442 research outputs found
Elements of Cellular Blind Interference Alignment --- Aligned Frequency Reuse, Wireless Index Coding and Interference Diversity
We explore degrees of freedom (DoF) characterizations of partially connected
wireless networks, especially cellular networks, with no channel state
information at the transmitters. Specifically, we introduce three fundamental
elements --- aligned frequency reuse, wireless index coding and interference
diversity --- through a series of examples, focusing first on infinite regular
arrays, then on finite clusters with arbitrary connectivity and message sets,
and finally on heterogeneous settings with asymmetric multiple antenna
configurations. Aligned frequency reuse refers to the optimality of orthogonal
resource allocations in many cases, but according to unconventional reuse
patterns that are guided by interference alignment principles. Wireless index
coding highlights both the intimate connection between the index coding problem
and cellular blind interference alignment, as well as the added complexity
inherent to wireless settings. Interference diversity refers to the observation
that in a wireless network each receiver experiences a different set of
interferers, and depending on the actions of its own set of interferers, the
interference-free signal space at each receiver fluctuates differently from
other receivers, creating opportunities for robust applications of blind
interference alignment principles
Cognitive Wyner Networks with Clustered Decoding
We study an interference network where equally-numbered transmitters and
receivers lie on two parallel lines, each transmitter opposite its intended
receiver. We consider two short-range interference models: the "asymmetric
network," where the signal sent by each transmitter is interfered only by the
signal sent by its left neighbor (if present), and a "symmetric network," where
it is interfered by both its left and its right neighbors. Each transmitter is
cognizant of its own message, the messages of the transmitters to its
left, and the messages of the transmitters to its right. Each receiver
decodes its message based on the signals received at its own antenna, at the
receive antennas to its left, and the receive antennas to its
right. For such networks we provide upper and lower bounds on the multiplexing
gain, i.e., on the high-SNR asymptotic logarithmic growth of the sum-rate
capacity. In some cases our bounds meet, e.g., for the asymmetric network. Our
results exhibit an equivalence between the transmitter side-information
parameters and the receiver side-information parameters in the sense that increasing/decreasing or by a positive
integer has the same effect on the multiplexing gain as
increasing/decreasing or by . Moreover---even in
asymmetric networks---there is an equivalence between the left side-information
parameters and the right side-information parameters .Comment: Second revision submitted to IEEE Transactions on Information Theor
Approximate Sum-Capacity of K-user Cognitive Interference Channels with Cumulative Message Sharing
This paper considers the K user cognitive interference channel with one
primary and K-1 secondary/cognitive transmitters with a cumulative message
sharing structure, i.e cognitive transmitter knows non-causally
all messages of the users with index less than i. We propose a computable outer
bound valid for any memoryless channel. We first evaluate the sum-rate outer
bound for the high- SNR linear deterministic approximation of the Gaussian
noise channel. This is shown to be capacity for the 3-user channel with
arbitrary channel gains and the sum-capacity for the symmetric K-user channel.
Interestingly. for the K user channel having only the K th cognitive know all
the other messages is sufficient to achieve capacity i.e cognition at
transmitter 2 to K-1 is not needed. Next the sum capacity of the symmetric
Gaussian noise channel is characterized to within a constant additive and
multiplicative gap. The proposed achievable scheme for the additive gap is
based on Dirty paper coding and can be thought of as a MIMO-broadcast scheme
where only one encoding order is possible due to the message sharing structure.
As opposed to other multiuser interference channel models, a single scheme
suffices for both the weak and strong interference regimes. With this scheme
the generalized degrees of freedom (gDOF) is shown to be a function of K, in
contrast to the non cognitive case and the broadcast channel case.
Interestingly, it is show that as the number of users grows to infinity the
gDoF of the K-user cognitive interference channel with cumulative message
sharing tends to the gDoF of a broadcast channel with a K-antenna transmitter
and K single-antenna receivers. The analytical additive additive and
multiplicative gaps are a function of the number of users. Numerical
evaluations of inner and outer bounds show that the actual gap is less than the
analytical one.Comment: Journa
Interference Alignment for Cognitive Radio Communications and Networks: A Survey
Β© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignmentβs theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe
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