How many users should inform the BS about their channel information?
ISWCS'09 Proceedings of the 6th international conference on Symposium on Wireless Communication Systems
Fast transfer of channel state information in wireless systems
IEEE Transactions on Signal Processing
Capacity of a mobile multiple-antenna communication link in Rayleigh flat fading
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
How much training is needed in multiple-antenna wireless links?
IEEE Transactions on Information Theory
Sum capacity of the vector Gaussian broadcast channel and uplink-downlink duality
IEEE Transactions on Information Theory
Sum capacity of Gaussian vector broadcast channels
IEEE Transactions on Information Theory
Multiple-antenna channel hardening and its implications for rate feedback and scheduling
IEEE Transactions on Information Theory
On the capacity of MIMO broadcast channels with partial side information
IEEE Transactions on Information Theory
The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel
IEEE Transactions on Information Theory
On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming
IEEE Journal on Selected Areas in Communications
Optimization of Training and Scheduling in the Non-Coherent SIMO Multiple Access Channel
IEEE Journal on Selected Areas in Communications
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In a system comprising of a multiple antenna enabled base station (BS) and multiple single antenna users, very high data rates can be obtained if BS transmits to multiple users simultaneously. This simultaneous transmission to multiple users over the same bandwidth is realizable only if BS knows the forward channels linking its transmit antennas to these users. We study a time-division duplexed (TDD) broadcast channel with initial assumption of channel information neither at the BS nor at the users' side. We propose two simple transmission strategies, one where users feedback independent of their channel realizations (earlier proposed in [1]) and the other where users feedback based upon their channel realizations. We derive a lower bound of the sum rate which reflects the rate loss compared to a system with perfect channel knowledge and the corresponding approximate sum rate expressions are developed for both schemes. These expressions capture the benefits of channel feedback, multi-user diversity and inter-user interference cancellation, and the cost of exchange of information required, and hence can be optimized for the sum rate maximization.