Steve Perlman’s team is testing a new kind of wireless network that he says can fit thousands of times more data into the same amount of radio spectrum as a conventional one. The approach is known as DIDO, for distributed input distributed output, and is currently being tested around Palo Alto, California, and in rural Texas.
All wireless systems have access to a fixed portion of radio spectrum, and hence a fixed capacity for transmitting data, known as bandwidth. Today’s wireless networks, like those that serve data to cell phones, share that bandwidth among the gadgets connected to the network. The more devices that connect, the smaller the slice for any individual user, and the slower the download speeds. By constrast, a DIDO system, says Perlman, “can offer the full bandwidth available to the network to every user.”
If a DIDO network was rolled out to supplement today’s cellular ones, it would use many small towers rather than the large ones typically used now. “You would rely on lots of little towers scattered about that will work together to target you with your own signal,” says Perlman. “They could be on light poles, on top of buildings, in businesses.” Those small base stations would be under the control of DIDO servers constantly calculating how to make signals that interfere in just the right way. Those signals could be altered to deal with changing radio conditions and transmitter availability as gadgets moved, even when users were driving.
19 page DIDO white paper – Distributed-Input-Distributed-Output (DIDO) Wireless Technology A New Approach to Multiuser Wireless
DIDO involves intentionally combining signals from multiple transmitters, exploiting interference to create a bubble of crystal-clear reception around every user. Each signal that leaves an individual transmitter is incomprehensible until it encounters, and interferes with, other DIDO signals near a device connected to the network.
This approach removes the need to share bandwidth, says Perlman, because each bubble covers a small area and can occupy all the spectrum available to the network. The size and shape of the bubbles varies depending on the number of antennas broadcasting to a device, says Perlman.
Designing radio signals that will interfere with one another in just the right way takes complex mathematics and careful coordination among the different DIDO transmitters. “The computational requirements are very large, but we solved that by using a cloud server,” says Perlman.
Distributed-Input-Distributed-Output (DIDO) wireless technology is a breakthrough approach that allows each wireless user to use the full data rate1 of shared spectrum simultaneously with all other users, by eliminating interference between users sharing the same spectrum. With conventional wireless technologies the data rate available per user drops as more users share the same spectrum to avoid interference, but with DIDO, the data rate per user remains steady at the full data rate of the spectrum as more users are added.
As a result, DIDO profoundly increases the data capacity of wireless spectrum, while increasing reliability and reducing the cost and complexity of wireless devices. DIDO deployment is far less expensive than conventional commercial wireless deployment, despite having vastly higher capacity and performance, and is able to use consumer Internet infrastructure and indoor access points.
The potential of DIDO is to have unlimited number of simultaneous users, all streaming high-definition video, utilizing the same spectrum that a single user would use with conventional wireless technology, with no degradation in performance, no dead zones, no interference between users, and no reduction in data rate as more users are added.
DIDO works indoor/outdoor for urban/suburban applications at distances of several miles, and for rural applications, DIDO works at distances up to 250 miles. Urban/suburban latency is sub-millisecond.
This paper describes how DIDO is dramatically different than conventional wireless technology, how DIDO works, what we have running so far, and the mind-blowing applications DIDO makes possible.
We do not know of a theoretical limitation to how many users we can add to a DIDO system without a degradation in data rate per user. There certainly will be practical limitations with each era of technology evolution, but we have not yet come close to them. So far, as we’ve increased the number of simultaneous users in the same area to 10 (limited just by the number of hand-built radios we have) we have not seen any degradation in performance. So, while our demonstrated spectral capacity today is 10X the Shannon Limit, we expect we can get to 100X, and are optimistic that 1000X is achievable. But, until we start to see some degradation in performance as we add more users, we will not be able to predict how far it can go.
