group delay spread from MD, minimizing the complexity of MIMO signal processing. Likewise, it reduces the variations of loss and gain from MDL, maximizing channel capacity. In the strongcoupling regime, the statistics of MD and MDL depend only on the number of modes and the variance of accumulated group delay or loss/gain, and can be derived from the eigenvalue distributions of certain Gaussian random matrices. Index Terms—Channel capacity, frequency diversity, MIMO, modedivision multiplexing, multimode fiber.