Optimum Co-Design of Spectrum Sharing Between MIMO Radar and MIMO Communication Systems: An Interference Alignment Approach
A major challenge in designing a spectral co-existence between radar and communication systems is how to simultaneously provide efficient utilization of the shared spectrum while maintaining a reliable performance for both systems. Due to its flexibility in using linear independent waveforms and sup...
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Published in | IEEE transactions on vehicular technology Vol. 67; no. 12; pp. 11667 - 11680 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.12.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
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Summary: | A major challenge in designing a spectral co-existence between radar and communication systems is how to simultaneously provide efficient utilization of the shared spectrum while maintaining a reliable performance for both systems. Due to its flexibility in using linear independent waveforms and superiority in terms of target detection and estimation, the collocated multiple-input-multiple-output (MIMO) radars provide a paramount capability in realizing spectrum sharing with communication systems. In this paper, we consider the use of joint transmit and receive beamformers for both the MIMO radar and MIMO communication systems. Specifically, we design a two-tier alternating optimization spectrum sharing framework that is based on interference alignment (IA) approach. The effectiveness of spectrum sharing between radar and communication systems is guaranteed by mitigating the mutual interference signals in the shared spectral band. Subsequently, motivated by the excellent performance provided by IA in different wireless network scenarios, we propose a spectrum sharing framework that consists of a main iterative algorithm with two subalgorithms included within its operation. The first subalgorithm is used to maximize the signal-to-interference-plus-noise ratio of the radar system, whereas the second one is utilized to maximize the average sum-rate of the communication system. The main iterative algorithm is proposed to jointly optimize the transmit and receive beamforming filters of both systems by performing alternating optimization between the two subalgorithms. The convergences of the proposed algorithm and its subalgorithms are numerically verified. Simulation results are provided to confirm the superiority of the proposed framework for both systems. |
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ISSN: | 0018-9545 1939-9359 |
DOI: | 10.1109/TVT.2018.2872917 |