John Roach » Old posts

Giving Small Robots New Ways to Move (IEEE)

John Roach — Fri, 23 Oct 2009 06:57:17 +0000

I always thought that there should be smaller robots. We do have the technology. Look at your PDAs,IPhones and HTC model telephones. All are actually sophisticated computers. Why not use this technology to make smaller bots? And while making them smaller why not make the so they can move easily through. After all a cockroach can go to places where you would usually say “How in the hell did it get up there?”.

These 10 years are about bio-robots. By tagging the name of bio-robots I mean robots that act and move like insects and other simple life forms. And if we can perfect our way in constructing and programming such robots we will find out how to make androids!! ( Probably going too far.) I hope to maybe get my hand on some part to make my own. But I just really don’t have the time .

Installed Fedora 11 on Compaq Presario CQ50 (Dual-boot/Vista)

John Roach — Thu, 22 Oct 2009 09:13:35 +0000

Fedora. My first love in linux started with Fedora and now I realized this love was not because of some novelty. It was actually because it is easier to use.(As a developer.) So I simply installed Fedora 11 over Ubuntu 9.04 it worked like a charm tough I had to do couple of tweaks. The first tweak was the adding the recovery hard-disk of Vista to the boot menu. No problem there just a simple grub.conf editing was done as below ;

# grub.conf generated by anaconda # # Note that you do not have to rerun grub after making changes to this file # NOTICE: You have a /boot partition. This means that # all kernel and initrd paths are relative to /boot/, eg. # root (hd0,2) # kernel /vmlinuz-version ro root=/dev/mapper/vg_johnsfedorabox-lv_root # initrd /initrd-version.img #boot=/dev/sda default=3 timeout=15 splashimage=(hd0,2)/grub/splash.xpm.gz #hiddenmenu title NCTUns (2.6.28.9-nctuns-20090901) root (hd0,2) kernel /vmlinuz-2.6.28.9-nctuns-20090901 ro root=/dev/mapper/vg_johnsfe$ initrd /initrd-2.6.28.9-nctuns-20090901.img title Fedora (2.6.30.8-64.fc11.i586) root (hd0,2) kernel /vmlinuz-2.6.30.8-64.fc11.i586 ro root=/dev/mapper/vg_johnsfedor$ initrd /initrd-2.6.30.8-64.fc11.i586.img title Fedora (2.6.29.4-167.fc11.i586) root (hd0,2) kernel /vmlinuz-2.6.29.4-167.fc11.i586 ro root=/dev/mapper/vg_johnsfedo$ initrd /initrd-2.6.29.4-167.fc11.i586.img title Vista rootnoverify (hd0,0) chainloader +1 title Vista-backup rootnoverify (hd0,1) chainloader +1

See simple right? And then I just had to install the usual suspects such as ; flash-plugin, vlc, eclipse, netbeans, mysql, apache2, php5, nctuns and so on. However the thing with Fedora is that all of this is very easy. So if you have any problems with installing Fedora 11 on a Compaq Presario CQ50 just yell!

The site has been updated

John Roach — Tue, 20 Oct 2009 08:52:56 +0000

Yes, at last. Free of Blogger/Google. I won’t be blocked!! Thanks to Turkish blocking sites I have decided to carry EVERYTHING to my OWN host. And voila! What you see is what has happened.

I am using WordPress for people who are wondering and I know the theme is a little dark. But it is simple and I like simple.

And just to wet your appetites I shall post a tech related video.

iRobot’s Shape-Shifting Blob ‘Bot Takes Its First Steps (IEEE News)

John Roach — Wed, 14 Oct 2009 04:42:00 +0000

POSTED BY: Anne-Marie Corley // Tue, October 13, 2009

This is by far one of the coolest and weirdest robot prototypes we at IEEE Spectrum have ever seen.

Meet iRobot’s soft, shape-shifting robot blob. It rolls around and changes shape, and it will be able to squeeze through tiny cracks in a wall when the project is finished.

(Skip the first 1:50 minutes of the video above to see the blob in action.)

Researchers from iRobot and the University of Chicago discussed their palm-sized soft robot, known as a chemical robot, or chembot, at IROS yesterday. It’s “the first demonstration of a completely soft, mobile robot using jamming as an enabling technology,” they write in a paper.

