An FPGA-based implementation of a multifunction environment sensing device for shared access with rotating radars
Khan, Zaheer; Lehtomäki, Janne J.; Hossain, Ekram; Latva-Aho, Matti; Marshall, Alan (2018-05-16)
Z. Khan, J. J. Lehtomäki, E. Hossain, M. Latva-Aho and A. Marshall, "An FPGA-Based Implementation of a Multifunction Environment Sensing Device for Shared Access With Rotating Radars," in IEEE Transactions on Instrumentation and Measurement, vol. 67, no. 11, pp. 2561-2578, Nov. 2018. doi: 10.1109/TIM.2018.2828718
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https://urn.fi/URN:NBN:fi-fe2018101037976
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Abstract
To protect radar receivers and to facilitate shared access in radar bands, regulatory bodies have recommended the use of spectrum monitoring devices called environmental sensing capability (ESC). High-speed and low-cost ESC devices are required to process in real time the large amount of data (in-phase and quadrature samples) for the detection of radar signals and to differentiate them from secondary users (SUs) signals. In this paper, we present a field-programmable gate array (FPGA)-based design and implementation of a multifunction ESC device that can detect radar pulses and can also differentiate them from SU signals in microsecond time scales. The proposed ESC device performs the following tasks in parallel: 1) it detects and differentiates between radar and SU signals; 2) it measures received signal strength from SUs for radar protection; and 3) it also measures SUs’ airtime utilization (ATU) in a channel, which can be used to perform load balancing (based on ATU) of SUs on different channels for efficient access. Detection of signals requires threshold setting. We present a novel minimum-based threshold setting technique, which is suitable for real-time operation of energy detectors. We implement a prototype of the proposed ESC device design on a Wireless Open-Access Research Platform node, which is equipped with a Xilinx FPGA. We evaluate the performance of the implemented device and show that with very high probability (close to 100%), it detects and differentiates between radar and SU signals. Moreover, it also accurately measures the ATU of SUs.
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