Abstract
It has recently been shown that flexible channelization, whereby wireless stations adapt their spectrum bands on a per-frame basis, is feasible in practice. In this paper, we propose TF-CSMA/CA, an algorithm for flexible channelization that schedules packets in time and frequency domains. TFCSMA/CA is a simple extension of the CSMA/CA protocol used by IEEE 802.11. Contrary to existing channelization schemes, it is entirely distributed and it reacts only to packet collisions, successful transmissions and carrier sensing. With TF-CSMA/CA, when a station is involved in a collision, it performs backoff in both time and frequency domains. Backing off also in the frequency domain allows the transmitters to be much more efficient and aggressive in the time domain, which significantly reduces the severe overheads present with recent 802.11 PHY layers. The main challenge, however, is that the stations need some level of self-organization in order to find spectrum bands of variable widths that minimize interference, while still efficiently using the available spectrum. Using analysis and simulations, we show that such an extension of CSMA/CA to the frequency domain drastically improves both throughput and fairness. Notably, it enables the stations to find interference-free spectrum bands of appropriate size using no communication – relying only on collisions and successes as implicit signals.
Original language | English |
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Title of host publication | 2015 IEEE 23rd International Conference on Network Protocols (ICNP) |
Publisher | IEEE |
Pages | 256-266 |
Number of pages | 11 |
ISBN (Electronic) | 9781467382953 |
DOIs | |
Publication status | Published - 21 Mar 2016 |
Event | 23rd IEEE International Conference on Network Protocols 2015 - San Francisco, United States Duration: 10 Nov 2015 → 13 Nov 2015 |
Conference
Conference | 23rd IEEE International Conference on Network Protocols 2015 |
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Abbreviated title | ICNP 2015 |
Country/Territory | United States |
City | San Francisco |
Period | 10/11/15 → 13/11/15 |
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Vsevolod Shneer
- School of Mathematical & Computer Sciences - Associate Professor
- School of Mathematical & Computer Sciences, Actuarial Mathematics & Statistics - Associate Professor
Person: Academic (Research & Teaching)