Low-Power Maximum Magnitude Computation for PAPR Reduction in OFDM Transmitters

Author(s):  
Th. Giannopoulos ◽  
V. Paliouras
2013 ◽  
Vol 380-384 ◽  
pp. 3538-3541
Author(s):  
Qian Hui Liu ◽  
Jian Wang

High peak-to-average power ratio (PAPR) is one of the main disadvantages for OFDM signals, which will always result in low power efficiency of power amplifier. The peak cancellation method is a powerful PAPR reduction technique. In this paper, the advanced peak cancellation implement method (APC) is proposed for OFDM signals. Extensive simulations demonstrate that in comparison with the conversational peak cancellation implement method, the APC is more suitable for OFDM signals due to less iteration and comparative performance.


2018 ◽  
Vol 49 (1) ◽  
pp. 47-62 ◽  
Author(s):  
Petra C. Schmid

Abstract. Power facilitates goal pursuit, but how does power affect the way people respond to conflict between their multiple goals? Our results showed that higher trait power was associated with reduced experience of conflict in scenarios describing multiple goals (Study 1) and between personal goals (Study 2). Moreover, manipulated low power increased individuals’ experience of goal conflict relative to high power and a control condition (Studies 3 and 4), with the consequence that they planned to invest less into the pursuit of their goals in the future. With its focus on multiple goals and individuals’ experiences during goal pursuit rather than objective performance, the present research uses new angles to examine power effects on goal pursuit.


2019 ◽  
Vol 117 (2) ◽  
pp. 338-363 ◽  
Author(s):  
Emily J. Cross ◽  
Nickola C. Overall ◽  
Rachel S. T. Low ◽  
James K. McNulty

2004 ◽  
Vol 18 (3) ◽  
pp. 37
Author(s):  
J. Frenkil
Keyword(s):  

1989 ◽  
Vol 28 (01) ◽  
pp. 14-19 ◽  
Author(s):  
J. F. Dartigues ◽  
Ph. Peytour ◽  
E. Puymirat ◽  
P. Henry ◽  
M. Gagnon ◽  
...  

Abstract:When studying the possible effects of several factors in a given disease, two major problems arise: (1) confounding, and (2) multiplicity of tests. Frequently, in order to cope with the problem of confounding factors, models with multiple explanatory variables are used. However, the correlation structure of the variables may be such that the corresponding tests have low power: in its extreme form this situation is coined by the term “multicollinearity”. As the problem of multiplicity is still relevant in these models, the interpretation of results is, in most cases, very hazardous. We propose a strategy - based on a tree structure of the variables - which provides a guide to the interpretation and controls the risk of erroneously rejecting null hypotheses. The strategy was applied to a study of cervical pain syndrome involving 990 subjects and 17 variables. Age, sex, head trauma, posture at work and psychological status were all found to be important risk factors.


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