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A low cost methodology for simultaneous testing and tuning of multiple chains of MIMO-OFDM wireless transmitter for system-level specifications is presented. Bandwidth-partitioned test stimuli enable the determination of the behavioral characteristics of the different chains of the RF transmitter using a one-time data acquisition. The determined behavioral characteristics of the transmitters are then...
In this paper, we present a low-cost methodology for parallel testing of MIMO-OFDM RF modules using optimized bandwidth-partitioned frequency domain stimulus applied from the embedded DSP module of the MIMO-OFDM system and a simple combination of sensors on the load board. A comprehensive set of specifications of multiple RF modules chains are computed simultaneously from the observed DUT response...
In recent years, MEMS accelerometers are being used on an increasing scale in different spheres of science and technology. Proper testing and calibration of these devices is as vital as that of its design and fabrication. The present paper details with the construction of a centrifuge equipment to be used in static testing of MEMS accelerometers. This is based on a conventional rotating platform generating...
We address the problem of detecting a target moving in clutter environment using an orthogonal frequency division multiplexing (OFDM) radar. The broadband OFDM signal provides frequency diversity to improve the performance of the system. First, we develop a parametric model that accounts for the measurements at multiple frequencies including the Doppler shift. Then, we present a statistical detection...
In this paper, a novel adaptive calibration technique for advanced RF front-ends is proposed in which sensors are implanted in the transmitter and the observed device test response to a special calibration test is compared against the known golden response to the same. Tuning 'knobs' which are built into the circuit are then used to minimize the error between the observed response and the golden response...
Testing remains a major challenge for model transformation development. Test models that are used as test data for model transformations, are constrained by various sources of knowledge that is expressed in different formalisms. Thus, in order to automatically generate test models it is necessary to interpret these different sources of knowledge and combine them into a consistent set of information...
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