The quality of the medium through which communication occurs, i.e., the wireless channel, is constantly changing. Consider the following figure, courtesy of the Laboratory for Information Technology at Aachen University, which shows the channel quality of a cellular network throughout a rural town in Germany (green=good, red=bad). Reality is actually much worse than this since the channel also fluctuates due to small scale fading.

Digital communication parameters used to construct wireless waveforms (e.g., QAM order, FEC rate, the number of spatial streams, etc.) observe a tradeoff between reliability, e.g., the probability of a dropped call in a voice network, and data rate in terms of the wireless channel quality. Consequently, modern wireless networks get the most “bang for their buck'’ in today’s spectrum limited wireless market through link adaptation where link adaptation is the process of selecting digital communication parameters based on real-time channel quality measurements. Link adaptation allows for joint optimization of reliability and data rate tailored to each application.

Most published research makes link adaptation seem like a straightforward problem.

1. Measure the wireless channel.
2. Extract a link quality metric from the wireless channel.
3. Map the link quality metric to digital communication parameters using a look-up-table or rate/reliability formulas.

Look-up-tables/formulas are created offline through analysis, simulations, or measurements. When I attempted to do this on our IEEE 802.11n prototype, Hydra, I found out that link adaptation in practice can be very difficult. Here are a few of the lessons I learned.

• System nonlinearities make look-up-tables created through analysis or simulations inaccurate.
• Non-Gaussian noise make look-up-tables created through analysis or simulations inaccurate.
• Channel estimation error must be accounted for.
• Look-up-tables based on actual over-the-air measurements result in the most accurate adaptation.
• Look-up-tables based on actual over-the-air measurements for one device may result in inaccurate adaptation if placed on a different wireless device.

After my initial testing I was concerned that it might be difficult to use our prototype, even with significant amplifier backoff to design/evaluate practical link adaptation algorithms. Apparently, however, commercial systems suffer from the same issues. For example, the Roofnet project found that the SNR link quality metric did not consistently reflect the expected reliability of the associated digital communication parameters, even when interference/collisions are not an issue.

Another large problem we discovered is that good link quality metrics for MIMO-OFDM systems just weren’t available. It turns out that analyzing the error rate of practical MIMO-OFDM links is very difficult. Consequently, finding a good, single-dimensional (which is required for look-up-tables) link quality metric that modeled the spatial and frequency selective effects of the channel was also very difficult.

So what do we do? The linear, time-invariant models we have used to create link adaptation rate/reliability expressions or to run link simulations (which may then result in look-up-tables) do not reflect the actual system. One approach is to make our analysis model more complex to include nonlinear and non-Gaussian noise effects. This seemed like a difficult undertaking. Analysis was already difficult with our simplistic linear, time-invariant system and additive Gaussian noise. Using a more complex system model would only lead to more design time for engineers. Moreover, even if we are able to find a good link quality metric, it will likely be multi-dimensional, and look-up-tables aren’t easily created in this case. All of this lead us (Professor Heath and I) to machine learning.

Machine learning algorithms allow systems (in our case the link adaptation algorithm) to learn behavior solely from data observations. Hence, as long as we were able to define an accurate link quality metric and pose the problem correctly, machine learning should be able to discover the relationship between the link quality metric and the reliability of the link. First, we created the multi-dimensional ordered SNR link quality metric based on our new expression of packet error rate in MIMO-OFDM systems. Then, with the help of Professor Caramanis, we validated the efficacy of classification algorithms that exploited this new link quality metric for link adaptation. However, all this work was done using system models. To compensate for unique hardware nonidealities, we needed an online algorithm that tuned link adaptation to each transmit/receive device pair. Consequently, Professor Heath and I designed online classifiers that harness training information on-the-fly. These algorithms constantly observe packets transmitted over channels and improve the link adaptation classifier in real time based on these observations.

For example, see the following figure which shows a plot of throughput and packet error rate for offline and online machine learning in a static wireless channel with our wireless prototype and a packet error rate reliability constraint of 10%. The offline algorithm is not able to tune itself to the unique hardware characteristics of the transmit/receive pair, resulting in lost rate/reliability. The online algorithm, however, discovers the correct digital communication parameters in real-time. There have been other rate adaptation algorithms, notably auto-rate fallback (ARF), which adapt online. Unfortunately, they don’t take advantage of explicit link quality metrics and so cannot adapt well in dynamic channel conditions (see following figure).

The best part of our online learning algorithms for link adaptation is simplicity. The algorithms are installed and we’re done. No complex analysis of the reliability curves. No calibration algorithms to determine amplifier backoff. Additionally, our recent results with support vector machines also show that online learning can be implemented with low memory/processing complexity.

