Abstract

<!-- /* Font Definitions */ @font-face {font-family:??; panose-1:2 1 6 0 3 1 1 1 1 1; mso-font-alt:SimSun; mso-font-charset:134; mso-generic-font-family:auto; mso-font-pitch:variable; mso-font-signature:3 135135232 16 0 262145 0;} @font-face {font-family:"\@??"; panose-1:2 1 6 0 3 1 1 1 1 1; mso-font-charset:134; mso-generic-font-family:auto; mso-font-pitch:variable; mso-font-signature:3 135135232 16 0 262145 0;} /* Style Definitions */ p.MsoNormal, li.MsoNormal, div.MsoNormal {mso-style-parent:""; margin:0cm; margin-bottom:.0001pt; text-align:justify; text-justify:inter-ideograph; mso-pagination:none; font-size:10.5pt; mso-bidi-font-size:12.0pt; font-family:"Times New Roman"; mso-fareast-font-family:??; mso-font-kerning:1.0pt;} /* Page Definitions */ @page {mso-page-border-surround-header:no; mso-page-border-surround-footer:no;} @page Section1 {size:612.0pt 792.0pt; margin:72.0pt 90.0pt 72.0pt 90.0pt; mso-header-margin:36.0pt; mso-footer-margin:36.0pt; mso-paper-source:0;} div.Section1 {page:Section1;} -->

Accurate power estimation has an important role for power control and handoff decisions in mobile communications. Window based weighed sample average power estimators are commonly used due to their simplicity. In practice, the performances of these estimators degrade severely when the estimators are used in the presence of correlated samples. In this paper performances of the three local mean power estimators namely, sample average, optimum unbiased and maximum likelihood estimators, are analysed in the presence of correlated samples. The variance of the estimators is used as performance measures. Finally, the simulation results show that the performances of the optimum unbiased and maximum likelihood estimators are very good as compared to the performance of the sample average estimator.

This work is licensed under a Creative Commons Attribution 4.0 License.