Probability and Random Processes For EE's (3rd Edition)
Probability and Random Processes For EE's (3rd Edition)
On the achievable throughput of a multiantenna Gaussian broadcast channel
IEEE Transactions on Information Theory
Sum capacity of the vector Gaussian broadcast channel and uplink-downlink duality
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
MIMO Broadcast Channels With Finite-Rate Feedback
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
What is the value of limited feedback for MIMO channels?
IEEE Communications Magazine
On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming
IEEE Journal on Selected Areas in Communications
Multi-Antenna Downlink Channels with Limited Feedback and User Selection
IEEE Journal on Selected Areas in Communications
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We develop a realistic model for multiple-input multiple-output (MIMO) broadcast channels, where each randomly located user's average SNR depends on its distance from the transmitter. With perfect channel state information at the transmitter (CSIT), the average sum capacity is proven to scale for many users like αM/2 log K instead of M log log K, where α, M, and K denote the path loss exponent, the number of transmit antennas, and the number of users in a cell. With only partial CSIT, the sum capacity at high SNR eventually saturates due to interference, and the saturation value scales for large B like MB/M-1 where B denotes the quantization resolution for channel feedback.