106,294 research outputs found
Capacity Region of Vector Gaussian Interference Channels with Generally Strong Interference
An interference channel is said to have strong interference if for all input
distributions, the receivers can fully decode the interference. This definition
of strong interference applies to discrete memoryless, scalar and vector
Gaussian interference channels. However, there exist vector Gaussian
interference channels that may not satisfy the strong interference condition
but for which the capacity can still be achieved by jointly decoding the signal
and the interference. This kind of interference is called generally strong
interference. Sufficient conditions for a vector Gaussian interference channel
to have generally strong interference are derived. The sum-rate capacity and
the boundary points of the capacity region are also determined.Comment: 50 pages, 11 figures, submitted to IEEE trans. on Information Theor
A New Capacity Result for the Z-Gaussian Cognitive Interference Channel
This work proposes a novel outer bound for the Gaussian cognitive
interference channel in strong interference at the primary receiver based on
the capacity of a multi-antenna broadcast channel with degraded message set. It
then shows that for the Z-channel, i.e., when the secondary receiver
experiences no interference and the primary receiver experiences strong
interference, the proposed outer bound not only is the tightest among known
bounds but is actually achievable for sufficiently strong interference. The
latter is a novel capacity result that from numerical evaluations appears to be
generalizable to a larger (i.e., non-Z) class of Gaussian channels
The Approximate Capacity of the Many-to-One and One-to-Many Gaussian Interference Channels
Recently, Etkin, Tse, and Wang found the capacity region of the two-user
Gaussian interference channel to within one bit/s/Hz. A natural goal is to
apply this approach to the Gaussian interference channel with an arbitrary
number of users. We make progress towards this goal by finding the capacity
region of the many-to-one and one-to-many Gaussian interference channels to
within a constant number of bits. The result makes use of a deterministic model
to provide insight into the Gaussian channel. The deterministic model makes
explicit the dimension of signal scale. A central theme emerges: the use of
lattice codes for alignment of interfering signals on the signal scale.Comment: 45 pages, 16 figures. Submitted to IEEE Transactions on Information
Theor
Inner and Outer Bounds for the Gaussian Cognitive Interference Channel and New Capacity Results
The capacity of the Gaussian cognitive interference channel, a variation of
the classical two-user interference channel where one of the transmitters
(referred to as cognitive) has knowledge of both messages, is known in several
parameter regimes but remains unknown in general. In this paper we provide a
comparative overview of this channel model as we proceed through our
contributions: we present a new outer bound based on the idea of a broadcast
channel with degraded message sets, and another series of outer bounds obtained
by transforming the cognitive channel into channels with known capacity. We
specialize the largest known inner bound derived for the discrete memoryless
channel to the Gaussian noise channel and present several simplified schemes
evaluated for Gaussian inputs in closed form which we use to prove a number of
results. These include a new set of capacity results for the a) "primary
decodes cognitive" regime, a subset of the "strong interference" regime that is
not included in the "very strong interference" regime for which capacity was
known, and for the b) "S-channel" in which the primary transmitter does not
interfere with the cognitive receiver. Next, for a general Gaussian cognitive
interference channel, we determine the capacity to within one bit/s/Hz and to
within a factor two regardless of channel parameters, thus establishing rate
performance guarantees at high and low SNR, respectively. We also show how
different simplified transmission schemes achieve a constant gap between inner
and outer bound for specific channels. Finally, we numerically evaluate and
compare the various simplified achievable rate regions and outer bounds in
parameter regimes where capacity is unknown, leading to further insight on the
capacity region of the Gaussian cognitive interference channel.Comment: submitted to IEEE transaction of Information Theor
On Constant Gaps for the Two-way Gaussian Interference Channel
We introduce the two-way Gaussian interference channel in which there are
four nodes with four independent messages: two-messages to be transmitted over
a Gaussian interference channel in the direction, simultaneously
with two-messages to be transmitted over an interference channel (in-band,
full-duplex) in the direction. In such a two-way network, all
nodes are transmitters and receivers of messages, allowing them to adapt
current channel inputs to previously received channel outputs. We propose two
new outer bounds on the symmetric sum-rate for the two-way Gaussian
interference channel with complex channel gains: one under full adaptation (all
4 nodes are permitted to adapt inputs to previous outputs), and one under
partial adaptation (only 2 nodes are permitted to adapt, the other 2 are
restricted). We show that simple non-adaptive schemes such as the Han and
Kobayashi scheme, where inputs are functions of messages only and not past
outputs, utilized in each direction are sufficient to achieve within a constant
gap of these fully or partially adaptive outer bounds for all channel regimes.Comment: presented at 50th Annual Allerton Conference on Communication,
Control, and Computing, Monticello, IL, October 201
State of the cognitive interference channel: a new unified inner bound
The capacity region of the interference channel in which one transmitter
non-causally knows the message of the other, termed the cognitive interference
channel, has remained open since its inception in 2005. A number of subtly
differing achievable rate regions and outer bounds have been derived, some of
which are tight under specific conditions. In this work we present a new
unified inner bound for the discrete memoryless cognitive interference channel.
We show explicitly how it encompasses all known discrete memoryless achievable
rate regions as special cases. The presented achievable region was recently
used in deriving the capacity region of the general deterministic cognitive
interference channel, and thus also the linear high-SNR deterministic
approximation of the Gaussian cognitive interference channel. The high-SNR
deterministic approximation was then used to obtain the capacity of the
Gaussian cognitive interference channel to within 1.87 bits.Comment: Presented at the 2010 International Zurich Seminar on Communications
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