Low Probability of Intercept-Based Optimal OFDM Waveform Design Strategy for an Integrated Radar and Communications System

Shi, Chenguang; Wang, Fei; Salous, Sana; Zhou, Jianjiang

Abstract

The integration of radar and communications systems can provide great advantages, such as enhanced efficiency, structure simplification, less occupied hardware resources, and interference mitigation, compared with traditional individual radar and communications applications. Extensive studies have presented achieving improved system performance, whereas the problem of low probability of intercept (LPI)-based waveform design for the integrated system is seldom discussed in the literature. In this paper, an LPI-based optimal orthogonal frequency multiplexing modulation (OFDM) waveform design strategy is developed for an integrated radar and communications system (IRCS). The dedicated transmitter in this system transmits integrated OFDM waveform for simultaneously target parameter estimation and downlink communications. The basis of the underlying strategy is to employ the optimization technique to design the integrated OFDM waveform of IRCS in order to minimize the total radiated power, while satisfying the specified requirements of target parameter estimation and data information rate. We analytically show that the resulting optimization problem is convex and can be solved by formulating the Karush–Kuhn–Tuckers optimality conditions. Numerical simulation results demonstrate that our proposed strategy can solve the waveform design problem in the IRCS with low complexity, and the LPI performance of the IRCS can efficiently be enhanced by utilizing the proposed integrated OFDM waveform design strategy.

Citation

Shi, C., Wang, F., Salous, S., & Zhou, J. (2018). Low Probability of Intercept-Based Optimal OFDM Waveform Design Strategy for an Integrated Radar and Communications System. IEEE Access, 6, 57689-57699. https://doi.org/10.1109/access.2018.2874007

• Journal Article Type: Article
• Acceptance Date: Oct 1, 2018
• Online Publication Date: Oct 5, 2018
• Publication Date: Oct 5, 2018
• Deposit Date: Nov 8, 2018
• Publicly Available Date: Nov 8, 2018
• Journal: IEEE Access
• Electronic ISSN: 2169-3536
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 6
• Pages: 57689-57699
• DOI: https://doi.org/10.1109/access.2018.2874007
• Public URL: https://durham-repository.worktribe.com/output/1309600