.png){kind=icon}
.png){kind=icon}
Return
Signal design for MIMO dual-function systems with permutation learning
.png){kind=icon}
PRE
AI
DOI：10.1007/s11432-022-3651-8.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper addresses the signal matrix synthesis in the multi-input-multi-output (MIMO) dual-function system aimed at obtaining the desired radar beampattern while embedding communication symbols into the permutation matrix of each pulse. To this end, transmit beampattern peak mainlobe to sidelobe level ratio (PMSR) is considered the figure of merit. Besides, the phases of the codebook induced by the designed weight vectors impinged on the directions of the communication receivers and eavesdroppers are restricted to be uniformly distributed and totally the same, respectively. To handle the resulting design problem, an iterative algorithm is devised to account for the coupled quadratic fractional programming objective function with multi-equality constraints, capitalizing on the alternating direction method of multipliers (ADMM) framework. As to the demodulation process for permutation learning, a novel algorithm based on the alternating direction penalty method (ADPM) framework is proposed to handle the mix-boolean optimization problem with the correlation between the communication dictionary and permutation of the received filtered data maximized. Finally, numerical results highlight the effectiveness of the conceived algorithms in comparison with the existing counterparts.
Keywords:
dual function radar and communication (DFRC) system
multi-input multi-output (MIMO) radar beampattern
alternating direction method of multipliers (ADMM)
permutation learning
mix-boolean optimization problem
alternating direction penalty method (ADPM)
Journal
IF:
7.6
Papers:
4.9K
Citations:
8.9K