2,376 research outputs found

    Interference Alignment for Cognitive Radio Communications and Networks: A Survey

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    © 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

    Cognitive Orthogonal Precoder for Two-tiered Networks Deployment

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    In this work, the problem of cross-tier interference in a two-tiered (macro-cell and cognitive small-cells) network, under the complete spectrum sharing paradigm, is studied. A new orthogonal precoder transmit scheme for the small base stations, called multi-user Vandermonde-subspace frequency division multiplexing (MU-VFDM), is proposed. MU-VFDM allows several cognitive small base stations to coexist with legacy macro-cell receivers, by nulling the small- to macro-cell cross-tier interference, without any cooperation between the two tiers. This cleverly designed cascaded precoder structure, not only cancels the cross-tier interference, but avoids the co-tier interference for the small-cell network. The achievable sum-rate of the small-cell network, satisfying the interference cancelation requirements, is evaluated for perfect and imperfect channel state information at the transmitter. Simulation results for the cascaded MU-VFDM precoder show a comparable performance to that of state-of-the-art dirty paper coding technique, for the case of a dense cellular layout. Finally, a comparison between MU-VFDM and a standard complete spectrum separation strategy is proposed. Promising gains in terms of achievable sum-rate are shown for the two-tiered network w.r.t. the traditional bandwidth management approach.Comment: 11 pages, 9 figures, accepted and to appear in IEEE Journal on Selected Areas in Communications: Cognitive Radio Series, 2013. Copyright transferred to IEE

    A General MIMO Framework for NOMA Downlink and Uplink Transmission Based on Signal Alignment

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    The application of multiple-input multiple-output (MIMO) techniques to non-orthogonal multiple access (NOMA) systems is important to enhance the performance gains of NOMA. In this paper, a novel MIMO-NOMA framework for downlink and uplink transmission is proposed by applying the concept of signal alignment. By using stochastic geometry, closed-form analytical results are developed to facilitate the performance evaluation of the proposed framework for randomly deployed users and interferers. The impact of different power allocation strategies, such as fixed power allocation and cognitive radio inspired power allocation, on the performance of MIMO-NOMA is also investigated. Computer simulation results are provided to demonstrate the performance of the proposed framework and the accuracy of the developed analytical results

    Improving Macrocell - Small Cell Coexistence through Adaptive Interference Draining

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    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
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