This is actually a subset of MIMO, which is already widely used in WiFi and other wireless networks. Thus it will, regrettably, not give access to any additional bandwidth.
The details on the equivalence is in a paper from IEEE Transactions on Antennas and Propagation, titled "Is orbital angular momentum (OAM) based radio communication an unexploited area?"
http://lup.lub.lu.se/luur/download?func=downloadFile&recordOId=2062936&fileOId=2339120
Because the overhead would be prohibitive for a lot of battery-operated applications. The same goes for the size necessary to implement a complete IPv6 stack.
And there are services that can not use IPv6, due to technical reasons: GPS is one example. Emergency beacons is another. Some scientific applications do also need their own frequency allocations. The same goes for the military.
In summary: frequency application strategies are not as simple as the proponents for "open spectrum" assumes. Cognitive radios comes with huge overheads in size and power, and would make a lot of wireless applications we use everyday impossible. (Typical example: remote control car locks.)
Yes, you are correct - it is the same thing as MIMO. Or actually - MIMO is more powerful than this scheme, which only describes a subset of MIMO scenarios.
The real strange thing is why they didn't compare their new capacitive coupling with a classic wired connection between the PA and the antenna. Instead they introduce an additional PA with corresponding power consumption when they test the wired connection.
The difference between the standalone chip antenna, with a maximum size of 1 mm, with the proposed antenna, with an size of 17 mm, is not revolutionary, it is expected due to the very bad efficiency of electrically small antennas.
Yes, it is counterintuitive. And also not what is actually claimed in the paper.
In the paper three designs are compared:
(1) One with only an antenna on chip. That is, an antenna on the actual chip, with a size of 1x0.5 mm. Draws 3.3 mW, "range" 1m. ("Range" is a very strange measure in RF design...)
(2) The same chip but without the on-chip antenna. Instead the power is coupled to an additional PA-amplifier, and an external small folded dipole antenna: Size about 16x10 mm. Draws 38 mW, "Range" 75 m.
(3) The same chip withou the PA, with the on-chip antenna coupling to an external patch antenna of size 17x17 mm. Draws 3.3 mW, "Range" 24 m.
In summary: Nice engineering work, but no conclusions can be drawn, as it is very much a case of apples and oranges. (No constant TX power, No constant size, Not very much constant between the designs at all.)
And a classic mobile phone does not use an on-chip antenna at all. So this design will not give any benefit to your iPhone or Blackberry etc.
You can not get any gain in an on-chip antenna at this frequencies: it is to small. He is comparing the use of only an on-chip antenna, which is never used in mobile phones, with the use of a coupled external, somewhat bigger, antenna on a ceramic substrate. Not at all suprising that he gets a better performance with the latter, as it is bigger. He would get even better performance with a classic mobile phone antenna, though.
I.e. This will not revolutionize the battery life of your iPhone or Blackberry. The losses in the coupling between the integrated PA and the antenna are very small (if we disregard detuning due to human proximity effects. Which is another story, and which is not influenced at all by the design in question.)
The comparison between two different antennas at different powers is not very good science - it is somewhat suprising it got published. (But it is only at a small conference, so it is not that surprising.)
Minor nitpick: 2.4 GHz is not the frequency of maximum aborbance of water. The frequency of the maximum is temperature dependent, and the absorbance peak is very broad. Thus there is no need to use any special frequency. 2.4 GHz is used in microwave ovens due to that it was free to use, being an ISM band, and that the penetration depth is useful for cooking.
I am referring to the actual paper. And no, the authors do not give any rational for the values. (And I only use them as an illustration of the quality of the statistical analysis in the paper.)
If the umbers used as limits were standard objectively deduced from the data, why is that then not mentioned in the article (ie. the research article, not the news one.)
The risk of getting this kind of tumor is about 1 in 100 000 (according to the article). So, with a risk increase of 50 %, you would get 3 tumors per year in 200 000 people using cell phones, which would fall to 2 tumors per year if they all stopped using them. (And, AFAIK, this kind of tumors are not killing you.)
You beat me to it (see below). They looked at about 140 different things. And the classes are heavily adjusted in order to find anything, like: "Cumulative no. of calls > 5480" and "Cumulative call time (hours) > 1035". And no explanation of why they use these exact values as class limits...
The researchers are fishing. They investigate if there is an increased risk based on different parameters. All these investigation are done with a confidence level of 95%, ie. one out of twenty results may show an increased risk without there being one, just because of statistical fluctuations. As they are investigating about 140 different parameters, there is an expectation of finding 7 "false" instances of increased risk. They found 6...
(And no, medical doctors, even researchers, are not very good at statistical theory. Quite the opposite. The same goes for the reviewers of certain journals.)
