TY - JOUR
T1 - Data-Driven Measurement of Receiver Sensitivity in Wireless Communication Systems
AU - Ma, Yuan
AU - Wang, Xu
AU - Quan, Zhi
AU - Poor, H. Vincent
N1 - Funding Information:
Manuscript received June 18, 2018; revised October 6, 2018 and December 16, 2018; accepted December 27, 2018. Date of publication January 9, 2019; date of current version May 15, 2019. This work was partially supported by National Natural Science Foundation of China (NSFC) under grant 61622108, and by the Shenzhen Science and Technology Program under grant JCYJ20170413151115990. The work of H. V. Poor was supported in part by the U.S. National Science Foundation under Grants CCF-1513915 and CNS-1702808. The associate editor coordinating the review of this paper and approving it for publication was V. Raghavan. (Corresponding author: Zhi Quan.) Y. Ma, X. Wang, and Z. Quan are with the College of Information Engineering, Shenzhen University, Shenzhen 518060, China (e-mail: mayuan@szu.edu.cn; xuwang@szu.edu.cn; zquan@szu.edu.cn).
Publisher Copyright:
© 1972-2012 IEEE.
PY - 2019/5
Y1 - 2019/5
N2 - Receiver sensitivity is one of the most important parameters in determining the overall performance of a radio frequency communication system. The traditional receiver sensitivity measurement is to use exhaustive search in a specified range to identify the receiver's sensitivity. However, such an exhaustive search is neither efficient in terms of measurement time, nor accurate due to the fixed step-size. In this paper, a data-driven approach is proposed to measure the receiver sensitivity based on a dynamic linearization representation of a time-varying pseudo-gradient parameter estimation procedure. Unlike the model-based approach, the proposed data-driven approach is dependent only on the input and output measurement data. Furthermore, an analytical approach is presented to derive the minimum number of test packets needed to satisfy the desired confidence level for packet error rate estimation. By adapting the number of test packets, the proposed approach can converge to the exact receiver sensitivity with less time. A theoretical analysis of the proposed approach is provided and further validated by numerical analyses and real-world experimental verification. These analyses show that the proposed data-driven sensitivity measurement can a achieve good estimation performance within a few iterations as well as reduce measurement time.
AB - Receiver sensitivity is one of the most important parameters in determining the overall performance of a radio frequency communication system. The traditional receiver sensitivity measurement is to use exhaustive search in a specified range to identify the receiver's sensitivity. However, such an exhaustive search is neither efficient in terms of measurement time, nor accurate due to the fixed step-size. In this paper, a data-driven approach is proposed to measure the receiver sensitivity based on a dynamic linearization representation of a time-varying pseudo-gradient parameter estimation procedure. Unlike the model-based approach, the proposed data-driven approach is dependent only on the input and output measurement data. Furthermore, an analytical approach is presented to derive the minimum number of test packets needed to satisfy the desired confidence level for packet error rate estimation. By adapting the number of test packets, the proposed approach can converge to the exact receiver sensitivity with less time. A theoretical analysis of the proposed approach is provided and further validated by numerical analyses and real-world experimental verification. These analyses show that the proposed data-driven sensitivity measurement can a achieve good estimation performance within a few iterations as well as reduce measurement time.
KW - Receiver sensitivity
KW - data-driven signal processing
KW - pseudo partial derivative
KW - radio frequency
KW - statistical analysis
KW - wireless communication systems
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U2 - 10.1109/TCOMM.2019.2891708
DO - 10.1109/TCOMM.2019.2891708
M3 - Article
AN - SCOPUS:85065927666
SN - 0090-6778
VL - 67
SP - 3665
EP - 3676
JO - IEEE Transactions on Communications
JF - IEEE Transactions on Communications
IS - 5
M1 - 8606141
ER -