• Publications
  • Influence
Random Matrix Theory and Wireless Communications
  • A. Tulino, S. Verdú
  • Computer Science, Mathematics
    Found. Trends Commun. Inf. Theory
  • 28 June 2004
A tutorial on random matrices is provided which provides an overview of the theory and brings together in one source the most significant results recently obtained.
Optimum power allocation for parallel Gaussian channels with arbitrary input distributions
This paper gives the power allocation policy that maximizes the mutual information over parallel channels with arbitrary input distributions, and admits a graphical interpretation, referred to as mercury/waterfilling, which generalizes the waterfilling solution and allows retaining some of its intuition.
Impact of antenna correlation on the capacity of multiantenna channels
This paper applies random matrix theory to obtain analytical characterizations of the capacity of correlated multiantenna channels that uncover compact capacity expansions that are valid for arbitrary numbers of antennas and that shed insight on how antenna correlation impacts the tradeoffs among power, bandwidth, and rate.
Multiple-antenna capacity in the low-power regime
Analysis of the impact of antenna correlation, Ricean factors, polarization diversity, and out-of-cell interference on multiple-antenna capacity in the regime of low signal-to-noise ratio yields practical design lessons for arbitrary number of antennas in the transmit and receive arrays.
Order-Optimal Rate of Caching and Coded Multicasting With Random Demands
The random demand setting is considered and a comprehensive characterization of the order-optimal rate for all regimes of the system parameters is provided, as well as an explicit placement and delivery scheme achieving order-Optimal rates.
Capacity of multiple-transmit multiple-receive antenna architectures
The capacity of wireless communication architectures equipped with multiple transmit and receive antennas and impaired by both noise and cochannel interference is studied. We find a closed-form
Achievable Sum Rate of MIMO MMSE Receivers: A General Analytic Framework
A new analytic framework is presented which exploits an interesting connection between the achievable sum rate with MMSE receivers and the ergodic mutual information achieved with optimal receivers, and leads to the discovery of key insights into the performance of MIMOMMSE receivers under practical channel conditions.
Finite-Length Analysis of Caching-Aided Coded Multicasting
This paper designs a new random placement and an efficient clique cover-based delivery scheme that achieves this lower bound approximately and provides tight concentration results that show that the average number of transmissions concentrates very well requiring only a polynomial number of packets in the rest of the system parameters.
Capacity-achieving input covariance for single-user multi-antenna channels
The capacity-achieving input covariance for multi-antenna channels known instantaneously at the receiver and in distribution at the transmitter is characterized and an iterative algorithm that exhibits remarkable properties is presented: universal applicability, robustness and rapid convergence.
Network MIMO With Linear Zero-Forcing Beamforming: Large System Analysis, Impact of Channel Estimation, and Reduced-Complexity Scheduling
A new simplified downlink scheduling scheme that preselects the users according to probabilities obtained from the large-system results, depending on the desired fairness criterion is proposed, performing close to the optimal (finite-dimensional) opportunistic user selection while requiring significantly less channel state feedback, since only a small fraction of preselected users must feed back their channel state information.