Spectral Analysis of Polynomial Nonlinearity with Applications to RF Power Amplifiers
- PDF / 903,562 Bytes
- 10 Pages / 600 x 792 pts Page_size
- 94 Downloads / 167 Views
Spectral Analysis of Polynomial Nonlinearity with Applications to RF Power Amplifiers G. Tong Zhou School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0250, USA Email: [email protected]
Raviv Raich School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0250, USA Email: [email protected] Received 1 September 2003; Revised 2 December 2003 The majority of the nonlinearity in a communication system is attributed to the power amplifier (PA) present at the final stage of the transmitter chain. In this paper, we consider Gaussian distributed input signals (such as OFDM), and PAs that can be modeled by memoryless or memory polynomials. We derive closed-form expressions of the PA output power spectral density, for an arbitrary nonlinear order, based on the so-called Leonov-Shiryaev formula. We then apply these results to answer practical questions such as the contribution of AM/PM conversion to spectral regrowth and the relationship between memory effects and spectral asymmetry. Keywords and phrases: nonlinear, polynomial, power amplifier, spectral analysis.
1.
INTRODUCTION
Power amplifiers (PAs) are important components of communications systems and are inherently nonlinear. For Example, the so-called class AB PAs, which are moderately nonlinear, are typically employed in wireless base stations and handsets. When a nonconstant modulus signal goes through a nonlinear PA, spectral regrowth (broadening) appears in the output, which in turn causes adjacent channel interference (ACI). Stringent limits on ACI are imposed by the standard bodies and thus the extent of the PA nonlinearity must be controlled. We are interested in predicting the amount of spectral regrowth for a given level of PA nonlinearity. Since more linear PAs are less efficient, one may want to maximize nonlinearity (and hence optimize efficiency) subject to the spectral mask constraint. Such optimization strategy is feasible if we have tools for spectral regrowth analysis of the nonlinear output. If the PA input is Gaussian, the PA output power spectral density (PSD) has been derived for a 5th-order nonlinear PA in [1, 2]. In [3], the analysis was carried out for a 9th-order nonlinear PA. The results in [4] are fairly general but developed for bandpass signals, whereas references [1, 2, 3] and the present paper adopt a baseband nonlinear formulation. In [5], a general expression is given without proof. When the PA input is non-Gaussian, theoretical analysis becomes more
complicated, but results are available in [6] for a 7th-order nonlinear PA with (non-)Gaussian inputs. The objective of this paper is to derive closed-form expressions for the PA output PSD (or output autocovariance function) for an arbitrary nonlinear order, for both the memoryless and memory baseband polynomial PA models. The PA input is assumed to be Gaussian distributed, which is a reasonable assumption for OFDM signals [2], forward link CDMA signals with a large number of Walsh-coded channels at the
Data Loading...
