Semi-analytical computation of error vector magnitude for UMTS SAW filters

Freisleben, S.

doi:10.1109/ultsym.2002.1193364

Cited by 9 publications

(2 citation statements)

References 3 publications

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“…Basically, it is an average frequency response (S 21 ) weighted with the spectral power distribution of a WCDMA signal. EVM is a measure of signal distortion due to non-uniform attenuation and non- uniform group delay over a 5 MHz wide WCDMA channel [10]. Both, power transfer function and error vector magnitude are plotted as function of center frequency of the respective WCDMA channel.…”

Section: B Dual Mode Receiversmentioning

confidence: 99%

Concepts for RF Front-Ends for Multi-Mode, Multi-Band Cellular Phones

Bauernschmitt¹,

Block²,

Hagn³

et al. 2007

2007 European Conference on Wireless Technologies

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This paper describes front-end architectures of modern multi-mode, multi-band cellular phones and will discuss the requirements on RF filtering in such applications. Special focus will be on dual mode (GSM and WCDMA) cellular phones with four GSM and three WCDMA bands. On the one hand driven by forward integration -e.g., from PA function via transmit front-end to a fully integrated radio -on the other hand influenced by new requirements of 3G systems and the integration of complementary access, filtering components such as SAW and BAW filters have to solve several increased requirements simultaneously. New technologies are required to follow the demand of increased RF performance, reduced PCB area consumption and continuously decreasing component costs.

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Section: B Dual Mode Receiversmentioning

confidence: 99%

Concepts for RF Front-Ends for Multi-Mode, Multi-Band Cellular Phones

Bauernschmitt¹,

Block²,

Hagn³

et al. 2007

2007 European Conference on Wireless Technologies

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“…McKinley et al [15] derived EVM equations based on normalization of measured WLAN data, and Ku and Kenney [16] proposed a method to estimate EVM for a power amplifier by use of an intrinsic kernel function derived from two-tone intermodulation measurements. Freisleben [17] derived equations for a semi-analytical approach to estimate EVM for SAW filters with good experimental agreement.…”

Section: Introduction and State-of-the-artmentioning

confidence: 99%

Robust Computation of Error Vector Magnitude for Wireless Standards

Jensen

Larsen

2013

IEEE Trans. Commun.

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The modulation accuracy described by an error vector magnitude is a critical parameter in modern communication systems -defined originally as a performance metric for transmitters but now also used in receiver design and for more general signal analysis. The modulation accuracy is a measure of how far a test signal is from a reference signal at the symbol values when some parameters in a reconstruction model are optimized for best agreement. This paper provides an approach to computation of error vector magnitude as described in several standards from measured or simulated data. It is shown that the error vector magnitude optimization problem is generally non-convex. Robust estimation of the initial conditions for the optimizer is suggested, which is particularly important for a non-convex problem. A Bender decomposition approach is used to separate convex and non-convex parts of the problem to make the optimization procedure simpler and robust. A two step global optimization method is suggested where the global step is the grid method and the local method is the Newton method. A number of test cases are shown to illustrate the concepts.

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