Opportunistic beamforming using dumb antennas
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
On the achievable throughput of a multiantenna Gaussian broadcast channel
IEEE Transactions on Information Theory
On the capacity of MIMO broadcast channels with partial side information
IEEE Transactions on Information Theory
Dirty-paper coding versus TDMA for MIMO Broadcast channels
IEEE Transactions on Information Theory
The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel
IEEE Transactions on Information Theory
An introduction to the multi-user MIMO downlink
IEEE Communications Magazine
Capacity limits of MIMO channels
IEEE Journal on Selected Areas in Communications
On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming
IEEE Journal on Selected Areas in Communications
Fast communication: Scaling of the minimum of iid random variables
Signal Processing
On the distribution of indefinite quadratic forms in Gaussian random variables
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 3
On the trade-off between feedback and capacity in measured MU-MIMO channels
IEEE Transactions on Wireless Communications
Exact performance analysis of the ε-NLMS algorithm for colored circular Gaussian inputs
IEEE Transactions on Signal Processing
Opportunistic random beamforming with optimal precoding for spatially correlated channels
IEEE Communications Letters
EURASIP Journal on Wireless Communications and Networking - Special issue on interference management in wireless communication systems: theory and applications
Cognitive Radio MIMO Gaussian Broadcast Channels with the Power Constraint
Wireless Personal Communications: An International Journal
Hi-index | 0.01 |
This paper considers the effect of spatial correlation between transmit antennas on the sum-rate capacity of the MIMO Gaussian broadcast channel (i.e., downlink of a cellular system). Specifically, for a system with a large number of users n, we analyze the scaling laws of the sum-rate for the dirty paper coding and for different types of beamforming transmission schemes. When the channel is i.i.d., it has been shown that for large n, the sum rate is equal to M log log n + M log P/M + o(1) where M is the number of transmit antennas, P is the average signal to noise ratio, and o(1) refers to terms that go to zero as n → ∞. When the channel exhibits some spatial correlation with a covariance matrix R (non-singular with tr(R) = M), we prove that the sum rate of dirty paper coding is M log log n + M log P/M + log det(R) + o(1). We further show that the sum-rate of various beamforming schemes achieves M log log n + M log P/M + M log c + o(1) where c ≤ 1 depends on the type of beamforming. We can in fact compute c for random beamforming proposed in [1] and more generally, for random beamforming with precoding in which beams are pre-multiplied by a fixed matrix. Simulation results are presented at the end of the paper.