Computer Science – Information Theory
Scientific paper
2011-10-31
Computer Science
Information Theory
Scientific paper
In this work, we consider the joint precoding across K transmitters (TXs), sharing the knowledge of the user's data symbols to be transmitted towards K single-antenna receivers (RXs). We consider a distributed channel state information (DCSI) configuration where each TX has its own local estimate of the overall multiuser MIMO channel. The focus of this work is on the optimization of the allocation of the CSI feedback subject to a constraint on the total sharing through the backhaul network. Building upon the Wyner model, we derive a new approach to allocate the CSI feedback while making efficient use of the pathloss structure to reduce the amount of feedback necessary. We show that the proposed CSI allocation achieves good performance with only a number of CSI bits per TX which does not scale with the number of cooperating TXs, thus making the joint transmission from a large number of TXs more practical than previously thought. Indeed, the proposed CSI allocation reduces the cooperation to a local scale, which allows also for a reduced allocation of the user's data symbols. We further show that the approach can be extended to a more general class of channel: the exponentially decaying channels, which model accuratly the cooperation of TXs located on a one dimensional space. Finally, we verify by simulations that the proposed CSI allocation leads to very little performance losses.
Gesbert David
Kerret Paul de
No associations
LandOfFree
Towards Optimal CSI Allocation in Multicell MIMO Channels does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Towards Optimal CSI Allocation in Multicell MIMO Channels, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Towards Optimal CSI Allocation in Multicell MIMO Channels will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-147652