Blind Interference Alignment for MapReduce: Exploiting Side-information with Reconfigurable Antennas
arxiv(2024)
摘要
In order to explore how blind interference alignment (BIA) schemes may take
advantage of side-information in computation tasks, we study the degrees of
freedom (DoF) of a K user wireless network setting that arises in full-duplex
wireless MapReduce applications. In this setting the receivers are assumed to
have reconfigurable antennas and channel knowledge, while the transmitters have
neither, i.e., the transmitters lack channel knowledge and are only equipped
with conventional antennas. The central ingredient of the problem formulation
is the message structure arising out of MapReduce, whereby each transmitter has
a subset of messages that need to be delivered to various receivers, and each
receiver has a subset of messages available to it in advance as
side-information. The challenge resides in both achievability and converse
arguments. Unlike conventional BIA where alignments occur only within the
symbols of the same message (intra-message) the new achievable scheme also
requires inter-message alignments, as well as an outer MDS (maximum distance
separable) code structure. The scheme emerges from two essential ideas: 1)
understanding the DoF of a K user vector broadcast channel with groupcast
messages, and 2) a mapping of messages from the broadcast setting to the
MapReduce setting that makes use of inter-message alignment. On the converse
side, whereas prior BIA converse bounds relied only on a compound channel
argument, in the new setting our converse bounds also require a statistical
equivalence assumption.
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