DIDO is a cloud wireless system. All of the intelligence of the DIDO system is in a DIDO Data Center, which then communicates to all of the users at once through all of the APs at once. So, you can think of the DIDO APs as a vast random array of antennas extending out from the DIDO Data Center for miles, but instead of running long wires from the Data Center to the antennas, DIDO uses the Internet to connect to each DIDO AP, allowing each DIDO AP to be placed anywhere there is an Internet connection, whether indoor or outdoor, much like a Wi-Fi AP could be placed anywhere there is an Internet connection.
With so many users sharing the same spectrum at once, why doesn’t Shannon’s Law result in the reduction of the data rate per user as more users are added?
The reason is Shannon’s Law is not about spectrum data rate limits, it is about channel data rate limits. We are used to thinking of spectrum and a channel as the same thing, because in conventional multiuser wireless system such as Wi-Fi or cellular, when you have a high density of users in the same area (e.g. an apartment building or a cell sector), all the users are sharing the same spectrum and the same channel. So, as you add users, Shannon’s Law applies because they are all sharing the same channel, and it is incidental they are all sharing the same spectrum. The reason techniques like MIMO and beamforming can increase data rate by 3X-4X using the same spectrum is they are able to create a few (perhaps 3 or 4) independent channels in a densely-shared area, and indeed, if the circumstances allow for it, they are able to achieve 3X-4X the Shannon Limit in shared spectrum.
DIDO is a general solution that creates an independent channel for each user, even in densely-shared areas. Since each user has an independent channel, Shannon’s Law does not apply, despite the fact that all users are sharing the same spectrum.
The reason why DIDO channels are independent is very hard to understand the first time you hear it, so let’s start with a different wireless arrangement that is not as general as DIDO, but is easier to comprehend.
Let’s say you had 10 highly directional antennas (e.g. dish antennas) spread out in a line and 10 users spread out in a line parallel to the dish antennas. If each dish antennas is aimed directly at user in the same position in the other line (i.e. all 10 beams are parallel and do not overlap), then there will be 10 beams transmitted to 10 users, and each will be an independent channel that does not interfere with the other channels. Suppose that instead of keeping all 10 beams parallel you pair up the dish antennas and users randomly, so that each dish antenna only points at 1 user, but now the beams are all crossing each other. We still have 10 independent channels because, despite the fact the beams cross each other in space, they do not cross each other where each is received by a user, and as a result do not interfere (e.g. just as theater spotlights that cross in the air, but hit the stage at different points do not interfere). So, in this very specific arrangement, with 10 antennas and 10 users, we can have 10 independent channels in the same area. This tells us the concept of 10 simultaneous channels is physically possible. Unfortunately, in practice with a typical multiuser wireless arrangement, the antennas and users are distributed randomly both among and around each other, with walls and other obstacles all about. Even if we very carefully aim the dish antennas, even trying to bounce the radio signals off walls, we’d find very few completely independent paths between antennas and users, and as a result, in typical wireless networks we can’t come anywhere close to creating 10 independent channels in an area. As a result, users need to share channels and Shannon’s Law applies, limiting the data rate per user as more users are added.
Unlike the dish antenna example, DIDO has almost no restrictions as to the arrangement of antennas and users, walls or other obstacles. In fact, the more widely distributed the DIDO APs and more widely distributed the DIDO users, the better. Hence the name: “Distributed-Input-Distributed-Output”. In wireless parlance, widely distributing both AP and user antennas achieves exceptionally high “diversity”. Diversity makes each antenna “statistically independent” (its signal paths are different than other antenna signal paths), which is how the DIDO Data Center distinguishes each APs signal from those of the many APs that reach a given user. This allows the DIDO Data Center to figure out precisely what waveforms it needs to generate so that all the waveforms sum together into a clean waveform for each user. Each of these clean waveforms is an independent channel.
So, as more users sharing the same spectrum are added to a DIDO network, Shannon’s Law does not apply. Equally importantly, DIDO achieves this goal in a completely general wireless system: APs are located where it is convenient to place them, and users can be located anywhere.
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Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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