The concept of “jamming skin enabled locomotion” is explained quite nicely in the video. The polymer used for the bot’s stretchy skin is off-the-shelf silicon two-part rubber.

By controlling the parts of the blob that “inflate,” the researchers can make it roll.

The video shows the project as it was about a year ago. The current stage has a bit different design and is moving toward the ability to include sensors or even connect different blobs together, but those details are sketchy.

When asked about the usefulness of such a bot, iRobot researcher Annan Mozeika promptly answered, “to squeeze into small holes.” And who wants to do that? DARPA, of course. End of questions.

This is how we will look to aliens (do they even exist?)

John Roach — Fri, 18 Sep 2009 07:13:00 +0000

Quantum Chip Helps Crack Code (IEEE News)

John Roach — Fri, 11 Sep 2009 07:02:00 +0000

BY ANNE-MARIE CORLEY // SEPTEMBER 2009

Photo: Jonathan Matthews/University of Bristol

3 September 2009—Modern cryptography relies on the extreme difficulty computers have in factoring huge numbers, but an algorithm that works only on a quantum computer finds factors easily. Today in Science, researchers at the University of Bristol, in England, report the first factoring using this method—called Shor’s algorithm—on a chip-scale quantum computer, bringing the field a tiny step closer to realizing practical quantum computation and code cracking.

Quantum computers are based on the quantum bit, or qubit. A bit in an ordinary computer can be either a 1 or a 0, but a qubit can be 1, 0, or a ”superposition” of both at the same time. That makes solving certain problems—like factoring—exponentially faster, because it lets the computer try many more solutions at once. The race is on to find the ideal quantum computer architecture, with qubit contenders that include ions, electrons, superconducting circuits, and in the University of Bristol’s case, photons.

MIT professor Seth Lloyd, who has been researching quantum computing and communication systems since the early 1990s, says that ”optical methods [using photons] have a long way to go before being useful.” But, Lloyd adds, the Bristol experiment demonstrates that the components for optical quantum computing can be squeezed onto a chip, which is an important step forward.

Shor’s algorithm was first demonstrated in a computing system based on nuclear magnetic resonance—manipulating molecules in a solution with strong magnetic fields. It was later demonstrated with quantum optical methods but with the use of bulk components like mirrors and beam splitters that take up an unwieldy area of several square meters.

Last year, the Bristol researchers showed they could miniaturize this optical setup, building a quantum photonic circuit on a silicon chip mere millimeters square. They replaced mirrors and beam splitters with waveguides that weave their way around the chip and interact to split, reflect, and transmit light through the circuit. They then injected photons into the waveguides to act as their qubits.

Now they’ve put their circuit to work: Using four photons that pass through a sequence of quantum logic gates, the optical circuit helped find the prime factors of the number 15. While the researchers showed that it was possible to solve for the factors, the chip itself didn’t just spit out 5 and 3. Instead, it came up with an answer to the ”order-finding routine,” the ”computationally hard” part of Shor’s algorithm that requires a quantum calculation to solve the problem in a reasonable amount of time, according to Jeremy O’Brien, a professor of physics and electrical engineering at the University of Bristol. The researchers then finished the computation using an ordinary computer to finally come up with the correct factors.

Of course, says O’Brien, ”a smart schoolkid could tell you [the answer] in a few seconds.” To be really useful, he says, ”what we’d need is a quantum computer that has millions of qubits, to solve problems that are genuinely hard to solve otherwise.”

That quantum factoring machine is decades away, but in the meantime chip-scale optical architectures like those of the Bristol team could help in applications like quantum key distribution, which guarantees secure communication based on the laws of quantum mechanics rather than on the mathematical difficulty of factoring. Or they could be used to simulate quantum systems in physics experiments, which might require just hundreds of qubits instead of thousands or millions.

Photo: Jonathan Matthews/University of Bristol

”We know 3 times 5 is 15,” says University of Maryland quantum computing expert Christopher Monroe, but this experiment ”has promise for developing something that could tell us the answer to something we don’t know.”