Yes, there are RF-ID tags that can be read at long distances. One example is the cited one with a range of 450 feet. That requires a tag, http://www.iautomate.com/t800.html, which is 85x70x9 mm big and requires a new battery every 5 years. Hardly something you easily conceal in a new sweather och a pair of shoes.
There exists two types of RF-ID tags: passive and active. Passive are small and cheap, and have very short read ranges (inches). Active a large and bulky, and requires batteries. But these can achieve ranges in the hundreds of feet.
You are still assuming that "data" implies a need to maximise the bandwidth available to the user- a lot of applications does not have this need, and would for example benefit from an extended range instead.
You make a lot of assumptions in this argument. Voice today is essentially data - it is digitized information being transferred. Data service quality does not need to be bandwidth limited - SMS is an example of data transfer of fixed bandwidth that could benefit from larger cells. The interference you are talking about is the reason why lower frequencies gives larger cells - with larger cells you have exact the same situation with 700 MHz and 2.45 GHz. Perhaps you are alluding to the measure : bits/second/Hz/square km? If we are trying to optimise the amount of data being transferred per area, we should go to higher carrier frequencies - thus the push for the 60 GHz band.
The problem with cognitive radio is to determine if a part of the spectrum is really empty. If you do this by listening before broadcasting, you will need to have a reciver and antenna that are as good as the best one that you may interfere with. And that is a big problem: in a totally open spectrum scenario, the best antenna is a 70 meter dish listening to tranmsissions from mars, and the reciever is big, powerhungry and liquid-cooled. A less extreme example is the GPS-signals, which are really hard to find if you do not know what you are looking for. A simple, cheap and low-power reciever, such as the one you want in a laptop, will have no chance of detecting these transmission. Which gives that we need some kind of frequency allocation, and some kind of regulation. (Cognitive radio is still an interesting concept, but the hidden node problem seems to be very hard to solve...)
There is this stupid little thing called physics - it is quite interesting at times, you should give it a try! (To have a led at the cornea of the eye give an image on the retina is not possible - and to compare this with a common LCD-display is uninformed. And adaptive control is quite effective at times, but there are limits to what it can do. Fundamental limits, that is.)
The optic nerve does not exit at the dead center of the eye; the blind spot, where it connects, is to the side of the center. But the center of the eye has the highest concentration of cones, which gives us colour vision. To the sides the rods are more common, these have better sensitivity, but are only registering the amount of illumination, not the colour. Thus an astronomer who is searching for faint objects in the sky is better of looking to the side of the object, using the rods of the retina, than trying to see the objects in colour with the cones, as they are less sensitive to light.
And exactly what is the difference between using MIMO tech, and using MIMO tech with phased arrays? Are you only proposing that WiMax should have lager arrays, or do you propose that there is some fundamental difference in implementation?
I am not sure what your last point is: If you implement full MIMO, you are already using all the spatial multiplexing available in the channel (up to the limitation set by the actual number of antennas used. Also mark that the channel will be dependent on the antenna configurations.) You can not put phased arrays on top of this, as the MIMO is a superset of phased arrays: a fully implemented MIMO is actually better than a phased array (the latter term which is commonly used for deterministic beam steering and nulling).
First part of your post sounds interesting, do you have any reference? (I can't remember reading anything about it in Kandel och Purves, but it is a couple of years since I read them.)
And even so your analogy with the eyes are strained, keep in mind that the eyes are "antennas" with an approximate size of 30000 times the wavelength, it is this very large size which gives them so high directivity. At 2.45 GHz this would equal an antenna array with a diameter of 3600 meters. This is another reason why I do not think that the analogy is good, it is overoptimistic.
Actually, I am working with "making it work", and that is why I say that human vision and phased arryas has very little to do with each other. Take only the small detail that human vision receptors (analog to the individual antennas in a phased array), is not recording tha phase of the incoming photons, but only the amplitude. That in itself tells something about the huge limitations of the analogy. In fact, the only antenna that the human eye is reminiscent of is a lens antenna, which is commonly not called a phased array. (Not even in wikipedia. And by the way, the wiki article on MIMO is not very good...)
As you insist I must point out that your analogy between the human vision and phased arrays is not a very good one - I would even say that it is a very bad one. If you are comparing multipath noise in the visual spectra with the one at RF-frequncies, you must ever have looked at a impulse response from an indoor channel at all. And one more thing: Phased arrays in themselves does not cope with multipaht, MIMO technology does.