For More Information:

R. C. Daniels and R. W. Heath, Jr., “Online Adaptive Modulation and Coding with Support Vector Machines,” to appear in Proceedings of the IEEE European Wireless Conference, Lucca, Italy, April 2010.

R. C. Daniels and R. W. Heath, Jr, “An Online Learning Framework for Link Adaptation in Wireless Networks,” Proceedings of the Information Theory and Applications Workshop, San Diego, CA, February, 2009.

R. C. Daniels, C. M. Caramanis, and R. W. Heath, Jr, “Adaptation in Convolutionally-Coded MIMO-OFDM Wireless Systems through Supervised Learning and SNR Ordering,” IEEE Transactions on Vehicular Technology, January, 2010.

This is really amazing to me, a trained engineer winning this award. Yes, John Bardeen won two of these, but he was really trained as a physicist. I’m willing to bet money that physicists don’t like this decision.

I really like the first point: “the authors don’t use TeX”. I don’t know why but there seems to be such a correlation but I have seen this time and again.

I like how they use the music analogy. Perhaps the first hopping algorithm was something like “Scott Joplin’s Entertainer” since Bach would be easily recognized by the Germans.

I actually don’t think that the way I got interested in relay selection was the ideal strategy in terms of “finding a good research topic.” Instead, I’ll discuss what I think is a better way of “finding a good research topic.” Note that the following is especially relevant for graduate students researching wireless communications (for the obvious reasons).

It’s fairly common for a new graduate student to be overwhelmed by the plethora of potential research topics. When I was starting work on my masters degree, I wanted to do research involving some aspect of wireless networks, since I felt (wrongly, as it turned out) that all of the good point-to-point problems had already been solved. During the summer of 2004, I worked on beamforming for MIMO ad hoc networks, but that ended up being a major dead end. On a related note, I recently perused my research notebook and found that during January 2006, I was interested in cooperative diversity for OFDM networks (my, how things have changed).

This brings up the key question: how should a new graduate student sort through the morass of potential research topics and come up with a good one? I’ll discuss two potential answers.

One approach is to have your advisor answer this question for you, assuming that you have an advisor. In general, you can assume that your advisor has a strong grasp of the current state of research in wireless communications. This knowledge can help him/her determine a topic for you that is 1) interesting, so you won’t be bored stiff for approximately 5 years and 2) worthy of a Ph.D. dissertation, so you will have made a fundamental contribution of some sort by the time you graduate.

The second approach, which I highly recommend, is to take the initiative. To start off, you should do a significant amount of reading. Survey articles in journals such as the IEEE Communications Magazine and the IEEE Signal Processing Magazine can be valuable starting points for the interested yet relatively inexperienced grad student.

A particularly well-written survey article can provide the reader with a good grasp of “what’s been done” on a topic such as “OFDMA power allocation for relay-based networks” and suggest various open problems that are both interesting and important. When reading through these survey articles, one should also scan the list of references to learn about the key papers (and researchers, so you can bookmark their home pages) in a particular area.

It’s then important to read through these key papers to grasp the nuances of the topic that you’re learning about and ask yourself tough questions along the way. For example, do you understand the (technical) paper that you’re reading? Can you justify all of the authors’ assumptions? Can you re-derive every expression (especially the proofs of key theorems) in the paper? I should note that sometimes papers contain typos/gross errors, so you shouldn’t automatically trust everything you read.

If you want to answer these questions in the affirmative, this is a great opportunity for building your technical background. For example, let’s say that the authors are studying a MIMO wireless system and assume that a two-ring scattering model is being employed. If you don’t know what a two-ring scattering model is, you should obtain a copy of a MIMO textbook such as this one by Paulraj et al. and learn more about channel modeling.

Also, let’s say that you’re reading through this famous paper by Gupta and Kumar, and you’re having trouble deriving some (or all, as this paper is actually quite tricky to understand) of the key results. In this case, you might want to strengthen your graph theory background by taking an appropriate class, such as this one at UT-Austin. You might also want to improve your knowledge of random geometry, and you can check your university library for a helpful book such as this one by Bollobas for more coverage of this advanced topic.

As you read through the key technical papers in the area that you’re learning about, you should think of additional open problems and ask yourself more tough questions. For example, you can ponder something like, “the authors’ assumption of a zero-error feedback channel seems a bit restrictive. From my other reading it’s clear that introducing a channel estimation error at the transmitter would better model a practical system. Maybe I can’t obtain an exact expression for the sum capacity given channel estimation errors, since that seems quite complicated, but can I obtain relatively tight bounds?”

