3,301 research outputs found
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
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
Joint Channel Assignment and Opportunistic Routing for Maximizing Throughput in Cognitive Radio Networks
In this paper, we consider the joint opportunistic routing and channel
assignment problem in multi-channel multi-radio (MCMR) cognitive radio networks
(CRNs) for improving aggregate throughput of the secondary users. We first
present the nonlinear programming optimization model for this joint problem,
taking into account the feature of CRNs-channel uncertainty. Then considering
the queue state of a node, we propose a new scheme to select proper forwarding
candidates for opportunistic routing. Furthermore, a new algorithm for
calculating the forwarding probability of any packet at a node is proposed,
which is used to calculate how many packets a forwarder should send, so that
the duplicate transmission can be reduced compared with MAC-independent
opportunistic routing & encoding (MORE) [11]. Our numerical results show that
the proposed scheme performs significantly better that traditional routing and
opportunistic routing in which channel assignment strategy is employed.Comment: 5 pages, 4 figures, to appear in Proc. of IEEE GlobeCom 201
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