133 research outputs found
Interference Alignment via Message-Passing
We introduce an iterative solution to the problem of interference alignment
(IA) over MIMO channels based on a message-passing formulation. We propose a
parameterization of the messages that enables the computation of IA precoders
by a min-sum algorithm over continuous variable spaces -- under this
parameterization, suitable approximations of the messages can be computed in
closed-form. We show that the iterative leakage minimization algorithm of
Cadambe et al. is a special case of our message-passing algorithm, obtained for
a particular schedule. Finally, we show that the proposed algorithm compares
favorably to iterative leakage minimization in terms of convergence speed, and
discuss a distributed implementation.Comment: Submitted to the IEEE International Conference on Communications
(ICC) 201
Degrees of Freedom of Certain Interference Alignment Schemes with Distributed CSIT
In this work, we consider the use of interference alignment (IA) in a MIMO
interference channel (IC) under the assumption that each transmitter (TX) has
access to channel state information (CSI) that generally differs from that
available to other TXs. This setting is referred to as distributed CSIT. In a
setting where CSI accuracy is controlled by a set of power exponents, we show
that in the static 3-user MIMO square IC, the number of degrees-of-freedom
(DoF) that can be achieved with distributed CSIT is at least equal to the DoF
achieved with the worst accuracy taken across the TXs and across the
interfering links. We conjecture further that this represents exactly the DoF
achieved. This result is in strong contrast with the centralized CSIT
configuration usually studied (where all the TXs share the same, possibly
imperfect, channel estimate) for which it was shown that the DoF achieved at
receiver (RX) i is solely limited by the quality of its own feedback. This
shows the critical impact of CSI discrepancies between the TXs, and highlights
the price paid by distributed precoding.Comment: This is an extended version of a conference submission which will be
presented at the IEEE conference SPAWC, Darmstadt, June 201
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