12,687 research outputs found
Blind Interference Alignment in General Heterogeneous Networks
Heterogeneous networks have a key role in the design of future mobile
communication networks, since the employment of small cells around a macrocell
enhances the network's efficiency and decreases complexity and power demand.
Moreover, research on Blind Interference Alignment (BIA) has shown that optimal
Degrees of Freedom (DoF) can be achieved in certain network architectures, with
no requirement of Channel State Information (CSI) at the transmitters. Our
contribution is a generalised model of BIA in a heterogeneous network with one
macrocell with K users and K femtocells each with one user, by using Kronecker
(Tensor) Product representation. We introduce a solution on how to vary
beamforming vectors under power constraints to maximize the sum rate of the
network and how optimal DoF can be achieved over K+1 time slots.Comment: 5 pages, 7 figures, accepted to IEEE PIMRC'1
Interference Management in Heterogeneous Networks with Blind Transmitters
Future multi-tier communication networks will require enhanced network
capacity and reduced overhead. In the absence of Channel State Information
(CSI) at the transmitters, Blind Interference Alignment (BIA) and Topological
Interference Management (TIM) can achieve optimal Degrees of Freedom (DoF),
minimising network's overhead. In addition, Non-Orthogonal Multiple Access
(NOMA) can increase the sum rate of the network, compared to orthogonal radio
access techniques currently adopted by 4G networks. Our contribution is two
interference management schemes, BIA and a hybrid TIM-NOMA scheme, employed in
heterogeneous networks by applying user-pairing and Kronecker Product
representation. BIA manages inter- and intra-cell interference by antenna
selection and appropriate message scheduling. The hybrid scheme manages
intra-cell interference based on NOMA and inter-cell interference based on TIM.
We show that both schemes achieve at least double the rate of TDMA. The hybrid
scheme always outperforms TDMA and BIA in terms of Degrees of Freedom (DoF).
Comparing the two proposed schemes, BIA achieves more DoF than TDMA under
certain restrictions, and provides better Bit-Error-Rate (BER) and sum rate
performance to macrocell users, whereas the hybrid scheme improves the
performance of femtocell users.Comment: 30 pages, 18 figure
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
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
A hybrid TIM-NOMA scheme for the SISO Broadcast Channel
Future mobile communication networks will require enhanced network efficiency
and reduced system overhead due to their user density and high data rate
demanding applications of the mobile devices. Research on Blind Interference
Alignment (BIA) and Topological Interference Management (TIM) has shown that
optimal Degrees of Freedom (DoF) can be achieved, in the absence of Channel
State Information (CSI) at the transmitters, reducing the network's overhead.
Moreover, the recently emerged Non-Orthogonal Multiple Access (NOMA) scheme
suggests a different multiple access approach, compared to the current
orthogonal methods employed in 4G networks, resulting in high capacity gains.
Our contribution is a hybrid TIM-NOMA scheme in Single-Input-Single-Output
(SISO) K-user cells, in which users are divided into T groups, and 1/T DoF is
achieved for each user. By superimposing users in the power domain, we
introduce a two-stage decoding process, managing 'inter-group' interference
based on the TIM principles, and 'intra-group' interference based on Successful
Interference Cancellation (SIC), as proposed by NOMA. We show that for high SNR
values the hybrid scheme can improve the sum rate by at least 100% when
compared to Time Division Multiple Access (TDMA).Comment: 6 pages, 6 figures, submitted to IEEE ICC'15 - IEEE SCAN Worksho
- …