Its interesting that if one wants to establish a WiFi connection with a predetermined address then one has to understand the the concepts of Ipaddress ( local), Ipaddress gateway, Ipaddress subnet, Ipaddress Primary DNS, Ipaddress secondary DNS.

A lot of this information is available ( in win 10 for example) by using the command under the CMD system i.e. run>cmd .

At present a significant amount of work is being done on WiFi at Signal Processing Group Inc. Please visit our website at www.signalpro.biz.

Some simulation results are presented in this post that may be of interest to layout of RFMW circuits as well as to the design of the MIC or MMIC circuitry. What has been done here, is to simulate a microstrip with fixed width and varying length. The source impedance is 50 Ohm and the load impedance is 50 Ohms. What it shows is, that in layout for example, if the width is constant ( and designed for 50 Ohms) the length of a microstrip ( where alpha = 0) causes a very small change in the peak voltage across the load. However, the angle of the voltage changes significantly. This has implications for interconnecting devices using microstrip and phase issues ( if important). Your comments are welcome. Please visit the Signal Processing Group Inc website at www.signalpro.biz for other interesting items.

Note: Simulations were run using QUCS.

A compensation filter for a CIC filter was required. We chose to use the free software tool OCTAVE to help us do this. Here is the sequence of tasks that were done. (Be aware that a compensation filter filter design is not trivial unless you have been doing it for a long while. )

1.0) Design the CIC filter. 2) Measure the droop of the filter . (3) Use the inverse response of the CIC filter to synthesize the compensation filter. (4) Use the frequency response of the inverse filter to generate a frequency – magnitude table. ( Much like a piecewise linear SPICE signal). This table consists of frequency – magnitude pairs for the compensation filter you want. (5) Use this table as the input to the function fir2(n,f,m) in Octave. This function provides the coefficients of the filter you need. However, the trick is to choose the right “n”; It took us a while to get the value of n right for our purposes. You will have to choose yours however you wish. (6) Run fir2 and take the results ( say “b[]”) and generate the impulse response of the filter from it using another OCTAVE function called impz(). The input argument is the “b[]” you just got from fir2. Once you have the impulse response use the freqz function in Octave to simulate the filter you just designed. Once you have the frequency magnitude characteristic of the new filter you can do a multiplot using the plot function from OCTAVE. This allows you to compare the two filters. i.e. the filter you wanted and the filter you designed.

You can make adjustments by using multiple runs of the above sequence until you get the best filter you can get, An example of the multiplot is shown below. The blue line is the original filter and the orange line is the one we got from using the sequence quoted above. Please visit the Signal Processing Group Inc website for more info and contact information.

Octave is GNU ( read public domain free CAD tool). It can be downloaded from the Octave website. We downloaded the latest version and the following is our experience with it. (1) Installation: Installation was not too painful but had to be done multiple times until we succeeded. Takes a few minutes but when it works its really fine.

(2) Execute: This was really difficult to do. After installation a couple of Icons appear on the desktop. One for “CLI” and one for “GUI” Neither of them work. Its pure frustration initially before we realized these icons were never going to work. So we went back to the system and traced where the binaries were– also a fairly hard path — and ran octave from there. It did run but it ran in a shell using command lines.

(3) Utilities: Octave core does not have the scripts we wanted to run like FFT, IFFT etc. These and most other scripts all are in octave “packages”. So we tried to get these packages to run but it took a significant amount of time ( and with significant help from Google) to finally load the packages we wanted. After that we could use the program.

We still have not stress tested the program but I am happy to report that Octave is now running on our machine.

Is it worth all this trouble? I think it is. For the price you pay for it i.e $0.0, and the capability you get once the initial teething problems are over it surely is worth it.

The competitor to Octave is of course MATLAB but MATLAB is very expensive so if you do not have the money to pay for MATLAB you might try OCTAVE. Please visit the Signal Processing Group Inc website for more technical info.

Its interesting that although GAN is in regular and fairly extensive use today, how Wolfspeed and QORVO have not released GAN models for public domain simulators. It is also interesting that public domain developers such as LTSPICE and QUCS seem to be not interested in implementing a proper GAN model for RF and/or Power electronics. This trend has limited the usage of GAN and both fabricators and users of GAN are suffering, It is about time some entrepreneurs ( University or industrial) develop these models for the public domain simulators and thereby give some relief to users who do not have Fort Knox in their back pockets to buy ADS or Microwave Office.

