2,039 research outputs found
On the Optimality of Treating Interference as Noise: General Message Sets
In a K-user Gaussian interference channel, it has been shown that if for each
user the desired signal strength is no less than the sum of the strengths of
the strongest interference from this user and the strongest interference to
this user (all values in dB scale), then treating interference as noise (TIN)
is optimal from the perspective of generalized degrees-of-freedom (GDoF) and
achieves the entire channel capacity region to within a constant gap. In this
work, we show that for such TIN-optimal interference channels, even if the
message set is expanded to include an independent message from each transmitter
to each receiver, operating the new channel as the original interference
channel and treating interference as noise is still optimal for the sum
capacity up to a constant gap. Furthermore, we extend the result to the
sum-GDoF optimality of TIN in the general setting of X channels with arbitrary
numbers of transmitters and receivers
Generalized Degrees of Freedom of the Symmetric Cache-Aided MISO Broadcast Channel with Partial CSIT
We consider the cache-aided MISO broadcast channel (BC) in which a
multi-antenna transmitter serves single-antenna receivers, each equipped
with a cache memory. The transmitter has access to partial knowledge of the
channel state information. For a symmetric setting, in terms of channel
strength levels, partial channel knowledge levels and cache sizes, we
characterize the generalized degrees of freedom (GDoF) up to a constant
multiplicative factor. The achievability scheme exploits the interplay between
spatial multiplexing gains and coded-multicasting gain. On the other hand, a
cut-set-based argument in conjunction with a GDoF outer bound for a parallel
MISO BC under channel uncertainty are used for the converse. We further show
that the characterized order-optimal GDoF is also attained in a decentralized
setting, where no coordination is required for content placement in the caches.Comment: first revisio
On the Optimality of Treating Inter-Cell Interference as Noise in Uplink Cellular Networks
In this paper, we explore the information-theoretic optimality of treating
interference as noise (TIN) in cellular networks. We focus on uplink scenarios
modeled by the Gaussian interfering multiple access channel (IMAC), comprising
mutually interfering multiple access channels (MACs), each formed by an
arbitrary number of transmitters communicating independent messages to one
receiver. We define TIN for this setting as a scheme in which each MAC (or
cell) performs a power-controlled version of its capacity-achieving strategy,
with Gaussian codebooks and successive decoding, while treating interference
from all other MACs (i.e. inter-cell interference) as noise. We characterize
the generalized degrees-of-freedom (GDoF) region achieved through the proposed
TIN scheme, and then identify conditions under which this achievable region is
convex without the need for time-sharing. We then tighten these convexity
conditions and identify a regime in which the proposed TIN scheme achieves the
entire GDoF region of the IMAC and is within a constant gap of the entire
capacity region.Comment: Accepted for publication in IEEE Transactions on Information Theor
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