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      Interfering Channel Estimation in Radar-Cellular Coexistence: How Much Information Do We Need?

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          Abstract

          In this paper, we focus on the coexistence between a MIMO radar and cellular base stations. We study the interfering channel estimation, where the radar is operated in the "search and track" mode, and the BS receives the interference from the radar. Unlike the conventional methods where the radar and the cellular systems fully cooperate with each other, in this work we consider that they are uncoordinated and the BS needs to acquire the interfering channel state information (ICSI) by exploiting the radar probing waveforms. For completeness, both the line-of-sight (LoS) and Non-LoS (NLoS) channels are considered in the coexistence scenario. By further assuming that the BS has limited a priori knowledge about the radar waveforms, we propose several hypothesis testing methods to identify the working mode of the radar, and then obtain the ICSI through a variety of channel estimation schemes. Based on the statistical theory, we analyze the theoretical performance of both the hypothesis testing and the channel estimation methods. Finally, simulation results verify the effectiveness of our theoretical analysis and demonstrate that the BS can effectively estimate the interfering channel even with limited information from the radar.

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          Spectral Coexistence of MIMO Radar and MIMO Cellular System

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            A projection based approach for radar and telecommunication systems coexistence

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              Optimum Design for Coexistence Between Matrix Completion Based MIMO Radars and a MIMO Communication System

              Recently proposed multiple input multiple output radars based on matrix completion (MIMO-MC) employ sparse sampling to reduce the amount of data that need to be forwarded to the radar fusion center, and as such enable savings in communication power and bandwidth. This paper proposes designs that optimize the sharing of spectrum between a MIMO-MC radar and a communication system, so that the latter interferes minimally with the former. First, the communication system transmit covariance matrix is designed to minimize the effective interference power (EIP) to the radar receiver, while maintaining certain average capacity and transmit power for the communication system. Two approaches are proposed, namely a noncooperative and a cooperative approach, with the latter being applicable when the radar sampling scheme is known at the communication system. Second, a joint design of the communication transmit covariance matrix and the MIMO-MC radar sampling scheme is proposed, which achieves even further EIP reduction.
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                Author and article information

                Journal
                11 July 2018
                Article
                1807.04000
                3819f8ba-f270-41bd-865a-42d7e8e13b81

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                History
                Custom metadata
                15 pages, 10 figures. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
                eess.SP cs.IT math.IT

                Numerical methods,Information systems & theory,Electrical engineering
                Numerical methods, Information systems & theory, Electrical engineering

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