Wednesday 30 July 2025
Researchers have made a breakthrough in designing sensing waveforms for multiple base stations (MBS) systems, which could significantly improve radar detection performance.
The MBS system is a promising technology that allows multiple base stations to work together to provide better sensing and communication capabilities. However, the high autocorrelation and cross-correlation of the OFDM (orthogonal frequency division multiplexing) waveforms used in this system pose a challenge for radar detection.
A team of scientists has tackled this problem by formulating an integrated sidelobe level (ISL) minimization problem that takes into account the mainlobe level, peak-to-average power ratio (PAPR), and spectrum allocation constraints. This problem is non-convex, meaning it cannot be solved using traditional optimization methods.
To overcome this challenge, the researchers developed an alternating optimization algorithm that solves the problem iteratively. The algorithm updates the sensing waveform and receive filter in an alternating manner, with each update being based on the previous iteration’s results.
The team tested their algorithm using simulations and found that it can significantly reduce the sidelobe level of the OFDM waveforms. This improvement is particularly notable for weak targets in dense urban environments, where high sidelobe levels can degrade radar detection performance.
The researchers also explored how different numbers of unavailable subcarriers affect the ISL performance. They found that as the number of available subcarriers increases, the ISL level decreases, indicating that more subcarriers provide better sensing capabilities.
This breakthrough has significant implications for the development of MBS systems and their applications in areas such as autonomous driving, surveillance, and remote sensing. The ability to design sensing waveforms with improved sidelobe levels could lead to more accurate radar detection and better overall system performance.
In addition to its potential impact on MBS systems, this research also highlights the importance of waveform design in radar systems. By optimizing waveforms for specific applications, researchers can improve the overall performance and capabilities of these systems.
The development of this algorithm is a significant step forward in the design of sensing waveforms for MBS systems, and it has the potential to revolutionize the way we approach radar detection and sensing.
Cite this article: “Optimizing Sensing Waveforms for Improved Radar Detection Performance in Multiple Base Stations Systems”, The Science Archive, 2025.
Multiple Base Stations, Radar Detection, Waveform Design, Orthogonal Frequency Division Multiplexing, Sidelobe Level, Peak-To-Average Power Ratio, Spectrum Allocation, Alternating Optimization Algorithm, Simulation Results, Autocorrelation And Cross-C
