1,550 research outputs found
On the Interference Alignment Designs for Secure Multiuser MIMO Systems
In this paper, we propose two secure multiuser multiple-input multiple-output
transmission approaches based on interference alignment (IA) in the presence of
an eavesdropper. To deal with the information leakage to the eavesdropper as
well as the interference signals from undesired transmitters (Txs) at desired
receivers (Rxs), our approaches aim to design the transmit precoding and
receive subspace matrices to minimize both the total inter-main-link
interference and the wiretapped signals (WSs). The first proposed IA scheme
focuses on aligning the WSs into proper subspaces while the second one imposes
a new structure on the precoding matrices to force the WSs to zero. When the
channel state information is perfectly known at all Txs, in each proposed IA
scheme, the precoding matrices at Txs and the receive subspaces at Rxs or the
eavesdropper are alternatively selected to minimize the cost function of an
convex optimization problem for every iteration. We provide the feasible
conditions and the proofs of convergence for both IA approaches. The simulation
results indicate that our two IA approaches outperform the conventional IA
algorithm in terms of average secrecy sum rate.Comment: Updated version, updated author list, accepted to be appear in IEICE
Transaction
Generalized Signal Alignment For MIMO Two-Way X Relay Channels
We study the degrees of freedom (DoF) of MIMO two-way X relay channels.
Previous work studied the case , where and denote the number of
antennas at the relay and each source, respectively, and showed that the
maximum DoF of is achievable when by
applying signal alignment (SA) for network coding and interference cancelation.
This work considers the case where the performance is limited by the
number of antennas at each source node and conventional SA is not feasible. We
propose a \textit{generalized signal alignment} (GSA) based transmission
scheme. The key is to let the signals to be exchanged between every source node
align in a transformed subspace, rather than the direct subspace, at the relay
so as to form network-coded signals. This is realized by jointly designing the
precoding matrices at all source nodes and the processing matrix at the relay.
Moreover, the aligned subspaces are orthogonal to each other. By applying the
GSA, we show that the DoF upper bound is achievable when ( is even) or ( is odd). Numerical results also demonstrate
that our proposed transmission scheme is feasible and effective.Comment: 6 pages, 6 figures, to appear in IEEE ICC 201
Interference Alignment for Cognitive Radio Communications and Networks: A Survey
© 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 alignment’s 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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