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**1 - 3**of**3**### Design Methodology for Multichannel Communication Systems

, 2004

"... A methodology for understanding and modeling the interaction of multiple CDMA signals in a nonlinear multichannel environment is introduced and verified. The analysis is based on understanding the statistical properties of input signals and developing a modeling technique that enables distortion to ..."

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A methodology for understanding and modeling the interaction of multiple CDMA signals in a nonlinear multichannel environment is introduced and verified. The analysis is based on understanding the statistical properties of input signals and developing a modeling technique that enables distortion to be estimated. This is coupled with the introduction of a new behavioral modeling technique that captures the black box characteristics of mul-tichannel amplifiers. In addition, a performance analysis that relates nonlinear distortion to probability of bit error (BER) is introduced. The analysis presented here provides an insight into communication system design by relating distortion to system performance. The methodology is verified using simulations and measurements performed on a nonlinear power amplifier. A nonlinear model was extracted and used in developing the statistical model by which distortion is estimated. The resulting estimates of distortion were verified using measurements of distortion performed on the amplifier using the IS-95 CDMA system standard.

### High Order Volterra Series Analysis Using Parallel Computing

"... INTRODUCTION The Volterra series technique has been used extensively in various applications in the area of nonlinear circuit analysis and optimization (see e.g. references [1]--[28]). Examples are in the (i) analysis of intermodulation in small signal amplifiers [6]--[12], (ii) determination of os ..."

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INTRODUCTION The Volterra series technique has been used extensively in various applications in the area of nonlinear circuit analysis and optimization (see e.g. references [1]--[28]). Examples are in the (i) analysis of intermodulation in small signal amplifiers [6]--[12], (ii) determination of oscillation frequency and amplitude in near sinusoidal oscillators [3]--[5], (iii) analysis of mixers with moderate local oscillator levels [13, 14], analysis of communication systems [14]--[18], and (v) analysis of noise in nonlinear networks [24]--[28]. The use of the Volterra series technique basically involves two steps: (i) first, from specified input signal frequencies to determine all relevant Volterra transfer functions of the network, and (ii) next, to determine the output response from the non-linear network based on specified amplitudes of the input signals. One limitation in the use of Volterra series is that the determination of Volterra transfer functions is usually limi

### The Frequency Domain Behavioral Modeling and Simulation of Nonlinear Analog Circuits and Systems

, 1993

"... LUNSFORD II, PHILIP J. The Frequency Domain Behavioral Modeling and Simulation of Nonlinear Analog Circuits and Systems. (Under the direction of Michael B. Steer.) A new technique for the frequency-domain behavioral modeling and simulation of nonautonomous nonlinear analog subsystems is presented. ..."

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LUNSFORD II, PHILIP J. The Frequency Domain Behavioral Modeling and Simulation of Nonlinear Analog Circuits and Systems. (Under the direction of Michael B. Steer.) A new technique for the frequency-domain behavioral modeling and simulation of nonautonomous nonlinear analog subsystems is presented. This technique extracts values of the Volterra nonlinear transfer functions and stores these values in binary files. Using these files, the modeled substem can be simulated for an arbitrary periodic input expressed as a finite sum of sines and cosines. Furthermore, the extraction can be based on any circuit simulator that is capable of steady state simulation. Thus a large system can be divided into smaller subsystems, each of which is characterized by circuit level simulations or lab measurements. The total system can then be simulated using the subsystem characterization stored as tables in binary files.