MIT’s Lloyd is not convinced that the technology is scalable. The real trick, he says, will be to develop a self-contained method that measures the photons, reads the results, and finds the factors of huge numbers without dipping back into classical computation or knowing the answer ahead of time. That’s the ”tough technological problem that no one has any idea how to solve,” Lloyd says, although he believes it’s ”not against the laws of physics.”

O’Brien, however, says that only the hard part needs to be done on a quantum computer, which will likely be a highly sophisticated device and in much demand. ”You wouldn’t waste its time with classical computations,” O’Brien says. ”If the other bits are easy, why do them on a quantum computer?”

The Bristol group next aims to build larger, more sophisticated quantum optical circuits, with more waveguides packed on the chip, in addition to more-efficient single-photon generators and detectors. That will push them toward a scaled-up system that might, decades hence, break math-based encryption codes using millions of qubits.

Flexible Inorganic LED Displays ( IEEE News)

John Roach — Fri, 04 Sep 2009 04:22:00 +0000

by John Rogers

Photo: D. Stevenson and C. Conway/Beckman Institute/University of Illinois

21 August 2009—Organic light-emitting diodes, or OLEDs, are seen as the successor to liquid crystal technology for small, pixel-dense displays like the ones in laptops, smartphones, and digital cameras. Conventional inorganic LEDs, which are poised to put incandescent and fluorescent lightbulbs out to pasture, have never been in the race, because the processing techniques used to make them don’t allow scaling down to the resolution required for a pocket-size display.

But a group made up of researchers based in Illinois and Beijing reported yesterday in the online edition of Science that they have developed methods for creating, assembling, and connecting inorganic LEDs on a flexible substrate. This will finally allow the miniaturization of the technology, which beats OLEDs in brightness, energy efficiency, durability, and moisture resistance.

The technology was developed as part of a research project funded by the Ford Motor Co., which envisions many possible automotive applications for thin, flexible lighting systems. Among these are instrumentation gauges that can be placed just about anywhere.

The researchers started by growing a four-layer semiconductor sandwich with all the makings of an inorganic LED. They did this atop a layer of aluminum arsenide which itself coated a gallium arsenide substrate. Using a combination of photolithography, chemical etching, and a proprietary polymer process, they turned the wafer into an array of 100-by-100-micrometer LEDs loosely attached to the gallium arsenide by polymer anchors.

The team then used an automated printing tool composed of a soft rubber stamp with embossed features that act as suction cups. The cups attach to the tops of the LEDs, and when the stamp is peeled away, the polymer anchors break. The stamp then deposits the LEDs on a glass substrate coated with an adhesive strong enough to overcome the suction force.

Photo: D. Stevenson and C. Conway/Beckman Institute/University of Illinois

The researchers say the device can also be printed onto flexible substrates instead of glass to cover objects with curves or corners. Rogers has done pioneering work in making flexible electronic circuits and has founded a firm—Semprius, in Durham, N.C.—to commercialize it.

Displays produced from this printing process are highly efficient, says Rogers, who explains that you can achieve the same brightness and image clarity with a lot less material than that used in OLEDs. The 16-by-16 array the team produced has a total surface area of 325 square millimeters. The LEDs together take up less than 1 percent of that real estate, he says. And the LED devices can be made even smaller than the 100-µm-edged version; the techniques the team used are compatible with devices as small as 10 µm on a side.

However, such small LED sizes do not improve picture quality in any way, because the human eye can’t resolve anything smaller than about 100 µm across, says Rogers. ”This is all about making the devices lighter and cheaper,” he says. As a bonus, such displays would be almost completely transparent—and well suited for another automotive need: inexpensive head-up displays.

And thus man landed on the moon…

John Roach — Thu, 16 Jul 2009 11:59:00 +0000

I hope this video makes you remember what it was like to explore an unknown place.

Visit msnbc.com for Breaking News, World News, and News about the Economy

Analysis of openSUSE 11.1

John Roach — Sat, 20 Jun 2009 06:59:00 +0000

Hi there. It has been some time since I wrote my own news. The reason is that lately IEEE has had these great articles that I wanted to share with you. Hoped you like them. Now back to business.