Slashdot Mirror
This is actually a subset of MIMO, which is already widely used in WiFi and other wireless networks. Thus it will, regrettably, not give access to any additional bandwidth. The details on the equivalence is in a paper from IEEE Transactions on Antennas and Propagation, titled "Is orbital angular momentum (OAM) based radio communication an unexploited area?" http://lup.lub.lu.se/luur/download?func=downloadFile&recordOId=2062936&fileOId=2339120
Because the overhead would be prohibitive for a lot of battery-operated applications. The same goes for the size necessary to implement a complete IPv6 stack.
And there are services that can not use IPv6, due to technical reasons: GPS is one example. Emergency beacons is another. Some scientific applications do also need their own frequency allocations. The same goes for the military.
In summary: frequency application strategies are not as simple as the proponents for "open spectrum" assumes. Cognitive radios comes with huge overheads in size and power, and would make a lot of wireless applications we use everyday impossible. (Typical example: remote control car locks.)
Yes, you are correct - it is the same thing as MIMO. Or actually - MIMO is more powerful than this scheme, which only describes a subset of MIMO scenarios.
Is this the game/level-version of Phun? ( http://www.phunland.com/wiki/Home ) Which is a very similar simulation, but instead in a sandbox format.
The real strange thing is why they didn't compare their new capacitive coupling with a classic wired connection between the PA and the antenna. Instead they introduce an additional PA with corresponding power consumption when they test the wired connection.
The difference between the standalone chip antenna, with a maximum size of 1 mm, with the proposed antenna, with an size of 17 mm, is not revolutionary, it is expected due to the very bad efficiency of electrically small antennas.
Yes, it is counterintuitive. And also not what is actually claimed in the paper.
In the paper three designs are compared:
(1) One with only an antenna on chip. That is, an antenna on the actual chip, with a size of 1x0.5 mm. Draws 3.3 mW, "range" 1m.
("Range" is a very strange measure in RF design...) (2) The same chip but without the on-chip antenna. Instead the power is coupled to an additional PA-amplifier, and an external small folded dipole antenna: Size about 16x10 mm. Draws 38 mW, "Range" 75 m. (3) The same chip withou the PA, with the on-chip antenna coupling to an external patch antenna of size 17x17 mm. Draws 3.3 mW, "Range" 24 m.
In summary: Nice engineering work, but no conclusions can be drawn, as it is very much a case of apples and oranges. (No constant TX power, No constant size, Not very much constant between the designs at all.)
And a classic mobile phone does not use an on-chip antenna at all. So this design will not give any benefit to your iPhone or Blackberry etc.
You can not get any gain in an on-chip antenna at this frequencies: it is to small. He is comparing the use of only an on-chip antenna, which is never used in mobile phones, with the use of a coupled external, somewhat bigger, antenna on a ceramic substrate. Not at all suprising that he gets a better performance with the latter, as it is bigger. He would get even better performance with a classic mobile phone antenna, though.
I.e. This will not revolutionize the battery life of your iPhone or Blackberry. The losses in the coupling between the integrated PA and the antenna are very small (if we disregard detuning due to human proximity effects. Which is another story, and which is not influenced at all by the design in question.)
The comparison between two different antennas at different powers is not very good science - it is somewhat suprising it got published. (But it is only at a small conference, so it is not that surprising.)
Minor nitpick: 2.4 GHz is not the frequency of maximum aborbance of water. The frequency of the maximum is temperature dependent, and the absorbance peak is very broad. Thus there is no need to use any special frequency. 2.4 GHz is used in microwave ovens due to that it was free to use, being an ISM band, and that the penetration depth is useful for cooking.
I am referring to the actual paper. And no, the authors do not give any rational for the values. (And I only use them as an illustration of the quality of the statistical analysis in the paper.)
If the umbers used as limits were standard objectively deduced from the data, why is that then not mentioned in the article (ie. the research article, not the news one.)
The risk of getting this kind of tumor is about 1 in 100 000 (according to the article). So, with a risk increase of 50 %, you would get 3 tumors per year in 200 000 people using cell phones, which would fall to 2 tumors per year if they all stopped using them. (And, AFAIK, this kind of tumors are not killing you.)
You beat me to it (see below). They looked at about 140 different things. And the classes are heavily adjusted in order to find anything, like: "Cumulative no. of calls > 5480" and "Cumulative call time (hours) > 1035". And no explanation of why they use these exact values as class limits...
The researchers are fishing. They investigate if there is an increased risk based on different parameters. All these investigation are done with a confidence level of 95%, ie. one out of twenty results may show an increased risk without there being one, just because of statistical fluctuations. As they are investigating about 140 different parameters, there is an expectation of finding 7 "false" instances of increased risk. They found 6...
(And no, medical doctors, even researchers, are not very good at statistical theory. Quite the opposite. The same goes for the reviewers of certain journals.)