Regardless of the approach that you take in terms of finding a good research topic, it’s crucial that you interact with your advisor during this process. Your advisor, who has worked in either the general area that you’re considering or a related area, can help you determine if the open problem you’re considering is either trivial, worthy of multiple dissertations, or actually reasonable for a dissertation. Note that by adopting the second approach I discussed above, your ability to have meaningful dialogue with your advisor during this process is enhanced. In particular, you can evaluate your advisor’s suggestions and converge on a reasonable topic more quickly; this is especially important if your advisor has not worked in the general area that you’re considering.

That’s all I had to say on this subject, at least for now. I welcome comments, especially from my group-mates on this issue of “finding a good research topic.”

The winning team consisted of Robert C. Daniels, Ketan Mandke, Steven W. Peters, Prof. Scott M. Nettles, and Prof. Robert W. Heath, Jr., and their winning presentation was called “Machine Learning for Physical Layer Link Adaptation in Multiple-Antenna Wireless Networks”. Daniels and Peters are graduate students in the WSIL, which is directed by Prof. Heath. The demo consisted of using simple machine learning techniques to do adaptation in wireless devices using a custom-built IEEE 802.11n physical layer (PHY). Because this PHY uses coded MIMO-OFDM, adaptation is a difficult prospect. The team successfully demonstrated that the devices were learning the channel with no pre-existing knowledge, and could easily adapt to changing conditions. They used the Hydra prototype, which is in continuous development, as the foundation for the demo.

The winning students received a $2500 cash prize kindly donated by the sponsors, ViaSat, Nokia Siemens Networks, The Center for Multimedia Communication, and BBN Technologies.

The work was sponsored in part by NSF and DARPA ITMANET.

- from LTE / LTE-A TSG RAN mailing list

Some people also say “Long Term Employment” or “Life Time Employment.” :)
But my pick is “Love Thy Enemy.” How about you?

First and foremost, our dear Kaibin Huang just successfully defended his dissertation and is on his way to a post-doc at Hong Kong University of Science and Technology. Not only that, but he was awarded the WNCG Student Leadership award. A WSIL member has won this award two of the past three years.

Along the same lines, Takao Inoue is now a Ph.D. Candidate. He joins Chan-Byoung Chae and Caleb Lo as the next in line to graduate.

We also welcomed the well-known Dr. Marios Kountouris as a post-doctoral researcher.

In addition, we had eight journal papers published:

• R. C. Daniels R. W. Heath, Jr., “60 GHz Wireless Communications: Emerging Requirements and Design Recommendations,'’ IEEE Vehicular Technology Magazine, vol. 2, no. 3, pp. 41-50, Sept. 2007. [IEEE Xplore]
• J. G. Andrews, W. Choi, and R. W. Heath, Jr., “Overcoming interference in spatial multiplexing MIMO cellular networks,'’ IEEE Wireless Communications, vol. 14, no. 6, pp. 95-104, Dec. 2007. [IEEE Xplore]
• W. Choi, A. Forenza, J. G. Andrews, and R. W. Heath, Jr., “Opportunistic space division multiple access with beam selection,'’ IEEE Trans. on Communications, vol. 55, no. 12, pp. 2371-2380, Dec. 2007. [IEEE Xplore]
• K. Huang, R. W. Heath, Jr., and J. G. Andrews, “Uplink SDMA with Limited Feedback: Throughput Scaling,'’ EURASIP Journal on Advances in Signal Processing, special issue on MIMO Transmission with Limited Feedback, vol. 2008, Article ID 479357, 17 pages, doi:10.1155/2008/479357, 2008. [EURASIP Website]
• B. Mondal and R. W. Heath, Jr., “A Diversity Guarantee and SNR Performance for Quantized Precoded MIMO Systems,'’ EURASIP Journal on Advances in Signal Processing, special issue on MIMO Transmission with Limited Feedback, vol. 2008, Article ID 594928, 15 pages, doi:10.1155/2008/594928, 2008. [EURASIP Website]
• Kyung Seung Ahn, R. W. Heath, Jr., and H. K. Baik, “Shannon Capacity and Symbol Error Rate of Space-Time Block Codes in MIMO Rayleigh Channels with Channel Estimation Error,'’ IEEE Trans. on Wireless Communications, vol. 7, no. 1, pp. 324-333, Jan. 2008. [IEEE Xplore]
• C. B. Chae, T. Tang, R. W. Heath, Jr., and S. Cho, “MIMO Relaying with Linear Processing for Multiuser Transmission in Fixed Relay Networks,'’ IEEE Trans. on Signal Processing, vol. 56, no. 2, pp. 727-738, Feb. 2008. [IEEE Xplore]
• D. Piazza, N. J. Kirsch, A. Forenza, R. W. Heath, Jr., and K. R. Dandekar, “Design and Evaluation of a Reconfigurable Antenna Array for MIMO Systems,'’ IEEE Trans. on Antennas and Propagation, vol. 56, no. 3, pp. 869-881, Mar. 2008. [IEEE Xplore]

