On the optimality of equal gain combining for energy detection of unknown signals

Sinan Gezici; Zafer Sahinoglu; H. Vincent Vincent Poor

doi:10.1109/LCOMM.2006.060906

On the optimality of equal gain combining for energy detection of unknown signals

Sinan Gezici, Zafer Sahinoglu, H. Vincent Vincent Poor

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

28 Scopus citations

Abstract

In this letter, the optimality of equal gain combining (EGC) for energy detection of unknown signals in a system with receive-diversity is studied. It is shown that EGC results in an optimal test statistic for inflnitesimally small signal-to-noise ratios (SNRs); however, it does not yield the optimal test for all SNR values according to the Neyman-Pearson criterion. In other words, EGC does not induce a uniformly most powerful (UMP) test for unknown signal detection.

Original language	English (US)
Pages (from-to)	772-774
Number of pages	3
Journal	IEEE Communications Letters
Volume	10
Issue number	11
DOIs	https://doi.org/10.1109/LCOMM.2006.060906
State	Published - Nov 2006
Externally published	Yes

All Science Journal Classification (ASJC) codes

Modeling and Simulation
Computer Science Applications
Electrical and Electronic Engineering

Keywords

Diversity
Energy detection
Neyman-Pearson criterion

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10.1109/LCOMM.2006.060906

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abstract = "In this letter, the optimality of equal gain combining (EGC) for energy detection of unknown signals in a system with receive-diversity is studied. It is shown that EGC results in an optimal test statistic for inflnitesimally small signal-to-noise ratios (SNRs); however, it does not yield the optimal test for all SNR values according to the Neyman-Pearson criterion. In other words, EGC does not induce a uniformly most powerful (UMP) test for unknown signal detection.",

keywords = "Diversity, Energy detection, Neyman-Pearson criterion",

author = "Sinan Gezici and Zafer Sahinoglu and {Vincent Poor}, {H. Vincent}",

year = "2006",

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doi = "10.1109/LCOMM.2006.060906",

language = "English (US)",

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AU - Sahinoglu, Zafer

AU - Vincent Poor, H. Vincent

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N2 - In this letter, the optimality of equal gain combining (EGC) for energy detection of unknown signals in a system with receive-diversity is studied. It is shown that EGC results in an optimal test statistic for inflnitesimally small signal-to-noise ratios (SNRs); however, it does not yield the optimal test for all SNR values according to the Neyman-Pearson criterion. In other words, EGC does not induce a uniformly most powerful (UMP) test for unknown signal detection.

AB - In this letter, the optimality of equal gain combining (EGC) for energy detection of unknown signals in a system with receive-diversity is studied. It is shown that EGC results in an optimal test statistic for inflnitesimally small signal-to-noise ratios (SNRs); however, it does not yield the optimal test for all SNR values according to the Neyman-Pearson criterion. In other words, EGC does not induce a uniformly most powerful (UMP) test for unknown signal detection.

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KW - Neyman-Pearson criterion

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JO - IEEE Communications Letters

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On the optimality of equal gain combining for energy detection of unknown signals

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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