I have for long been a fan of Fedora due to its openness and available packets for almost everything and moreover flexibility of RedHat helped me through the deadly marshes of Linux world. However Fedora lacked something. That something was user friendliness. True it does have community friendliness but it lacks the friendliness which new users who have no experience with linux need. I new user to Linux must not be chocked to death with driver problems or repository clashes and dual-boot bugs.

OpenSUSE has many pros but many out-of-the-box bugs too. Let’s start from the installation.

Installation : So far this was the easiest installation ever. I just emptied a partition on my windows drive and simply installed openSUSE within it. The dual-boot settings was all done automatically. For this openSUSE gets 50 points!!

First Boot : (Driver Problems) It seems that openSUSE has the same driver problems as Fedora. The moment I installed openSUSE the video card was not able to work properly (NVidia 6600 GT or TD don’t remember ) I got this weird screen with lots of bright colors. The problem was resolved by taking the following steps ;

Step1: Reboot machine and write 3 at the end of the boot line in the boot menu.
Step2: In command line (init 3) write ” zypper ref && zypper up ” and update your system.
Step3: After update write ” zypper ar http://download.nvidia.com/opensuse/11.1/ ”
Step4: Write ” zypper install x11-video-nvidiaG02 nvidia-gfxG02-kmp-KERNEL ” where KERNEL is your supposed kernel name which you can learn from entering the following command ” uname -a ”
Step5: Reboot your system and cross your fingers.

By taking these five simple steps you will now be able to boot openSUSE.

Playing Around: As you can understand instead of YUM in Fedora openSUSE uses ZYPPER which is kind of funny name for package handler. The user interface is … well… different really… it’s almost like XP. ( I am using gnome… just couldn’t get used to KDE ) And that’s about it… If I were to give a windows user a Linux and had to choose between openSUSE and Fedora I would probably give them an openSUSE. However openSUSE lacks the Fedora repo’s and such…

Hope you guys liked this peace.
I would like to hear more from you!

The Universal Handset

John Roach — Thu, 11 Jun 2009 07:05:00 +0000

BY PETER KOCH, RAMJEE PRASAD // APRIL 2009

Time was when most radio sets had no software at all, and those that had any didn’t do much with it. But Joseph Mitola III, an engineer working for a company called Eâ¿¿Systems (now part of Raytheon), envisioned something very different—a mostly digital radio that could be reconfigured in fundamental ways just by changing the code running on it. In a remarkably prescient article he wrote in 1992 for the IEEE National Telesystems Conference, he dubbed it software-defined radio (SDR).

A few short years later, Mitola’s vision became reality. The mid-1990s saw the advent of military radio systems in which software controlled most of the signal processing digitally, enabling one set of electronics to work on many different frequencies and communications protocols. The first example was the U.S. military’s Speakeasy radio, which allowed units from different branches of the armed forces to communicate effectively for the first time. But the technology was costly and rather unwieldy—the first design took up racks that only a large vehicle could carry around.

In the new millennium, SDR has spread from the battlefield to the commercial arena. Wireless service providers, in particular, have begun using it in the transceivers in cellphone base stations, allowing the same hardware to handle different cellular protocols. Next, SDR will spread to sets that fit in the palm of your hand.

That will come none too soon. Today’s wireless mix is an often-turbulent alphabet soup of communication schemes: BGAN (Broadband Global Area Network), BT (Bluetooth), DECT (Digital Enhanced Cordless Telecommunication), EDGE (Enhanced Data Rates for GSM Evolution), GPRS (General Packet Radio Service), GSM (Global System for Mobile communication), IMT-A (International Mobile Telecommunications–Advanced), UMTS (Universal Mobile Telecommunications System), WiBro (Wireless Broadband), Wiâ¿¿Fi, WiMax (Worldwide Interoperability for Microwave Access), and more. A mobile software radio that could communicate in all of these ways would, of course, be invaluable.

Up until now, SDR technology worked only in applications that didn’t need to be small in size or frugal in power consumption. New technology should, however, overcome these constraints. Indeed, within

the next year or so, you can expect to see people mothballing their old cellphones in favor of new software-defined handsets. By 2015, the transition should be nearly complete.