In addition, our fearless leader Prof. Heath, along with Prof. Andrews, won the WNCG Spring 2008 Bocce Ball tournament.

And finally, a long semester of ups and downs concludes with a nice week in the U.S. Virgin Islands for the IEEE Communication Theory Workshop, with Prof. Heath as General Chair.

Please add more here if I forgot something.

News from Washington Post

Note: this news was not posted on April 1st.

Example problem: Let z, l and m be a natural numbers, l less than m. Let p be a prime which appers in the prime factorization of z, e.g. 2 and 3 appear in the prime factorization of 24. The problem is to find out the number of natural numbers between l and m (including l and m) that have p ones in their binary representation.

What makes 60G so interesting for research?
In my opinion there are two primary reasons that 60 GHz has received so much attention recently.

1. There is 7 GHz of unlicensed (free) bandwidth available in the United States alone! Additionally, there is around 5 GHz of unlicensed bandwidth common to Europe, most of Asia, Australia, and North America. This amount of bandwidth is unparalleled at traditional frequencies such as 900 MHz, 1800 MHz, 2450 MHz, and 5000 MHz. 62 MHz of licensed spectrum around the 700 MHz carrier frequency was recently auctioned in the United States netting a total of around 20 billions of dollars. Obviously bandwidth is precious, and when 7 GHz is available, people pay attention.
2. The 60G carrier frequency in fundamentally range limited and presents significant challenges in antenna design, analog circuits, digital processing, and higher (cross) layer design. For this reason the 7 GHz of bandwidth is still relatively unused even though it was opened up over 5 years ago. If operating at 60G was just a matter of ramping up the carrier frequency of current systems, there might not be so much buzz (or money) in 60G research. As communication engineers, we should be licking our chops, because it gives us some unsolved problems we can sink our teeth into. Next, I will elaborate on some of the limitations and design challenges that make 60G so interesting.

60G Challenges
The most obvious limitation of 60G to an engineer is the carrier frequency itself. Physics (via the Friis free space propagation formula) dictates that we lose 20 dB in received power every time we multiply the carrier frequency by 10. That means if I have two systems, one operating at 6 GHz and one operating at 60 GHz, I would have to transmit 20 dB more power in the 60 GHz system to achieve the same performance in a vacuum. Of course we don’t live in a vacuum, and that brings us to two more limitations at 60 GHz: reduced propagation through materials and increased Doppler effects. The ability of electromagnetic waves to penetrate solid objects is a function of the carrier frequency. Measurements have shown that propagation through objects is reduced at 60 GHz, limiting the ability of non-line-of-sight communication. Doppler frequency, which results from mobility of objects around communication devices, is proportional to the carrier frequency. Since the carrier frequency is significantly larger than traditional systems, we will experience much larger Doppler frequencies, which may complicate feedback, channel estimation, and higher layer design. Finally, and perhaps the limitation that encouraged national entities to remove licensing restrictions, 60 GHz wireless transmissions experience Oxygen absorption effects. It turns out that Oxygen resonates at 60 GHz, providing 10-20 dB of signal attenuation per kilometer (see image at right sourced from Marcus Spectrum Solutions).

From a design perspective, the fundamental limitations of the wireless channel are not the only difficulties. 60G antenna design is unique since the antenna dimensions are reduced. Therefore, antenna fabrication will require more expensive milling technology, especially for planar antenna arrays. RF circuits at 60 GHz may also have to discard simplifying lumped element assumptions as wavelengths approach device dimensions. Analog circuit design is complicated for many other reasons including reduced amplifier gain characteristics, reduced power output capabilities for transistors, amplification of frequency instability (phase noise). In general this leads to increased cost in engineering design or the technology implemented.

