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RL1218JK07R047L_Datasheet PDF


 The next step in our analysis was to analyze all 70 applications and assign a penetration rate by device by region for the year 2023 (10 years out). In most cases our penetration rate assumption for connected devices range from 2 percent to 10 percent.  Semico believes this is a very conservative view.  

RL1218JK07R047L_Datasheet PDF

From our perspective, it is a conservative but reasonable adoption rate as we are already seeing manufacturers marketing Internet of Things products. One example is Lodi garage door openers. This manufacturer is currently selling a garage door opener that can be monitored and controlled from your smart phone or tablet.

Based on conservative penetration rates of 2 percent to 10 percent, the worldwide residential only” Internet of Things in 2023 will grow to 22.7 billion products. This would result in a semiconductor unit TAM of 204 billion devices associated with the Internet of Things.  For comparison purposes, in 2012, the worldwide unit market for semiconductors totaled 673 billion.  The residential Internet of Things represents a 30 percent increase in the number of semiconductor units compared to the 2012 unit TAM.  Improved price points and widely adopted standards could set off a much higher product acceptance.    

Combine this with Internet of Things for commercial and industrial applications and we can expect semiconductor fabs to be kept quite busy over the next ten years.       This excerpt came from an upcoming Semico Report.  For more information, contact Semico.

RL1218JK07R047L_Datasheet PDF

Formula One and Indy racing teams are increasingly converging on a simulator in Italy to give themselves an edge in the design of their cars. The simulator, which enables professionals to drive and evaluate virtual versions of their vehicles, is gaining popularity among race teams because it enables them to get feedback from drivers early in the development process.

In the past, the driver was able to give you feedback only after the car was produced, which is typically 15 months for a racing car,” Allessandro Moroni, manager of simulation for Dallara Auomobili, an Italian race car chassis designer, told Design News. Now, from the very first stages, we can get the driver involved.”

RL1218JK07R047L_Datasheet PDF

Built by Moog Inc., the driving simulator is essentially a motion base. It consists of a 2,000-kg aluminum dome mounted atop six electromechanical actuators. The actuators allow drivers to feel the forces of acceleration and braking. A 270-degree screen inside the dome also lets them see a projected image of the track, while speakers enable them to hear the roar of the engine. Liquid crystal displays on screens alongside the drivers even let them examine the scene behind the car in rear view mirrors.

Click to read the rest of this article on Design News.

Figure 12: ET PA ACLR vs Temperature (105C range)

In a handset environment, the load impedance presented to the PA is not well controlled due to reflections from nearby objects, which can result in the PA having to work into load mismatches as high as 3:1 VSWR. The ET PA’s ‘self linearization’ principle previously described is also applicable under high VSWR conditions and this can result in significantly improved EVM and ACPR performance compared with the same PA operated in fixed supply mode (see Figure 13)

Summary The system efficiency benefit of operating a PA in ET mode is widely known. However, it also offers other useful system benefits, such as increased output power, improved operation into mismatched loads, and insensitivity to temperature variations. In contrast to fixed supply PAs, the performance of an ET PA is not ‘self contained’ and requires substantially more data to be gathered to predict system performance. This requires use of a test environment which allows the supply voltage in addition to input power to be swept. A key aspect is the definition of the ‘shaping table’ which defines the relationship between supply voltage and RF power. This defines many key PA metrics. Once the shaping function is defined, efficiency and linearity can be directly measured using an appropriate ‘system characterization’ bench.


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