Learn about RF designs, radio frequencies, RADAR, GPS, and RF terms you need to know in today’s electrical engineering podcast!
We sit down with Phil Gresock to talk about the basics of RF for “DC plebians.” Learn about RF designs, radio frequencies, RADAR, GPS, and RF terms you need to know in today’s electrical engineering podcast!
RF stands for radio frequency
00:40 Phil Gresock was an RF application engineer
1:15 Everything is time domain, but a lot of RF testing tools end up being frequency domain oriented
2:15 Think about radio, for example. A tall radio tower isn’t actually one big antenna!
7:00 Communication is just one use case. RADAR also is an RF application.
8:10 The principles between RF and DC or digital use models are very similar, but the words we use tend to be different.
Bandwidth for oscilloscopes means DC to a frequency, but for RF it means the analysis bandwidth around a center frequency
9:22 Cellular and FCC allocation chart will talk about different “channels.”
Channel in the RF world refers to frequency ranges, but in the DC domain it typically refers to a specific input.
10:25 Basic RF block diagram:
First, there’s an input from an FPGA or data creating device. Then, the signal gets mixed with a local oscillator (LO). That then connects to a transmission medium, like a fiber optic cable or through the air.
Cable TV is an RF signal that is cabled, not wireless.
Then, the transmitted signal connects to an RF downcoverter, which is basically another mixer, and that gets fed into a processing block.
Wide bandgap semiconductors, like Gallium Nitride (GaN) and Silicon Carbide (SiC) are shaping the future of power electronics by boosting power efficiency and reducing physical footprint. Server farms, alternative energy sources, and electrical grids will all be affected!
Wide bandgap semiconductors, like Gallium Nitride (GaN) and Silicon Carbide (SiC) are shaping the future of power electronics by boosting power efficiency and reducing physical footprint. Server farms, alternative energy sources, and electrical grids will all be affected! Mike Hoffman and Daniel Bogdanoff sit down with Kenny Johnson to discuss in today’s electrical engineering podcast.
3:00 What is a wide bandgap semiconductor? GaN (Gallium Nitride) devices and SiC (Silicon Carbide) can switch on and off much faster than typical silicon power devices. Wide bandgap semiconductors also have better thermal conductivity. And, wide bandgap semiconductors have a significantly lower drain-source resistance (R-on).
For switch mode power supplies, the transistor switch time is the key source of inefficiency. So, switching faster makes things more efficient.
4:00 They will also reduce the size of power electronics.
6:30 Wide bandgap semiconductors have a very fast rise time, which can cause EMI and RFI problems. The high switching speed also means they can’t handle much parasitic inductance. So, today’s IC packaging technology isn’t ideal.
8:30 Wide bandgap semiconductors are enabling the smart grid. The smart grid essentially means that you only turning on things being used, and turning off power completely when they aren’t being used.
9:35 Wide bandgap semiconductors will probably be integrated into server farms before they are used in power grid distribution or in homes.
10:20 Google uses a lot of power. 2.3 TWh (terawatt hour)
NYT article: http://www.nytimes.com/2011/09/09/technology/google-details-and-defends-its-use-of-electricity.html
It’s estimated Google has 900,000 servers, and that accounts for maybe 1% of the world’s servers.
So, they are willing to put in the investment to work out the details of this technology.
11:50 The US Department of Energy wants people to get an advanced degree in power electronics. Countries want to have technology leadership in this area.
13:00 Wide bandgap semiconductors are also very important for wind farms and other alternative forms of energy.
Having a solid switch mode power supply means that you don’t have to have extra capacity.
USA Dept of Energy: If industrial motor systems were wide bandgap semiconductors took over, it would save a ton of energy.
14:45 A huge percentage of the world’s power is consumed by electrical pumps.
16:20 Kenny’s oldest son works for a company that goes around and shows companies how to recover energy costs.
There aren’t many tools available for measuring wide bandgap semiconductor power electronics.
19:30 Utilities and servers are the two main industries that will initially adopt wide band gap semiconductors
20:35 When will this technology get implemented in the real world? There are parts available today, but it probably won’t be viable for roughly 2-5 years.
21:00 Devices with fast switching are beneficial, but have their own set of problems. The faster a devices switches, the more EMI and RFI you have to deal with.
Spread spectrum clocking is a technique used to pass EMI compliance.
24:00 Band gaps of different materials: Diamond 5.5 eV Gallium Nitride (GaN) 3.4 eV Silicon Carbide (SiC) 3.3 eV
Learn about parallel computing, the rise of heterogeneous processing (also known as hybrid processing), and quantum engineering in today’s EEs Talk Tech electrical engineering podcast!
Learn about parallel computing, the rise of heterogeneous processing (also known as hybrid processing), and the prospect of quantum engineering as a field of study!
Parallel computing used to be a way of sharing tasks between processor cores.