Anti-theft sensors commonly used by shops do not use RF-ID tech. They only detect the precense of an active tag, and the tags do not have separate identities. Wikipedia: http://en.wikipedia.org/wiki/Electronic_article_surveillance
Yes, there are RF-ID tags that can be read at long distances. One example is the cited one with a range of 450 feet. That requires a tag, http://www.iautomate.com/t800.html, which is 85x70x9 mm big and requires a new battery every 5 years. Hardly something you easily conceal in a new sweather och a pair of shoes.
There exists two types of RF-ID tags: passive and active. Passive are small and cheap, and have very short read ranges (inches). Active a large and bulky, and requires batteries. But these can achieve ranges in the hundreds of feet.
You are still assuming that "data" implies a need to maximise the bandwidth available to the user- a lot of applications does not have this need, and would for example benefit from an extended range instead.
You make a lot of assumptions in this argument. Voice today is essentially data - it is digitized information being transferred. Data service quality does not need to be bandwidth limited - SMS is an example of data transfer of fixed bandwidth that could benefit from larger cells. The interference you are talking about is the reason why lower frequencies gives larger cells - with larger cells you have exact the same situation with 700 MHz and 2.45 GHz. Perhaps you are alluding to the measure : bits/second/Hz/square km? If we are trying to optimise the amount of data being transferred per area, we should go to higher carrier frequencies - thus the push for the 60 GHz band.
The problem with cognitive radio is to determine if a part of the spectrum is really empty. If you do this by listening before broadcasting, you will need to have a reciver and antenna that are as good as the best one that you may interfere with. And that is a big problem: in a totally open spectrum scenario, the best antenna is a 70 meter dish listening to tranmsissions from mars, and the reciever is big, powerhungry and liquid-cooled. A less extreme example is the GPS-signals, which are really hard to find if you do not know what you are looking for. A simple, cheap and low-power reciever, such as the one you want in a laptop, will have no chance of detecting these transmission. Which gives that we need some kind of frequency allocation, and some kind of regulation.
(Cognitive radio is still an interesting concept, but the hidden node problem seems to be very hard to solve...)
There is this stupid little thing called physics - it is quite interesting at times, you should give it a try! (To have a led at the cornea of the eye give an image on the retina is not possible - and to compare this with a common LCD-display is uninformed. And adaptive control is quite effective at times, but there are limits to what it can do. Fundamental limits, that is.)
The optic nerve does not exit at the dead center of the eye; the blind spot, where it connects, is to the side of the center. But the center of the eye has the highest concentration of cones, which gives us colour vision. To the sides the rods are more common, these have better sensitivity, but are only registering the amount of illumination, not the colour. Thus an astronomer who is searching for faint objects in the sky is better of looking to the side of the object, using the rods of the retina, than trying to see the objects in colour with the cones, as they are less sensitive to light.
And exactly what is the difference between using MIMO tech, and using MIMO tech with phased arrays? Are you only proposing that WiMax should have lager arrays, or do you propose that there is some fundamental difference in implementation?
I am not sure what your last point is: If you implement full MIMO, you are already using all the spatial multiplexing available in the channel (up to the limitation set by the actual number of antennas used. Also mark that the channel will be dependent on the antenna configurations.) You can not put phased arrays on top of this, as the MIMO is a superset of phased arrays: a fully implemented MIMO is actually better than a phased array (the latter term which is commonly used for deterministic beam steering and nulling).
First part of your post sounds interesting, do you have any reference? (I can't remember reading anything about it in Kandel och Purves, but it is a couple of years since I read them.) And even so your analogy with the eyes are strained, keep in mind that the eyes are "antennas" with an approximate size of 30000 times the wavelength, it is this very large size which gives them so high directivity. At 2.45 GHz this would equal an antenna array with a diameter of 3600 meters. This is another reason why I do not think that the analogy is good, it is overoptimistic.
Actually, I am working with "making it work", and that is why I say that human vision and phased arryas has very little to do with each other. Take only the small detail that human vision receptors (analog to the individual antennas in a phased array), is not recording tha phase of the incoming photons, but only the amplitude. That in itself tells something about the huge limitations of the analogy. In fact, the only antenna that the human eye is reminiscent of is a lens antenna, which is commonly not called a phased array. (Not even in wikipedia. And by the way, the wiki article on MIMO is not very good...)
As you insist I must point out that your analogy between the human vision and phased arrays is not a very good one - I would even say that it is a very bad one. If you are comparing multipath noise in the visual spectra with the one at RF-frequncies, you must ever have looked at a impulse response from an indoor channel at all. And one more thing: Phased arrays in themselves does not cope with multipaht, MIMO technology does.