8 research outputs found
Feedback-Topology Designs for Interference Alignment in MIMO Interference Channels
Interference alignment (IA) is a joint-transmission technique that achieves
the capacity of the interference channel for high signal-to-noise ratios
(SNRs). Most prior work on IA is based on the impractical assumption that
perfect and global channel-state information(CSI) is available at all
transmitters. To implement IA, each receiver has to feed back CSI to all
interferers, resulting in overwhelming feedback overhead. In particular, the
sum feedback rate of each receiver scales quadratically with the number of
users even if the quantized CSI is fed back. To substantially suppress feedback
overhead, this paper focuses on designing efficient arrangements of feedback
links, called feedback topologies, under the IA constraint. For the
multiple-input-multiple-output (MIMO) K-user interference channel, we propose
the feedback topology that supports sequential CSI exchange (feedback and
feedforward) between transmitters and receivers so as to achieve IA
progressively. This feedback topology is shown to reduce the network feedback
overhead from a cubic function of K to a linear one. To reduce the delay in the
sequential CSI exchange, an alternative feedback topology is designed for
supporting two-hop feedback via a control station, which also achieves the
linear feedback scaling with K. Next, given the proposed feedback topologies,
the feedback-bit allocation algorithm is designed for allocating feedback bits
by each receiver to different feedback links so as to regulate the residual
interference caused by the finite-rate feedback. Simulation results demonstrate
that the proposed bit allocation leads to significant throughput gains
especially in strong interference environments.Comment: 28 pages; 11 figures ; submitted to IEEE Trans. on Signal Processin