The first software-enabled sets to crawl out of the primordial ooze of traditional analog radio were modest affairs ”Evolutionary Developments” (pdf)]. They used embedded computers only to change the output level of the RF amplifier or to shift between individual RF front ends so that one unit could cover multiple bands.

In some of today’s radios, software—often with the aid of digital hardware accelerators—does far more: It determines everything that happens to the signal after it’s converted from RF to lower frequencies and before it’s put in a form that’s suitable for your ears. In these radios, only the RF front end and the amplifier that powers the speaker still use analog components.

The next era in SDR evolution will see what some call the ideal software radio or true software radio, in which the filtering and conversion from RF to lower frequencies that’s normally accomplished in the radio’s front end will be done digitally using the appropriate software—a strategy that requires moving the analog-to-digital converter (ADC) much closer to the antenna. These radios will still require a low-noise RF amplifier, though, because it’s hard to imagine any ADC being able to pick up the micro- or even nanovolt signals generated in the antenna.

In the progression to that ideal radio, you’ll probably notice that cellphones, mobile TV sets, GPS equipment, satellite phones, PDAs, digital music players, game consoles, and their kin will begin to look less and less distinct. As with the beaks of the duck and the platypus, the evolution of such gadgetry will converge toward the most functional form—in this case a small wireless unit that allows its user always to stay connected, from anywhere and for any type of content or use.

Designing such universal gizmos will be tough, of course. Perhaps the highest hurdle will be engineering the antenna, the size of which normally depends on the frequency of operation. Indeed, it’s very difficult to make a radio with an antenna that is not a significant fraction of a wavelength in size. This dictate of physics introduces a fundamental problem, because you’d ideally like a single compact antenna to cover everything from FM reception, at roughly 100 megahertz, to satellite- and personal-network communications, which operate in the few-gigahertz range.

To cover such a large chunk of spectrum, you’d probably need a combination of something quite short, likely built into the unit’s printed-circuit board, and something relatively long, such as the wire that connects with the user’s earphones. But even if the frequency span isn’t so great, designers probably won’t be satisfied with just one antenna: RF engineers are quickly moving toward using multiple antennas, even for single-frequency operation. This strategy—known as multiple-input, multiple-output, or MIMO—allows for more reliable links and higher data rates. For example, IEEE 802.11n networking gear uses multiple antennas to communicate at about five times the speed of previous versions of Wi-Fi.

You can understand how MIMO works, at least in broad terms, with a simple thought experiment. Suppose you set up a transmitter with a single antenna and then move a receiver, also with a single antenna, far enough away for the reception to fade in and out once in a while. Such problems arise because the transmitted signal takes multiple routes to the receiver—some of it perhaps bouncing off a passing car, other parts reflecting off the steel beams of the building where the receiver is located. When the difference in length between two paths is half a wavelength (or three halves, or five halves, and so forth), the two waves will interfere destructively, clobbering the signal.

MIMO sidesteps that pitfall by multiplying the number of possible paths between transmitter and receiver. If the signal passed from one transmitting antenna to one receiving antenna fades, the signal from a different pair should still come in loud and clear, taking advantage of a phenomenon known to radio designers as transmit diversity.

Throw in some serious number crunching to process the digitized signals and you can achieve extraordinarily high data rates. Researchers at NTT DoCoMo, in Japan, which is developing such systems for 4G mobile communications, have managed 5 gigabits per second. And this wasn’t just in a controlled laboratory setting; they achieved this rate outdoors, albeit with the receiver moving no faster than a swift walking pace (doing the same while traveling down the highway would be much more difficult). Impressive results with MIMO and other advanced antenna systems are also coming out of Stanford’s Information Systems Laboratory, MIT’s Lincoln Laboratory, and the Center for TeleInfrastructure at Aalborg University, in Denmark.

Another tricky issue for the makers of SDR handsets is designing the transmitter’s power amplifier so that it can operate over a broad range of frequencies without mangling the signal. The challenge is not so great for FM transmission, but for communication schemes that require the amplitude of the wave to be manipulated, things can rapidly go awry.