Current Activity
After the laundry list of limitations and design obstacles presented above you might be thinking to yourself “there’s no point in trying” or “it will never work.” Thankfully, that’s not the consensus of the wireless market. We have seen significant activity in industry recently to try and bring 60 GHz to the consumer in the near future. IEEE 802.16d, the precursor to WiMax, actually considered using frequencies up to 66 GHz. Unfortunately, it quickly became apparent that the above challenges were too much for mobile broadband devices that need to communicate over kilometer distances. As a consequence, all the wireless devices to appear in the near future are targeted for indoor, short range communications. IEEE 802.15.3c is currently constructing a standard for operating wireless personal area networks at 60 GHz. The 3c working group has formally accepted a proposal, an important first step towards actual standardization. 15.3c devices should be seen as a replacement for UWB, which will eventually replace Bluetooth. While, 802.15.3c is addressing a host of applications for high throughput communications, WirelessHD has a single focus. WirelessHD is a consortium of companies that have banded together to create 60G technology for high definiton wireless video streaming. Here is a nice overview of their OFDM-based standard as well as a video summary of a CES 2008 presentation. In the past wireless video streaming was subject to low performance lossy compression or high cost lossless compression. Because of the 60 GHz bandwidth available the wireless industry is hoping to provide low cost, high performance uncompressed video streaming. With 60 GHz it is only a matter of time before all peripheral devices on a personal computer are cable-less and all the wires in your home entertainment center are gone (except for power cables of course). For completeness I want to also mention that ECMA has thrown their hat into the ring and are in the process of building a 60 GHz standard. Since this is the same standardization body that brought us the WiMedia Multiband OFDM standard for UWB, I can only expect they see 60 GHz as an extension for higher rates. In that sense IEEE 802.15.3c and the ECMA standard will be directly competing; whether the two can coexist is unknown at this point.

Design Ideas
If you’d like to know more about how to design the physical layer in view of these challenges or a look at developing technologies that may change the landscape of 60G, please refer to the aforementioned IEEE reference or its preprint here. I think there is copious room for physical layer or higher layer design suggestions that take advantage of 60 GHz with consideration of its challenges. Along with the 60G challenges, we also experience unique advantages such as reduced size constraints on antenna arrays and improved security of communication signals. I’m more than willing to hear your ideas so please contact me with any additional questions.

The MIMO-BC model is as follows. A transmitter with antennas wants to transmit independent information to receivers, where receiver is equipped with antennas . Let be the signal transmitted by the transmitter, then the received signal received by receiver is given by where is a channel matrix and is the additive white Gaussian noise (AWGN) with covariance matrix .

For MIMO-BC, several transmission strategies have been proposed in literature, for example, superposition coding and dirty paper coding. In superposition coding, if is the signal for receiver then is transmitted by the transmitter. Dirty paper coding (DPC) is a technique developed by Costa for single input single output (SISO) AWGN channels when there is an interference signal present at the receiver together with AWGN. We assume the interference signal is known non causally at the transmitter. In this setting Costa showed that the capacity is which is exactly equal to the capacity of AWGN channel without any interference. Thus, DPC is shown to completely eliminate the effect of interference. Using DPC for the MIMO BC, if the signal for the first receiver is , then the signal for receiver is generated using as the interference signal. Similarly, the signal for the receiver is generated using as the interference signals and is transmitted from the transmitter. From now on we consider in this article for simplicity. With ,the rates and , simultaneously achievable for receiver and , are given by and where is the covariance matrix of . Changing the order of coding, i.e. first generating and depending on generating , and We denote the convex hull of all rate vectors achievable with DPC as .

As shown above, finding the achievable rate region of MIMO-BC is easy using different transmission strategies but proving that they are capacity achieving, i.e. rate more than the rate achieved by a particular transmission strategy is not achievable with reliable transmission constraint, is quite difficult. Weingarten et.al. solved this problem in their paper and showed that rates achieved with DPC are optimal for MIMO-BC.

Here we present the argument for symmetric MIMO Broadcast channels from Weingarten et. al.’s paper, where the number of antennas at the transmitter and each receiver are equal. We also only consider two receivers here for simplicity, the general case follows similarly. As before let the received signal at receiver be , where Since we are assuming to be a square matrix, without loss we can multiply the received signal by without changing the capacity. Note that is invertible with probability . This is formally defined as aligned MIMO BC (AMIMO-BC) with Then a transformation of AMIMO-BC is considered, called degraded and aligned MIMO BC (DAMIMO-BC), where with , denotes the covariance matrix. For any two matrices, ,by we mean is a negative semidefinite matrix. It is easy to see that DAMIMO-BC is a degraded BC channel, i.e. one receiver receives less noisy signal than the other. For the degraded BC it is known that superposition coding is optimal, however, it is not known whether Gaussian signaling is optimal or not.

