Spectrum Usage Estimation and Channel Allocation inIEEE 802.22 Networks∗

Saptarshi Debroy, Shameek
Bhattacharjee and Mainak Chatterjee

Kevin Kwiat
Air Force Research Laboratory
Information Directorate
Rome, NY 13441

University of Central Florida
Orlando, Florida 32816{saptarsh,shameek,mainak}@eecs.ucf.edu

ABSTRACTIn this paper, we propose and evaluate a novel spectrum usage estimation methodology for IEEE 802.22 networks anduse that to efficiently allocate data channels to consumer
premise equipments (CPEs). We specifically analyze theproblem of estimating the spectrum usage report at any arbitrary CPE location. A base station (BS) achieves this byopportunistically sharing and fusing the raw spectrum usage
reports from different BSs using the well known Shepard’s
interpolation technique for irregular data sets in a multi dimensional space [2]. Once the spectrum usage is estimated,the BS performs uplink and downlink channel allocation to
the CPE. We evaluate our estimation and allocation framework by analyzing the number of allocated CPEs, the number of BSs required for efficient estimation, and by verifying
the nature of spectrum estimation with trace results.

1.

SPECTRUM USAGE SHARING IN IEEE
802.22 NETWORKSIEEE 802.22 based wireless regional area networks(WRAN) [1] is a cognitive radio technology that operates on the underutilized and unused sub-900 MHz
bands used primarily for TV services. The core components of an IEEE 802.22 network are the base stations(BS) and the consumer premise equipments (CPE). These
secondary nodes opportunistically access unused or underutilized license bands of primary users. Secondary
nodes monitor the activity of primary users on a constant basis using spectrum sensing mechanisms, therebybuilding a knowledge of spectrum usage called the spec∗

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kevin.kwiat@rl.af.miltrum or channel usage report. This report empowers
the secondary users to better adapt their transmission
parameters to the current conditions. Channel allocation to CPEs is performed by the BS, which is assumed
to have an accurate estimation of spectrum usage report of all CPEs in range. Hence, efficient channel allocation and sustenance of high data rates with low interference in WRAN largely rests upon the BS’s ability toaccurately estimate spectrum usage and allocate unused
bandwidth to the CPEs.
A base station initiates communication with a potentially allocable CPE through beacon broadcast. Thebase station periodically tunes itself to a particular channel, listens for any primary signal, and if none foundthen sends a connection establishment beacon to channel. Only a CPE tuned to that channel at that particular time can listen to that beacon and send a channel
allocation request back to the base station through thesame channel.
Once a base station receives a channel allocation request from a CPE, it finds the nearest (from the CPE)
spectrum sensing capable nodes (i.e., other base stations) who share their spectrum usage reports throughthe common control channel. Selection of these basestations depends on the search radius being considered.

2.

SPECTRUM USAGE ESTIMATION

To estimate the spectrum usage at any arbitrary CPE
location, we seek to define a continuous two-dimensional
interpolation function which passes through all the given
irregularly-spaced data points i.e., the base stations thatshare their spectrum usage.
Let ei be the value of the detected energy from thespectrum usage report of base station BSi . Let di be
the Euclidean distance between BSi and a CPE c andN be the total number of channels in the spectrum. We
adopt an approach to interpolate values using weightedaverages. Although the basic weighted average technique of finding expected value at an arbitrary point iseasy to compute, it overlooks some key aspects: thosebeing the number, locations, and the relative positions

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Figure 1: Performance of the proposed estimation and channel allocation techniqueof the known data points with respect to point wherethe value is to be determined. Considering all theseeffects on c, the interpolation function is defined as Xwi ei∈Rcn BSiX
if di 6= 0 f or all BSi
F (c) =win
 BSi ∈Rcei
if di = 0 f or some BSi
Here the weighing factor is defined as wi = (pi )2 (1 +ai ) where ai denotes the directional weighing factor andpj denotes the distance weighing factor. With the usage
for the entire spectrum estimated, the base station can
predict the set of free channels at c.

3.

CHANNEL ALLOCATIONOnce the potentially available channels at c is determined, the BS initiates channel allocation process.
Successful channel allocation to a CPE involves allocating a pair of channels, downlink and uplink. Only
those channels can be allocated as downlinks and uplinks which are free both at the CPE and at BS, otherwise it will cause harmful interference with primarytransmission. Whenever two channels are allocated toa CPE, they are added to the sets of allocated downlink and uplink channels. This helps the BS to ensurespatial reuse of the channels within its cell.
If CPE c wants to relinquish its channels, they are removed from their respective sets. There may be several
reasons for channel relinquishment. Session terminationby the CPE c or change in spectrum usage scenario ineither BS or CPE side because of arrival of primary incumbent. In that case these channels cannot be used
any longer until they are freed by primary incumbent,
and thus the CPE in question has to be reallocatedwithin the channel move time or kept starving.

4.

SIMULATION RESULTS

We conduct extensive simulations to validate the performance of the proposed channel allocation techniquesin C and MATLAB.

In Fig. 1(a) we show the spectrum map for the entire
region, i.e., the estimated channel usage of a particularchannel at every point in the region with 40 participating base stations. The base stations, shown by stars, arethe actual data points which are used for interpolation.
Fig. 1(b) shows the number of allocated CPEs under aparticular base station with varying number of CPEs inthat cell. This channel allocation performance is shown
for a particular base station with coverage radius of 10units and search radius of 30 units. A 45 ◦ slope isideal implying complete allocation where all CPEs are
assigned channels. Our success rate (0.96) is very close
to ideal. In Fig. 1(c), we show the number of CPEs in aparticular cell that were allocated channels successfullywith varying number of base stations. We see that thenumber of allocated CPEs starts to decrease as numberof cognitive base stations goes beyond a certain number. This observation is in accordance with Shepard’s
method [2] which says that increase in the number of
selected data-points beyond a certain point will introduce errors in the estimation process thereby affecting
allocation. Fig. 1(d) shows the estimated channel usage for a particular channel with varying number of
selected base stations. The result that the estimatedvalue reaches a steady state as number of base stations
gradually increases is intuitive.

5.

CONCLUSIONSIn this paper, we use a modified version of Shepard’s
interpolation function to estimate the channel usage at
any arbitrary CPE location in an IEEE 802.22 network.
We also described how such estimations help the basestation to efficiently allocate uplink and downlink channels to the CPEs. Through simulation experiments, weshowed the efficiency of the allocation technique, effectof total number of base stations and number of selected
cognitive nodes on the accuracy of estimation.

6.

REFERENCES[1] IEEE 802.22, Working Group on Wireless Regional Area
Networks (WRAN), http://grouper.ieee.org/ groups /802/22.
[2] D. Shepard, “A Two-Dimensional Interpolation Function for
Irregularly-Spaced Data,” ACM National Conference, 1968.