Avoiding problems in such cases typically requires some kind of feedback mechanism. You can, for example, sample the output of the power amplifier and convert this RF signal to lower frequencies, which you can then compare with the signals used to modulate the amplifier. You can then compensate for any error you find by digitally adding the reverse distortion to the input signal. Among the leading manufacturers of such designs are RF Micro Devices, in Greensboro, N.C.; Acco Semiconductor, in Saint-Germain-en-Laye, France; and Axiom MicroDevices, in Irvine, Calif.

Another challenge for SDR designers is making much faster ADCs. To avoid ”aliasing”—the effect that makes rapidly spinning wagon wheels in old Westerns look as though they’re turning slowly, or even backward—the ADC must sample the signal at a rate at least twice that of the highest-frequency component, and this may be quite high. The upcoming 4G technologies, for example, are expected to operate in the vicinity of 3.5 gigahertz, which means you’d need to take 7 billion samples per second—more than 10 times as fast as what today’s best ADCs of sufficient resolution can manage.

Many SDR researchers consider this to be among the toughest obstacles ahead—not only because they must up the sampling rate so much but also because they’ll simultaneously need to make significant improvements in the signal-to-noise ratio, power consumption, and physical size of this circuitry. Typically, you can better one of these parameters only by making trade-offs with the others. So achieving gains on all fronts at once is going to be extremely difficult.

There is, however, a strategy that might allow direct conversion of RF in the not-so-distant future: purposeful subsampling. The trick here is to arrange the sampling frequency of the ADC so that the inevitable aliasing that occurs works to your advantage. In one step, the operation both digitizes the RF signal and converts it to a lower frequency. This may seem a bit magical, but it’s not so hard to understand. Just imagine the RF signal as one of those rapidly spinning wagon wheels. Adjust the frame rate of the motion-picture camera appropriately and your captured version of this wheel will turn at whatever lower frequency you want [see ”Aliasing Harnessed”].

Astute readers might notice that the difficulties we’ve outlined so far all involve hardware. Software-defined handsets will have some challenging software, too. It’ll manage the modulation, demodulation, encoding, decoding, encryption, and decryption, as well as the packing and unpacking of the data needed for the communications protocol employed—all computationally intensive tasks. What’s the best kind of microprocessor for such heavy lifting?

Most SDR designers struggling with that question instinctively fixate on the MIPS rate—how many million instructions per second the processor can execute. That’s because it must carry out a huge number of arithmetic operations—largely multiplications and additions—to massage the digitized signal. Specialized digital signal processors (DSPs) are usually the best chips for such things, but they may not be the only solution for SDR handsets. The reason is that these radios must do other kinds of signal processing, too.

In particular, SDR handsets need to detect and correct errors in the received digital bit stream, and the algorithms for that consist less of multiplications and additions than of ”if-then-else” statements. Those branching operations are better done by a general-purpose processor, which would normally also be assigned the tasks of running the unit’s real-time operating system, keyboard, and display. So a software-defined handset will need to have such a chip around anyway.

A general-purpose processor will also be required to host the software interfaces that connect different applications with the underlying hardware. In the near term at least, that ”middleware” is likely to conform to the rules laid out in the U.S. military’s Software Communications Architecture, an object-oriented computing framework that has become the de facto standard for software radios intended for combat use.

Designers of future SDR handsets will revel in the flexibility afforded by having the software control so much of the signal processing. And designers will no doubt want as much of the set’s hardware as possible to be reconfigurable—that is, they’ll want software to do not only signal processing but also be able to switch between different antennas and RF front ends. Such capability would allow you to turn a cellphone into a satellite-radio receiver, say, at the touch of a button.

While the technology for accomplishing this has been around for years, until now it’s been too bulky and power hungry to be used in handsets. But consumers are now on the verge of enjoying the fruits of this approach, implemented with modest amounts of power and in very small packages. In February 2008, BitWave Semiconductor, of Lowell, Mass., announced its BW 1102 Softransceiver RFIC, a chip intended to bring SDR to both cellphones and femtocells (small wireless base stations that can be set up in a home or business to improve cellular coverage indoors). The BW 1102 is a single complementary metal-oxide-semiconductor integrated circuit containing a transceiver that supports a variety of wireless protocols and can operate anywhere on the spectrum from 700 MHz to 3.8 GHz.