For a single input single output degraded BC (SISO-DBC), where the transmitter and each receiver has a single antenna, Bergmans showed that Gaussian signaling is optimal, however, the proof of Bergmans does not extend to the DAMIMO-BC case.

The optimality of Gaussian signalling is shown as follows. Let be the set of all achievable rate vectors with Gaussian superposition coding for DAMIO-BC and let and be the input covariance matrices achieving and . To show that any rate vector which does not belong to is not achievable, an enhanced DAMIMO-BC is introduced, which is defined as where Clearly, any rate vector achievable on DAMIMO-BC is also achievable on the enhanced DAMIMO-BC, thus the capacity region of DAMIMO-BC is contained inside the capacity region of enhanced DAMIMO-BC.

Next, it is shown that for any DAMIMO-BC there exits an enhanced DAMIMO-BC such that the following properties hold
1. Proportionality: There exits , such that
2. Rate Preservation: The rate vector achievable on enhanced DAMIMO-BC with Gaussian signaling is equal to rate vector obtained with Gaussian signaling for DAMIMO-BC.
Then using the proportionality and rate preservation properties, it is shown that any rate vector which does not belong to is not achievable on the enhanced DAMIMO-BC, using Bergmans proof for SISODBC. An important point to note here is that the Bergmans proof works
because of the proportionality property, which is hard to show for DAMIMO-BC. Since the capacity region of DAMIMO-BC is contained inside the capacity region of enhanced DAMIMO-BC, it follows that any rate vector which does not belong to is not achievable and thus Gaussian signaling is optimal.

Coming back to the original AMIMO-BC, to show that DPC is optimal, the authors show that any rate vector which lies outside the region also lies outside the capacity region. Toward that end, it is shown that for any vector which lies outside the region there exists an enhanced DAMIMO-BC whose capacity region contains the capacity region of AMIMO-BC, but does not contain . Recall that we found out the capacity region of enhanced DAMIMO-BC and showed that Gaussian signaling is optimal, thus it follows that any rate vector which lies outside the region also lies outside of the capacity region of AMIMO-BC and we conclude that DPC is the optimal transmission strategy.

Writing a patent is quite different from writing a paper. A good paper should have a clear derivation of a good algorithm that has never been proven before. It should be academically challenging, mathematically tractable & reversible and conceptually innovative. A good example is Teletar’s MIMO capacity paper, Zheng & Tse’s D-MG tradeoff paper and the GLP paper by Dr. Love and Dr. Heath.

A good patent, however, is quite different. A good patent should have broad (as broad as possible) claims which are important in implementing and making real systems / devices. It focuses on new concepts, new methods and new apparatus that have never been claimed before. A good example of it is a series of handover patents by Qualcomm. Qualcomm’s MAHO (mobile assisted handover) patent and so called “501” (soft handover) patents has the following first claims:
——–
[MAHO] 1. A method of mobile assisted handoff in a cellular communication system comprising a plurality of mobile stations and a land system and a plurality of cells, comprising the steps of:
assigning a mobile station a list of cells to measure, wherein said list is divided into two sections, a steady section and an alternating section;
measuring quality level of each assigned cell;
reporting said quality levels to said land system;
transferring a cell from the alternating section of the list to the steady section of the list when said cell has a quality level higher than one of the cells in the steady section, wherein the cell with the lowest quality level in the steady section is transferred to said alternating section; and
changing said cells listed in said alternating section every predetermined period of time.
[link]

[501] 1. In a cellular telephone system in which a mobile system user and another system user communicate user information signals therebetween via at least one of a plurality of geographically separated cell-sites each defining a respective geographic service area, a system for directing communications between said mobile system user and said another system user via said at least one of said plurality of cell-sites as said mobile system user changes cell-site service areas, comprising:
means for, while said mobile system user is in a service area of one cell-site and communicating user information signals with said another system user via said one cell-site, determining a transition of said mobile system user from said one cell-site service area to a service area of another cell-site, and for providing a handoff request identifying said another cell-site;
means responsive to said handoff request for coupling a communication of said user information signals between said mobile system user and said another system user via said another cell-site while said mobile system user and said another system user continue in communication of said user information signals via said one cell-site such that said mobile system user and said another system user concurrently communicate said user information signals through said one cell-site and said another cell-site; and
means responsive to said coupling of communication of said user information signals between said mobile system user and said another system user via said another cell-site for terminating said communication of said user information signals between said mobile system user and said another system user via said one cell-site with said communication of said user information signals continuing between said mobile system user and said another system user via said another cell-site.
[link]

——–
As you see, MAHO and ‘501’ patents contain almost every possible method for the soft handover (SO) and mobile assisted handover (MAHO). It means that if you build a system with handover algorithms at cell edge, you have to design a system without SO and MAHO, to avoid those patents. You can’t either receive two pilot sequences from two base stations simultaneously, or compare the signal strength at the mobile side between the two. Then, what can you do? Will you pay millions of dollars to the legal owner of it, or try not to use both SO and MAHO?

