Jinlong Wu;Lixin Li;Wensheng Lin;Junli Liang;Zhu Han
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引用次数: 0
Abstract
With the development of integrated sensing and communication (ISAC) systems, waveform design is currently attracting extensive attention. At the same time, subcarrier superposition can lead to the high peak-to-average power ratio (PAPR) problem in orthogonal frequency-division multiplexing (OFDM). Therefore, in this article, we investigate the low PAPR waveform design for OFDM-based ISAC systems. A weighted optimization problem with the constraint of zero integrated sidelobe level (ISL) is formulated with the aim of flexibly balancing between PAPR and communication performance and an alternating direction method of multipliers (ADMMs)-based algorithm is proposed to address this issue. Moreover, the nonlinear power amplifier is also considered to demonstrate the impact of PAPR on ISAC systems. Simulation results demonstrate that the proposed algorithm can effectively reduce the PAPR and achieve a performance trade-off between PAPR and communication performance.
期刊介绍:
The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following:
-Sensor Phenomenology, Modelling, and Evaluation
-Sensor Materials, Processing, and Fabrication
-Chemical and Gas Sensors
-Microfluidics and Biosensors
-Optical Sensors
-Physical Sensors: Temperature, Mechanical, Magnetic, and others
-Acoustic and Ultrasonic Sensors
-Sensor Packaging
-Sensor Networks
-Sensor Applications
-Sensor Systems: Signals, Processing, and Interfaces
-Actuators and Sensor Power Systems
-Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting
-Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data)
-Sensors in Industrial Practice