MIMO-OFDM JSAC Waveform Design Based on Phase Perturbation and Hybrid Optimization.

Area of Science:

• Electrical Engineering
• Signal Processing
• Electromagnetic Compatibility

Background:

• Modern combat platforms face increasingly complex electromagnetic environments.
• Joint Sensing and Communication (JSAC) technology is crucial for integrated sensing and communication functions.
• JSAC waveform design is key to achieving simultaneous sensing and communication with a single waveform.

Purpose of the Study:

• To propose a novel waveform design for Multi-Input Multi-Output (MIMO) JSAC systems.
• To enhance waveform performance by introducing phase perturbation into Binary Phase Shift Keying (BPSK) signals.
• To address the high-dimensional, non-convex optimization challenge in waveform design.

Main Methods:

• Leveraging Orthogonal Frequency Division Multiplexing (OFDM) for reduced signal interference via low cross-correlation.
• Utilizing Linear Frequency Modulation (LFM) as the carrier waveform to narrow autocorrelation main lobe width.
• Developing a hybrid optimization algorithm (QGPV) combining Quantum Genetic Algorithm (QGA), Quantum Particle Swarm Optimization (QPSO), and Variable Neighborhood Search (VNS).

Main Results:

• The proposed QGPV algorithm demonstrates superior performance compared to typical methods.
• Achieved significant suppression of Peak Sidelobe Level (PSL) to approximately -21 dB within five iterations.
• Validated the effectiveness of the proposed approach in improving waveform characteristics.

Conclusions:

• The novel waveform design and QGPV optimization algorithm are effective for MIMO JSAC systems.
• The approach offers improved waveform characteristics with an acceptable trade-off in communication performance.
• This research contributes to advancing JSAC technology for sophisticated electromagnetic environments.