This is the main reason why the WiMAX system uses only hard handover (HO) and why the cell edge performance of that system doesn’t quite good. Another bad new is that even SO and MAHO was flied in 1992 and 1994 respectively (the patent right is valid for 15 years) there are tons of patents which covers another aspect of SO and MAHO. It will be the same in CDMA, LDPC, and probably MIMO.

As explained above, a well-written patent influence on the whole system design. In addition, it presents a huge amount of money to the legal owner (usually a company) and to the inventor (as some form of incentives). For example, Samsung pays about several hundred million dollars to Qualcomm as the CDMA patent right PER YEAR. And when they make a cell phone, they must use Qualcomm’s MSM chip and pay 5.25% - 5.75% of whole retail price as a royalty. Samsung makes at least 100 million cellphones per year.. imagine the amount of money that the CDMA patent makes. Yes, it is quite huge, and a little part of it (which is given to the inventor) is also huge.

The reason that I am writing this article is not to debase the importance of writing a good paper. I think it is one of the most important things to do as a grad student. (Especially the best paper award is a life-long honor. Isn’t it, Kaibin, Ramya, Chan-Byoung?) But it could be better, if you think about filing a patent for your brilliant idea BEFORE you submit it as a paper. (Usually if a thing is already presented and published before, it can’t be the claim of a patent.) You could be a millionaire, or if not so, there is nothing to lose.

I think a good patent may not guarantees a good paper. But a good paper may guarantees a good patent, because the patent can scale down the novel idea in the paper into a practical method and apparatus. One good example is the Alamouti Code. S. Alamouti and V. Tarokh have filed a patent (US 6185258) in Sep. 16, 1997, just before they submit the famous Alamoti code paper.
——–
[Alamoti] 1. An arrangement comprising:
a coder responsive to incoming symbols, forming a set of channel symbols that incorporate redundancy, where the coder employs replications and, at least for some of the channel symbols, forms a negative of an incoming symbol, forms a complex conjugate of an incoming symbol, or forms a negative complex conjugate of an incoming symbol; and
an output stage that applies said channel symbols to at least one transmitter antenna to form at least two distinct channels over a transmission medium.
[link]

——–

As you see in the first claim above, technically any diversity based STBC may infringe their right. It is really terrifying. And it is more terrifying if I can find a patent that has a claim like this: “a device that uses multiple transmit antennas and multiple receive antennas for communication.” It will be all MIMO companies’ nightmare.

The contest receives about 900 submissions every year in fields like including signal processing, analog circuit design, communications and networking, computer science, computer engineering, mechanical engineering, material science and process, physical devices, and physical science. Only six students are awarded the Gold prize annually, and thirty four graduate students share the Silver, Bronze and honor prizes.  There was only one Gold prize winner in the communications & networking area in the last five years.

I’ve never been awarded this kind of big prize in my life. Anyway, I will treat you guys soon.

I cannot say that I fully follow the V2V activities, but the following news caught my attention which seems to indicate that there is a strong movement towards V2V communication and ITS in Japan.

On Feb. 4, 2008, Denso announced the beginning of Vehicle-to-Vehicle communication tests on public roads in Japan (see press release here). It uses 669 - 679 MHz UHF and 5.8GHz band DSRC. The V2V communication is apparently part of the Japanese Ministry of Internal Affairs and Communications’ initiative “Ubiquitous ITS”, which includes digital video broadcast (or VICS, vehicle information and communication system), 60-76GHz mm-wave sensor application, cellular service, short range applications (expressway tollgates, DSRC, wireless service transaction, etc).

The reason for using 669-679MHz above is only to avoid interference with the TV broadcast in the 700MHz band, of which 715-725MHz is expected to open for ITS use in 2011 when the analog TV broadcast goes off air in the 700MHz band.

Some interesting areas of ITS are identified here at the ITS Japan website.Traditional wireless systems (cellular, WiFi, etc) has always had a  clear demand: cellular service to provide bidirectional voice services, and WiFi to provide fast download and so-so upload. For ITS, at least to me, it is not clear what kind of data traffics are needed, that is to say, what type of wireless technologies should be used to support the service. Look at it another way, this area is wide open with possible applications, technologies to support it, and perhaps new business models.

