Joint Design of Overlaid Communication Systems and Pulsed Radars

Zheng, Li; Lops, Marco; Wang, Xiaodong; Grossi, Emanuele

doi:10.1109/tsp.2017.2755603

Cited by 158 publications

(92 citation statements)

References 29 publications

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“…Algorithm 3 Sequential Optimization Algorithm for the Weighted-Sum Formulation Input: Channel SNRs γ r and γ c , IO waveform that is used to construct matrix H in (13), total radar power P r , and tolerance .…”

Section: Simplified Solution With No Timing Uncertaintymentioning

confidence: 99%

Joint Waveform and Receiver Design for Co-Channel Hybrid Active-Passive Sensing With Timing Uncertainty

Wang

2020

IEEE Trans. Signal Process.

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We consider a hybrid active-passive radar system that employs a wireless source as a passive illuminator of opportunity (IO) and a co-channel active radar transmitter operating in the same frequency band to seek spectral efficiency. The hybrid system can take advantage of the strengths of passive radar (e.g., energy efficiency, bi-/multi-static configuration, and spatial diversity) as well as those of active radar (dedicated transmitter, flexible transmit beam steering, waveform optimized for sensing, etc.). To mitigate the mutual interference and location-induced timing uncertainty between the radar and communication signals, we propose two designs for the joint optimization of the radar waveform and receive filters. The first is a max-min (MM) criterion that optimizes a worst-case performance metric over a timing uncertainty interval, and the other a weighted-sum (WS) criterion that forms a weighted sum of the performance metric at each delay within the delay uncertainty interval. Both design criteria result in nonconvex constrained optimization problems that are solved by sequential convex programming methods. When timing uncertainty vanishes, the two designs become identical and admit a simpler solution. Numerical results are presented to demonstrate the performance of the proposed hybrid schemes in comparison with conventional active-only and passive-only radar systems.

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Section: Simplified Solution With No Timing Uncertaintymentioning

confidence: 99%

Joint Waveform and Receiver Design for Co-Channel Hybrid Active-Passive Sensing With Timing Uncertainty

Wang

2020

IEEE Trans. Signal Process.

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“…Equation (11) highlights that data demodulation and interference mitigation are coupled, in the sense that they should be accomplished jointly and that poor performance in estimating either one has detrimental effects on the estimate of the…”

Section: Proposed Algorithmsmentioning

confidence: 99%

“…Motivated by the cooperative methods in cognitive radio networks, later works [13]- [15] exploit some prior knowledge to jointly design the radar waveform and communication code-book by minimizing a measure of the mutual interference under certain constraints. Le Many existing approaches assume that the radar and communication systems are aware of the existence of each other, and share information: for example, ad hoc design of radar waveforms or beam-formers is proposed in [5]- [7], [9], [10] to reduce the mutual interference, while [11]- [15] rely on making channel information available to the communication and radar through the transmission of pilot training. Otherwise stated, these approaches rely on a centralized architecture, namely on a strict coordination between the active players in order to allow co-existence.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Interference Removal for Uncoordinated Radar/Communication Coexistence

Zheng

Lops

Wang

2018

IEEE J. Sel. Top. Signal Process.

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124

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Most existing approaches to co-existing communication/radar systems assume that the radar and communication systems are coordinated, i.e., they share information, such as relative position, transmitted waveforms and channel state. In this paper, we consider an un-coordinated scenario where a communication receiver is to operate in the presence of a number of radars, of which only a sub-set may be active, which poses the problem of estimating the active waveforms and the relevant parameters thereof, so as to cancel them prior to demodulation. Two algorithms are proposed for such a joint waveform estimation/data demodulation problem, both exploiting sparsity of a proper representation of the interference and of the vector containing the errors of the data block, so as to implement an iterative joint interference removal/data demodulation process. The former algorithm is based on classical on-grid compressed sensing (CS), while the latter forces an atomic norm (AN) constraint: in both cases the radar parameters and the communication demodulation errors can be estimated by solving a convex problem. We also propose a way to improve the efficiency of the AN-based algorithm. The performance of these algorithms are demonstrated through extensive simulations, taking into account a variety of conditions concerning both the interferers and the respective channel states.

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“…2, during one PRI, the radar only transmits for a portion of the time, typically below 10%, and employs the remaining 90% for receiving, during which the radar remains silent. Such a ratio is called duty cycle [14]. By exploiting this property, the BS is able to blindly estimate the beginning and the end of a radar pulse by some simple methods, such as energy detection.…”

Section: Bs Signal Reception Modelmentioning

confidence: 99%

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

Liu

García‐Rodríguez

Masouros

et al. 2019

IEEE Trans. Wireless Commun.

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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-ofsight (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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Joint Design of Overlaid Communication Systems and Pulsed Radars

Cited by 158 publications

References 29 publications

Joint Waveform and Receiver Design for Co-Channel Hybrid Active-Passive Sensing With Timing Uncertainty

Joint Waveform and Receiver Design for Co-Channel Hybrid Active-Passive Sensing With Timing Uncertainty

Adaptive Interference Removal for Uncoordinated Radar/Communication Coexistence

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

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