White Space Networking with Wi-Fi like Connectivity

P. Bahl, R. Chandra, T. Moscibroda, R. Murty, M. Welsh, "White Space Networking with Wi-Fi like Connectivity", ACM SIGCOMM Conference, (August 2009).

One line summary: This paper describes a system for UHF white space wireless networking called WhiteFi that addresses the three main challenges unique to white space networking: spatial variation, temporal variation, and spectrum fragmentation in the available white space channels.

Summary

This paper presents a system for UHF white space wireless networking called WhiteFi. White spaces are the unused portions of the UHF spectrum that have recently been opened for use by unlicensed devices subject to the constraint that such devices not interfere with incumbent uses such as TVs broadcasts and wireless microphone transmissions. As a consequence of this, white space networks differ in three major ways from traditional wireless networks: spatial variation, spectrum fragmentation, and temporal variation. White space networking involves spatial variation in the availability of portions of the white space spectrum because the presence of incumbents varies over the wide area as well as on a finer scale. It involves spectrum fragmentation due to the presence of incumbents occupying certain UHF channels; fragmentation varies across area and this implies the need for using variable channel widths. Lastly, white space networking involves temporal variation largely because of the use of wireless microphones, which can be turned on and off at any time, and white space devices must switch channels when they detect a wireless microphone in that channel.

WhiteFi is supported on the KNOWS hardware platform, which consists of a PC, a scanner, and a UHF translator. Two key features of this platform are support for variable channel width use and a primary user signal detection algorithm called Signal Inspection before Fourier Transform (SIFT). Three key components of WhiteFi that build upon this are a novel spectrum assignment algorithm, SIFT for discovering white space wireless access points (APs), and a chirping protocol that permits indication of disconnection from a channel due to the appearance of an incumbent, without interfering with the incumbent. The spectrum assignment algorithm is adaptive and client-aware, picking a channel and a channel width that is free for all clients. It uses a spectrum map to indicate the presence of incumbents, an airtime utilization map to indicate the degree of utilization of each UHF channel, and control messages between the clients and AP containing these maps to share the necessary information. It uses this information along with channel probes to compute the multichannel airtime metric (MCham), which is roughly a measure of the aggregate bandwidth of given selection, and which it uses as the basic for channel selection. AP signals are detected by sampling bands of the UHF spectrum using SDR and performing an efficient time-domain analysis of the raw signal using SIFT. Sudden disconnections due to the appearance of an incumbent on a channel that an AP-client pair is using for communication is dealt with using a chirping protocol, which involves sending beacons about the white spaces now available over a backup channel.

In the evaluation of WhiteFi, several things are demonstrated. The first is that SIFT accurately detects packets over varying channel widths even with high signal attenuation, missing in the worst case at most 2%. The second is that the AP discovery algorithms are effective. The next is that WhiteFi correctly handles disconnections using its chirping protocol. The last is that WhiteFi’s channel selection algorithm adapts quickly and makes near-optimal selections to operate on the best available part of the spectrum. This last point is demonstrated via simulation.

Critique

This was one of my favorite papers that we’ve read so far (along with the classics). To me at least this seemed like an awesome feat of engineering and it’s obviously very useful technology so and exciting to think of it becoming available. I actually quite enjoyed reading it. Obviously there will be a lot of interesting work in the future that will build off of what they did here. I checked to confirm my suspicion that it won Best Paper Award at SIGCOMM this year so I like to think that somewhat legitimizes my raving about it.