Performance analysis of maximum likelihood estimation for transmit power based on signal strength model

Xiao Li Hu; Pin Han Ho; Limei Peng

doi:10.3390/jsan7030038

Performance analysis of maximum likelihood estimation for transmit power based on signal strength model

Xiao Li Hu, Pin Han Ho, Limei Peng

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

We study theoretical performance of Maximum Likelihood (ML) estimation for transmit power of a primary node in a wireless network with cooperative receiver nodes. The condition that the consistence of an ML estimation via cooperative sensing can be guaranteed is firstly defined. Theoretical analysis is conducted on the feasibility of the consistence condition regarding an ML function generated by independent yet not identically distributed random variables. Numerical experiments justify our theoretical discoveries.

Original language	English
Article number	38
Journal	Journal of Sensor and Actuator Networks
Volume	7
Issue number	3
DOIs	https://doi.org/10.3390/jsan7030038
State	Published - 4 Sep 2018

Keywords

Cooperative receiver
Cooperative sensing
Maximum likelihood
Wireless network

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10.3390/jsan7030038

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abstract = "We study theoretical performance of Maximum Likelihood (ML) estimation for transmit power of a primary node in a wireless network with cooperative receiver nodes. The condition that the consistence of an ML estimation via cooperative sensing can be guaranteed is firstly defined. Theoretical analysis is conducted on the feasibility of the consistence condition regarding an ML function generated by independent yet not identically distributed random variables. Numerical experiments justify our theoretical discoveries.",

keywords = "Cooperative receiver, Cooperative sensing, Maximum likelihood, Wireless network",

author = "Hu, {Xiao Li} and Ho, {Pin Han} and Limei Peng",

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AU - Peng, Limei

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AB - We study theoretical performance of Maximum Likelihood (ML) estimation for transmit power of a primary node in a wireless network with cooperative receiver nodes. The condition that the consistence of an ML estimation via cooperative sensing can be guaranteed is firstly defined. Theoretical analysis is conducted on the feasibility of the consistence condition regarding an ML function generated by independent yet not identically distributed random variables. Numerical experiments justify our theoretical discoveries.

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KW - Cooperative sensing

KW - Maximum likelihood

KW - Wireless network

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Performance analysis of maximum likelihood estimation for transmit power based on signal strength model

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