Paper at ICC: PDF and video

I'm back from beautiful Cape Town, where I presented the paper I mentioned earlier.

Citation:

N. Farsad and A. W. Eckford, “Resource allocation via linear programming for multi-source, multi-relay wireless networks,” in Proc. IEEE International Conference on Communications (ICC), Cape Town, South Africa, 2010.

PDF of the paper is here.

Presentation video (this is a playlist):

Seven continents

It's long been a life goal of mine to visit all seven continents, which I managed to cross off the list when I stepped off the plane in Africa.

Pictures from: Australia (Sydney, Australia, 2005); Europe (Fontainebleau, France, 2008); Asia (Great Wall near Beijing, China, 2008); Africa (Cape of Good Hope, South Africa, 2010); South America (Colonia, Uruguay, 2006); North America (Banff, Canada, 2008); Antarctica (Weddell Sea, 2006).

Paper at ICC

UPDATE: Paper PDF and presentation video are here.

I'll be heading to Cape Town later this week to present a paper at ICC:

Resource Allocation via Linear Programming for Multi-Source, Multi-Relay Wireless Networks
N. Farsad and A. W. Eckford
CT05: Tuesday, May 25, 1400-1545, Roof Terrace A

This paper continues my work on fractional cooperation, in which relay nodes only retransmit a fraction of the source's packet. Since the transmission is corrupted both by the channel effects and the possibility that not every source bit is retransmitted, we use LDPC codes to recover the original transmission. There are two key insights here: first, in LDPC decoding, the log-likeihood ratios of the relays are additive, weighted by coefficients equal to the source fractions (i.e., a linear combination); and second, for sufficiently many relaying partners, the sum of the LLRs has approximately a Gaussian distribution. Similarly to the design problem solved by EXIT charts, the problem of assigning source fractions can be posed as a linear program.

I'll be presenting the paper. Video of the talk and the PDF of the paper will be posted after the conference.

Paper at Queen's: PDF

It was a beautiful day in Kingston on Wednesday, which I mostly spent indoors listening to talks.

Here are the PDF and citation of the QBSC paper I mentioned earlier:

S. E. T. Hadley, A. W. Eckford, and W. H. Gage, “Power saving in a biomechanical sensor network using activity detection,” in Proc. 25th Biennial Symposium on Communications, Kingston, ON, pp. 173-176, 2010.

Summertime, and the living is busy

I love it when I tell someone that I'm a professor, and they respond with something like, "Oh, it must be great to have the whole summer off!" Especially today: with my spring grading finally out of the way, I'm making up my lengthy summer to-do list. Some highlights:

• Clean up my office disaster
  
• Attend this conference (and attend an executive committee meeting)
• Attend and speak at this conference
  
• Finally get the revisions done for this paper (which should have been done months ago)
• Write a journal version of this paper
• Get a grant proposal done
• Read and edit theses as two students get ready to defend
• Get some chapters done for a textbook project that were promised for months ago
• Make some headway on a new consulting contract
• Lots more that I'm forgetting, for sure

Yep. Another lazy, coronas-on-the-beach summer.

Paper at Queen's

My paper at the Queen's Biennial Symposium on Communications:

Power Saving in a Biomechanical Sensor Network Using Activity Detection
Scott E. T. Hadley, Andrew W. Eckford, and William H. Gage
Wednesday, May 12, 4:50-6:10 PM (second talk in session), Walter Light Hall rm. 210

This is the first paper out of an interdisciplinary project with Will Gage in Kinesiology. The basic idea is to place accelerometers on stroke patients to monitor their recovery in walking, but the main challenge is to design a system with the robustness, endurance, and ease of use to be used in the home, rather than in the therapist's office. It's a practical project with lots of neat signal processing, and we just got a grant to continue it.

One of the key issues is to reduce power consumption and extend battery life. In this paper, we show that signal processing can help with power saving: we use activity detection to scale the sampling rate based on what the patient is doing. As a result, we strike a nice balance between power saving and data loss: switching modes, we lose about a second of data (about one step -- because it takes that long to detect acceleration with the reduced sampling rate), whereas we would lose about 30 seconds by putting the node to sleep and waking it up.

Scott will be presenting the paper. I'll be at Queen's for Wednesday only, so I hope to see you there. PDF of the paper will be posted shortly.