Capacity Limits of Multi-Antenna Multicasting Under Correlated Fading Channels

Physical layer multicasting in wireless networks has been proposed to efficiently send an identical message to multiple users simultaneously. In this paper, we consider multiple antenna multicasting where the transmitter is equipped with M
_t
antennas and data is transmitted to K single-antenna users. When the downlink channels are assumed to follow an uncorrelated Rayleigh distribution, the multicasting capacity scaling for the large K asymptote is known. On the other hand, the effect of channel spatial correlation on the capacity performance has not been well addressed. Therefore, we investigate the effect of correlation using the channel correlation information at the transmitter. Using extreme value theory, it is shown that signaling using uniformly allocated transmit powers on the spatial channel correlation matrix's eigenvectors with non-zero eigenvalues approaches the multicasting capacity for the large K asymptote. Compared to the performance of uncorrelated fading channels with a constraint on the trace of the spatial correlation matrix, it is shown that the channel correlation degrades the performance. Specifically, if the correlation matrix is full rank the asymptotic outage (average) capacity ratio, which is defined as the ratio of the outage (average) capacities of the correlated fading channel and the uncorrelated fading channel as K goes to infinity, is equivalent to the geometric mean of the eigenvalues of the transmit channel correlation matrix of the correlated channel. On the other hand, if the correlation matrix is not full rank, the capacity ratios become zero. To assess the value of knowledge of the channel correlation information at the transmitter, we compare the asymptotic performances with and without knowledge of the channel correlation information. Specifically, the asymptotic performance improvement due to this correlation knowledge becomes (M
_t
/M)
^1/M
for the large K asymptote, where M is the rank of the transmit channel correlation matrix. In addition, we discuss the issues of nonidentical transmit channel correlations among the users and correlation between users' channels.