Suppose, however, that you are a radio designer and want more than BitWave’s chip can handle, such as the ability to receive FM broadcasts—and maybe even transmit on FM, too, so that you can play your favorite MP3 files on your car radio. How hard would it be to create the perfect IC for that? Hard indeed, it turns out, and that’s why BitWave still has essentially no competitors.

But let’s say you’re keen to try. You might start by estimating the allowable execution time for each of the radio’s intended functions and its power consumption, physical size, and other properties, including the frequency bands to be covered. Based on that assessment, you’d decide how to divide the overall system into hardware and software. Although this exercise isn’t trivial, tools for hardware-software codesign are available.

Now comes the more difficult job: You’ve got to come up with detailed designs for each piece. Fortunately, you won’t have to do that from scratch. Suitable designs for at least some of the larger building blocks—a DSP here, a general-purpose processor there—should be possible to find and license. After the hardware has been pinned down, you’ll need to pull together the software to run it, which itself should keep you and your team busy for a large number of programmer-years.

The next challenge is to verify that your radio works correctly. Unfortunately, even state-of-the-art simulation tools aren’t guaranteed to show system performance properly—and subtle errors here might be lethal for your product. Worse, many of the expected mobile services may be safety critical, so a tiny slip-up could be a literal killer, too.

One way to address this uncertainty is to go a step further than simulation: You can prototype the digital portion of your newly designed SDR system using one or more field-programmable gate arrays (FPGAs), integrated circuits that contain a vast number of logic blocks and potential interconnections. These devices can be configured after their manufacture to serve almost any purpose, constituting entire systems on a chip.

The problem with FPGAs for production is that they are the energy hogs of the semiconductor world, lacking the power-management features of their hardwired counterparts. Moreover, FPGAs suffer from the integrated-circuit equivalent of suburban sprawl, taking up a relatively large area on a silicon wafer. They are also expensive, which helps to explain why we haven’t seen FPGAs being used to manufacture SDR handsets—at least not yet. A few researchers are exploring low-power FPGA technologies, so it’s not out of the question that they could one day serve for high-volume production of handsets.

In the meantime, FPGAs remain a convenient way to build and test SDR prototypes. Among the most interesting examples of this is the Berkeley Emulation Engine 2 (BEE2) project at the University of California, Berkeley. This test-bed setup consists of five high-performance FPGAs, which with proper programming can be turned into various next-generation SDR systems. Another example of this approach is the SDRâ¿¿based design effort at San Diego State University, which became widely known through a 2007 article in DSP Magazine titled ”How to Pack a Room of Analog FM Modulators Into a Xilinx FPGA.”

No doubt, many people are waiting for the day when they’ll carry just one handheld gadget they can instantly switch from cellphone mode to that of a satellite radio receiver, or from a wireless Web browser to a mobile TV set; indeed, their handset might carry out all of these functions at once. Others, including the world’s many technophobes, might be less enthusiastic about such a prospect. But SDR technology offers something for them, too—the possibility that their wireless equipment will eventually become smart enough to adapt to its communications environment all by itself.

A radio intelligent enough to reconfigure itself—perhaps by detecting free spectrum and switching its frequency of operation to claim it—would make wireless services cheaper and more reliable for their users, most of whom will not even be aware that such marvelous things are going on under the hood. As with SDR, this is a concept that Mitola promoted early on, in a 1999 article he wrote with Gerald Maguire Jr., of the Royal Institute of Technology, in Stockholm. They called it cognitive radio.

Ah, to have a radio that not only switches function on demand but also configures itself into the most effective form possible without its user even knowing it. Now that will be a truly universal handset.

About the Author

PETER KOCH and RAMJEE PRASAD, who explain how software-defined radio will soon transform cellphones in ”The Universal Handset”, are professors at Aalborg University, in Denmark. Koch works at the university’s Center for Software Defined Radio and also operates an amateur radio station for fun. He’s shooting to reach other hams in all parts of the world. ”I’m not there yet,” he says. Prasad, an IEEE Fellow, heads the university’s Center for TeleInfrastructure. He, too, enjoys making international contacts, but rather than doing so wirelessly, he regularly travels to the far corners of the world.