Data Sharing Coordination and Blind Interference Alignment for Cellular Networks

International audienceWe consider coordination in a multi-user multiple input single output cellular system. In contrast with existing base station cooperation methods that rely on sharing CSI with or without user data to manage interference, we propose to share user data only. We consider a system where blind interference alignment (BIA) is applied to serve multiple users in each cell. We apply interference coordination through data sharing to mitigate other-cell interference at the cell-edge users. While BIA mitigates intra-cell interference in MU-MISO systems, it does not address the problem of inter-cell interference. We apply interference coordination through data sharing to mitigate inter-cell interference at the cell-edge users. We propose a new cooperative BIA scheme that takes into account the users whose data is being shared between adjacent base stations. We derive the achievable sum rate with interference mitigation and we compare it to achievable rates with the original BIA strategy. Numerical results show that the achievable sum rate of the cell-edge users with data sharing decreases with increasing number of served users in each cell and increasing number of antennas at the base stations

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

Cognitive Blind Interference Alignment for Macro-Femto Cellular Networks

The proceeding at: 2014 IEEE Global Communications Conference took place 8-12 December 2014 in Austin, TX, USA.A cognitive Blind Interference Alignment scheme is devised for use in macro-femto cellular networks. The proposed scheme does not require any channel state information at the transmitter or data sharing among the Macro Base Station and the Femto Access Points. It achieves transmission to femto cell users without affecting the rates of the Macro users. This is achieved by appropriately combining the supersymbols of the Macro Base Stations and the Femto Access Points. It is shown that in some scenarios the use of this scheme results to considerable rates for Femto users.This work has been partially funded by research projects COMONSENS (CSD2008-00010) and GRE3N (TEC2011-29006-C03-02). This research work was partly carried out at the ESAT Laboratory of KU Leuven in the frame of the Belgian Programme on Interuniversity Attractive Poles Programme initiated by the Belgian Science Policy Office: IUAP P7/23 ‘Belgian network on stochastic modeling analysis design and optimization of communication systems’ (BESTCOM) 2012-2017.Publicad

On the choice of blind interference alignment strategy for cellular systems with data sharing

The proceeding at: IEEE International Conference on Communications (ICC), tool place 2014, June, 10-14 in Sidney (Australia).A cooperative blind interference alignment (BIA) strategy is considered for the downlink of cellular systems. The aim is to reduce intercell interference in order to protect users, especially at the cell edge. The strategy consists of appropriately splitting the available bandwidth and is shown to be well-suited to scenarios where the number of cell-edge users is considerable. For a system comprising two cells each with a base station of Nt antennas, it is shown that, compared to a previous augmented code approach where transmission to all users occurs in the same frequency band, the proposed strategy leads to better rates over a wide range of signal-to-noise ratios when the number of cell-edge users in both cells exceeds 2Nt -1.This work has been partially funded by research projects COMONSENS (CSD2008-00010) and GRE3N (TEC2011-29006-C03-02). This research work was partly carried out at the ESAT Laboratory of KU Leuven in the frame of the Belgian Programme on Interuniversity Attractive Poles Programme initiated by the Belgian Science Policy Office: IUAP P7/23 ‘Belgian network on stochastic modeling analysis design and optimization of communication systems’(BESTCOM) 2012-2017.Publicad

Blind Interference Alignment for Cellular Networks

We propose a blind interference alignment scheme for partially connected cellular networks. The scheme cancels both intracell and intercell interference by relying on receivers with one reconfigurable antenna and by allowing users at the cell edge to be served by all the base stations in their proximity. An outer bound for the degrees of freedom is derived for general partially connected networks with single-antenna receivers when knowledge of the channel state information at the transmitter is not available. It is demonstrated that for symmetric scenarios, this outer bound is achieved by the proposed scheme. On the other hand, for asymmetric scenarios, the achievable degrees of freedom are not always equal to the outer bound. However, the penalty is typically small, and the proposed scheme outperforms other blind interference alignment schemes. Moreover, significant reduction of the supersymbol length is achieved compared with a standard blind interference alignment strategy designed for fully connected networks.This work has been partially funded by research projects COMONSENS (CSD2008-00010) and GRE3N (TEC2011-29006-C03-02). This research work was partly carried out at the ESAT Laboratory of KU Leuven in the frame of the Belgian Programme on Interuniversity Attractive Poles Programme initiated by the Belgian Science Policy Office: IUAP P7/23 ‘Belgian network on stochastic modeling analysis design and optimization of communication systems’ (BESTCOM) 2012–2017. The work of D. Toumpakaris was supported by the European Union (European Social Fund—ESF) and Greek national funds through the Operational Program Education and Lifelong Learning of the National Strategic Reference Framework through the Research Funding Program Thales—Investing in knowledge society through the European Social Fund. The work of Syed Jafar was supported in part by NSFgrants CCF-1319104 and CCF-1317351.Publicad