So I thought it would be interesting to throw out a question: What can we do in ITS?

Does MIMO enable certain applications? Or will new applications drive towards new technology?

Some links for further reading:

• US DoT ITS page
• ITS of America
• ITS Japan
• ERTICO: ITS Europe

For a preliminary solver, check out this link.

‘Antenna design for cellular systems’ is a very broad and generic term. I would like to point out here that antenna design requirements and capabilities for base stations and mobile terminals are very different. Let us start with the requirements of a base station antenna. First of all, it needs to be directional, i.e. the antenna should have a high gain in the direction facing cellular sector being illuminated, as shown in Fig. 1(a). Secondly, the major beam of the antenna should not be parallel to the ground. It should be tilted down slightly to ensure that the users on the ground get coverage (see Fig. 1(b)). The third requirement deals with the space occupied by a base station antenna. It is widely assumed that we can afford to have more antenna elements, larger inter-element spacing between the elements, and broadly speaking, larger antenna elements as compared to the receiver (mobile terminal). However, this is not completely true. As cellular service providers and base station antenna manufacturers will tell you, it is very expensive to mount antennas on towers, rooftops, etc. The cost can range from anything between $500 - $3000 a month. Sometimes, the charge is on the basis of the sq. footage or antenna units mounted. Hence, the all-so-common assumption of having any number of antenna elements on the base station side, separated by large inter-element spacings is actually quite impractical. This is where antenna design comes into picture. Our aim is to try and design base station antennas that satisfy all the above mentioned requirements, while ensuring that performance is not affected. When we say performance, we mean the average data rates obtained in the cell and the outage probabilities that a base station antenna design will yield.

Fig 1: Directional base station antennas.

Now we come to the part where MIMO fits into all this. Current (single antenna) cellular technologies like CDMA, GSM, EDGE etc. cannot support the growing number of cellular service users, coupled with the large demand for high data rate applications. Cellular service providers are now looking to MIMO as a solution to meet this demand for high data rates. The inclusion of MIMO in standards like WiMAX and 3GPP-LTE has increased pressure on the cellular service providers to make the shift (and make it soon). The only problem that the providers have with making this shift is that it might require that the transceivers at the base stations be upgraded to support MIMO. It is not clear if the base station antennas should be changed or if the existing setup will suffice for MIMO as well. We in WSIL are currently investigating if the existing base station antenna designs will work well for MIMO. This will make the transition for cellular service providers a whole lot easier.

Coming now to the mobile terminals. These devices, as we well know, are placed and held at random orientations. This implies that the antenna used should be such that it can receive (and transmit) equally well in all directions. This is the first requirement for antennas for a mobile terminal. Note that omnidirectional antennas generally do not perform as well as directional antennas, making this a challenge for the antenna designer. The second requirement for the mobile terminal antenna is that it should occupy as little space as possible. This is where low profile microstrip (patch) antennas, planar inverted-F antennas (PIFAs), etc. come into picture. Note that these are embedded antennas, whereas the earlier models of cell phones used whip, retractables, etc. The third requirement is that the cell phone antenna should be able to support a large number of functions apart from just supporting phone calls, like FM or bluetooth, for example. This requires that the antenna used should be a multi-band antenna supporting all the frequencies needed or that we use different antennas for each frequency. It is obvious that the single antenna is a much better option, both in terms of cost and space occupied. Designing multi-band antennas is a challenge for the designer if the number of bands to be supported is greater than two. The larger the number of frequencies required, the greater the difficulty in design.

I will conclude with a brief statement on why cellular antenna design is important. An antenna designer spends a lot of time and effort trying to optimize antenna parameters like cross-pol pattern discrimination, the port-to-port isolation, etc. These parameters need to be optimized by (in some cases) minutely tweaking the physical structure of the antenna. This process can at times take days to accomplish. By using effective antenna design techniques, we can optimize these parameters using simulations and can give a conservative estimate beyond which the performance will not be affected. This in turn, saves time and effort (and money!).

That’s it for now. I will post another blog on some details of antenna design and, in particular, the work we do in WSIL on this topic.

The news article here

We’ve all seen something similar in some SciFi movie. Imagine the things you can do. Connect wirelessly to display information about your location within your vision, a cheat sheet display for your next big talk, etc…

Unfortunately, it appears that there is no clean way to feed power and information signal to it other having a wire dangling from your eyes (ouch!). Maybe a RFID-like passive display could be of immediate use.

To give a MIMO flavor, maybe some form of MIMO visual communication is possible…