924 research outputs found
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
Opportunistic Interference Mitigation Achieves Optimal Degrees-of-Freedom in Wireless Multi-cell Uplink Networks
We introduce an opportunistic interference mitigation (OIM) protocol, where a
user scheduling strategy is utilized in -cell uplink networks with
time-invariant channel coefficients and base stations (BSs) having
antennas. Each BS opportunistically selects a set of users who generate the
minimum interference to the other BSs. Two OIM protocols are shown according to
the number of simultaneously transmitting users per cell: opportunistic
interference nulling (OIN) and opportunistic interference alignment (OIA).
Then, their performance is analyzed in terms of degrees-of-freedom (DoFs). As
our main result, it is shown that DoFs are achievable under the OIN
protocol with selected users per cell, if the total number of users in
a cell scales at least as . Similarly, it turns out that
the OIA scheme with () selected users achieves DoFs, if scales
faster than . These results indicate that there exists a
trade-off between the achievable DoFs and the minimum required . By deriving
the corresponding upper bound on the DoFs, it is shown that the OIN scheme is
DoF optimal. Finally, numerical evaluation, a two-step scheduling method, and
the extension to multi-carrier scenarios are shown.Comment: 18 pages, 3 figures, Submitted to IEEE Transactions on Communication
Opportunistic Interference Alignment in MIMO Interference Channels
We present two interference alignment techniques such that an opportunistic
point-to-point multiple input multiple output (MIMO) link can reuse, without
generating any additional interference, the same frequency band of a similar
pre-existing primary link. In this scenario, we exploit the fact that under
power constraints, although each radio maximizes independently its rate by
water-filling on their channel transfer matrix singular values, frequently, not
all of them are used. Therefore, by aligning the interference of the
opportunistic radio it is possible to transmit at a significant rate while
insuring zero-interference on the pre-existing link. We propose a linear
pre-coder for a perfect interference alignment and a power allocation scheme
which maximizes the individual data rate of the secondary link. Our numerical
results show that significant data rates are achieved even for a reduced number
of antennas.Comment: To appear in proc. IEEE PIMRC 2008 - Workshop in Emerging Network
Perspectives in Multiuser and Cooperative MIMO (NWMIMO). 5 pages and 4
figure
Improving Macrocell - Small Cell Coexistence through Adaptive Interference Draining
The deployment of underlay small base stations (SBSs) is expected to
significantly boost the spectrum efficiency and the coverage of next-generation
cellular networks. However, the coexistence of SBSs underlaid to an existing
macro-cellular network faces important challenges, notably in terms of spectrum
sharing and interference management. In this paper, we propose a novel
game-theoretic model that enables the SBSs to optimize their transmission rates
by making decisions on the resource occupation jointly in the frequency and
spatial domains. This procedure, known as interference draining, is performed
among cooperative SBSs and allows to drastically reduce the interference
experienced by both macro- and small cell users. At the macrocell side, we
consider a modified water-filling policy for the power allocation that allows
each macrocell user (MUE) to focus the transmissions on the degrees of freedom
over which the MUE experiences the best channel and interference conditions.
This approach not only represents an effective way to decrease the received
interference at the MUEs but also grants the SBSs tier additional transmission
opportunities and allows for a more agile interference management. Simulation
results show that the proposed approach yields significant gains at both
macrocell and small cell tiers, in terms of average achievable rate per user,
reaching up to 37%, relative to the non-cooperative case, for a network with
150 MUEs and 200 SBSs
On the Benefits of Edge Caching for MIMO Interference Alignment
In this contribution, we jointly investigate the benefits of caching and
interference alignment (IA) in multiple-input multiple-output (MIMO)
interference channel under limited backhaul capacity. In particular, total
average transmission rate is derived as a function of various system parameters
such as backhaul link capacity, cache size, number of active
transmitter-receiver pairs as well as the quantization bits for channel state
information (CSI). Given the fact that base stations are equipped both with
caching and IA capabilities and have knowledge of content popularity profile,
we then characterize an operational regime where the caching is beneficial.
Subsequently, we find the optimal number of transmitter-receiver pairs that
maximizes the total average transmission rate. When the popularity profile of
requested contents falls into the operational regime, it turns out that caching
substantially improves the throughput as it mitigates the backhaul usage and
allows IA methods to take benefit of such limited backhaul.Comment: 20 pages, 5 figures. A shorter version is to be presented at 16th
IEEE International Workshop on Signal Processing Advances in Wireless
Communications (SPAWC'2015), Stockholm, Swede
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