Computer Science – Information Theory
Scientific paper
2011-08-18
Computer Science
Information Theory
Scientific paper
In this work, we discuss the joint precoding across K transmitters (TXs), sharing the knowledge of the data symbols to be transmitted toward K single-antenna receivers (RXs). We introduce a distributed channel state information (DCSI) configuration where each TX has its own local estimate of the overall multiuser MIMO matrix and must make a precoding decision solely based on the available local CSI. We refer to this channel as the DCSI-MIMO channel and the precoding problem as distributed precoding. For the DCSI model with a limited number of bits for quantizing the CSI, we derive the multiplexing gain (MG) achieved by conventional precoding methods as a function of the scaling in the logarithm of the Signal-to-Noise Ratio (SNR) of the number of quantizing bits for each channel at each TX. We show that conventional zero-forcing, although being MG optimal in the classical MIMO channel, is severely limited in the DCSI case. Particularly, we show the seemingly pessimistic result that the MG is limited by the worst CSI across all antenna pairs. Following this, we provide precoding schemes improving on the achieved MG, and for certain cases, we derive the optimal MG achieving scheme. We advocate the use of hierarchical CSI, for which we show that considerable gains are possible and provide a corresponding precoding method. Finally, we use the previous analysis to derive the optimal allocation of the feedback bits to the various TXs under a total feedback constraint.
Gesbert David
Kerret Paul de
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