Our thanks to Keysight for letting us “evaluate” the 2020 update of ADS. We found it enormously helpful. The program has grown tremendously since we last used it, and is now a massive accomplishment by its owners, Keysight. We were impressed by the features in the program and its ability to help us simulate and design complex RFMW circuitry very quickly and smoothly. The AEL feature is great also. ( Applications Extension Language). The ability to write equations extends the power of the tool and is quite simple to do once you get used to it. We only have one or two reservations about the tool and these, in a strange way, have to do with its great performance. The program is so extensive that it will take a typical engineer a while to get to grips with it. Also getting technical support is good, but can take time and that may be frustrating. ( This is a consequence of the many users of ADS and the relative number of experts to support it, I assume). Otherwise the program is just great and the ability to evaluate its performance on a real, live project can be exceptionally useful. Please visit our website for more technical info as well as info about Signal Processing Group Inc.

Its interesting how little real information about this topic there is on the web !!! There are reams of paper dedicated to learned treatises and another set of reams of paper ( and articles) dedicated to so called practical methods of design but we find these of little value to a practicing engineer unless that practicing engineer is willing to spend an inordinate amount of time and effort to sift through a lot of unnecessary information about FIR filter design. To put it simply you have two pieces of information you need to do the task. Either you have an arbitrary frequency response you want to implement as a FIR filter or you have an impulse response you want to use to implement a FIR filter. The frequency response is the “FFT” of the impulse response while the impulse response is the reverse. It is our intention to present in these posts the details of techniques that allow an engineer to do this in a considered and logical fashion. Of course there is always MATLAB to fall back on, except MATLAB is an expensive piece of software. There is also OCTAVE but this is all but impossible to use or install correctly. However, it does have the merit of being very inexpensive .Also the mechanics of how you use FIR2, FIR1 etc is hidden so it is not instructive. Of course many engineers may find this an advantage. We feel that there is more to FIR filter design than just running MATLAB scripts. Please visit our website for more information on related topics.

It is interesting that the MATLAB utilities that I seem to use a lot ( besides those for filter design like FIR1, REMEZ and so on) are SPLINE, POLYFIT and POLYVAL. I typically use these for fitting x-y data for approximations of various measurements. In addition the identities based on INTERP are also very useful and can be used with the fitting utilities mentioned above. MATLAB has extensive documentation on these and their multiple options.

Please visit Signal Processing Group Inc’s. website for more technical and other information.

As the semiconductor technology line widths grow smaller and smaller, many functions that were implemented with analog techniques have to be designed using digital techniques.

Filtering is one such idea. Digital filters are a natural for fine line technology once the signal has been converted to digital. One of the more popular techniques is FIR filtering.

These filters have some favorable characteristics that make them popular for implementation in SOC technology. A recent book released by Signal Processing Group Inc ( authored by Ain Rehman) describes these types of filters in a succinct and practical manner.

This should allow a practicing engineer ( or a student) to implement FIR filters fairly easily. Click on the image below to get your copy. It is not free to purchase but costs a modest amount and gives much in exchange. Also please visit the Signal Processing Group Inc. website for more info.

Further to an earlier post on various frequencies and rates in a sampled DSP system or circuit, here is small addition to the collection. We know that if fs is the sampling rate, or sampling frequency, we can use it to normalize other frequencies in the circuit or system, by dividing the other frequencies by fs ( or fs/2) which is the normalizing factor. So we can use fs as unity ( fs/fs =1) and use this metric to normalize all other frequencies. We can also choose to use fs/2 as the normalizing factor so fs would be 2 in this case. MATLAB prefers to use fs/2 as the normalizing factor, so a 1 is fs/2 in this case.

We can also use another normalized expression for the frequency or frequencies. Divide the frequency in question by the sampling frequency and equate this to wo/2*pi. ( I like to think of wo as the radian frequency). The frequency in question ( say fo) should be expressed in terms of fs. So now you can express normalized frequencies in terms of pi!. All these units are very much in use in the DSP world. Please visit the Signal Processing Group Inc. website for more technical information.

I also like the treatment of digital frequency from two sources. Professor Fowler expose’ and from AllSignals, a website that appears to be very useful all around. I think anyone desirous of entering or remaining in the field of DSP should be very aware of the concept. Please visit our website for more info about us and technical info.