When processor clock rates stopped increasing, the response of the microprocessor companies was to increase the number of cores on a chip to increase throughput.
But now, the increased use of specialized processing elements has become more popular.
A GPU is a good example of this. A GPU is very different from an x86 or ARM processor and is tuned for a different type of processing.
GPUs are very good at matrix math and vector math. Originally, they were designed to process pixels. They use a lot of floating point math because the math behind how a pixel value is computed is very complex.
A GPU is very useful if you have a number of identical operations you have to calculate at the same time.
GPUs used to be external daughter cards, but in the last year or two the GPU manufacturers are starting to release low power parts suitable for embedded applications. They include several traditional cores and a GPU.
So, now you can build embedded systems that take advantage of machine learning algorithms that would have traditionally required too much processing power and too much thermal power.
This is an example of a heterogeneous processor (AMD) or hybrid processor. A heterogeneous processor contains cores of different types, and a software architect figures out which types of workloads are processed by which type of core.
Andrew Chen (professor) has predicted that this will increase in popularity because it’s become difficult to take advantage of shrinking the semiconductor feature size.
This year or next year, we will start to see heterogeneous processors (MOOR) with multiple types of cores.
Traditional processors are tuned for algorithms on integer and floating point operations where there isn’t an advantage to doing more than one thing at a time. The dependency chain is very linear.
A GPU is good at doing multiple computations at the same time so it can be useful when there aren’t tight dependency chains.
Neither processor is very good at doing real-time processing. If you have real time constraints – the latency between an ADC and the “answer” returned by the system must be short – there is a lot of computing required right now. So, a new type of digital hardware is required. Right now, ASICs and FPGAs tend to fill that gap, as we’ve discussed in the All about ASICs podcast.
Quantum cores (like we discussed in the what is quantum computing podcast) are something that we could see on processor boards at some point. Dedicated quantum computers that can exceed the performance of traditional computers will be introduced within the next 50 years, and as soon as the next 10 or 15 years.
To be a consumer product, a quantum computer would have to be a solid state device, but their existence is purely speculative at this point in time.
Quantum computing is reinventing how processing happens. And, quantum computers are going to tackle very different types of problems than conventional computers.
There is a catalog on the web of problems and algorithms that would be substantially better on a quantum on a computer than a traditional computer.
People are creating algorithms for computers that don’t even exist yet.
The Economist estimated that the total spend on quantum computing research is over 1 Billion dollars per year globally. A huge portion of that is generated by the promise of these algorithms and papers. The interest is driven by this.
Quantum computers will not completely replace typical processors.
Lee’s opinion is that the quantum computing industry is still very speculative, but the upsides are so great that neither the incumbent large computing companies nor the industrialized countries want to be left behind if it does take off.
The promise of quantum computing is beyond just the commercial industry, it’s international and inter-industry. You can find long whitepapers from all sorts of different governments laying out a quantum computing research strategy. There’s also a lot of venture capitalists investing in quantum computing.
Is this research and development public, or is there a lot of proprietary information out there? It’s a mixture, many of the startups and companies have software components that they are open sourcing and claim to have “bits of physics” working (quantum bits or qbits), but they are definitely keeping trade secrets.
19:50 Quantum communication means space lasers.
Engineering with quantum effects has promise as an industry. One can send photons with entangled states. The Chinese government has a satellite that can generate these photons and send them to base stations. If anyone reads them they can tell because the wave function collapsed too soon.
Quantum sensing promises to develop accelerometers and gyroscopes that are orders of magnitude more sensitive than what’s commercially available today.
Quantum engineering could become a new field. Much like electrical engineering was born 140 years ago, electronics was born roughly 70 years ago, computer science was born out of math and electrical engineering. It’s possible that the birth of quantum engineering will be considered to be some point in the next 5 years or last 5 years.
Lee’s favorite quantum state is the Bell state. It’s the equal probability state between 1 and 0, among other interesting properties. The Bell state encapsulates a lot of the quantum weirdness in one snippet of math.
Pricing a new hardware product in a global economy with regional pricing, psychological factors, and the challenges of pricing in white space. This week’s guest is Brig Asay. Hosted by Daniel Bogdanoff and Mike Hoffman, EEs Talk Tech is a twice-monthly electrical engineering podcast discussing tech trends and industry news from an electrical engineer’s perspective.
Daniel Bogdanoff and Mike Hoffman sit down with Brig Asay to talk about how to price a hardware project. Listen in as they discuss the complexities of pricing a new hardware product in a global economy.
Spreadsheets are the killer of pricing. They compete with your gut feeling.
$10K per GHz of bandwidth is a standard in oscilloscope pricing, but it doesn’t always apply. When we came out with the Infiniium Z-Series, a 63 GHz scope, we knew the market couldn’t support a $630K price.