1
DYNAMIC SPECTRUM ACCESS IN
DTV WHITESPACES: DESIGN RULES,
ARCHITECTURE AND ALGORITHMS
Supratim Deb, Vikram Srinivasan, (Bell Labs India)
Ritesh Maheshwari (State University of NY)
MobiCOM 2009
Presenter: Han-Tien Chang
Outline
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Introduction
Related Work
Background
Design Rules
System Architecture and Spectrum Allocation
Problem
Algorithms (for spectrum allocation)
Simulations
Conclusion and Comments
Introduction
3

The newly freed up spectrum (from analog to digital)


along with other slices of unused spectrum in the 50-700 MHz (channels
2-51) television band is known as DTV white-space (DTV-WS).
In November 2008, in FCC’s second report and order [4],

The FCC ruled that the digital TV whitespaces be used for unlicensed
access by fixed and portable devices



Fixed devices (e.g., IEEE 802.22 base stations) are used for providing last mile
internet access in underserved areas
Portable devices can be used to provide short range wireless connectivity for
Internet access (e.g., Wi-Fi like access points)
Indeed, unlicensed access in DTV-WS can not only decrease congestion
on the 2.4 GHz ISM band, but also provide much better data rates and
coverage due to superior propagation properties of the spectrum.
[4] FCC 08-260. Second Rep. and Order and Memorandum Opinion and Order. 2008.
Introduction (cont’d)
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
In this paper,


Perform a comprehensive design exercise of a system for Wi-Fi
like unlicensed access in the DTV whitespaces.
Design a system and architecture


where a central controller can be responsible for performing efficient
spectrum allocation based on access point demands
The Goal



develop a thorough understanding of the effect of frequency
dependent radio propagation and out of and emissions on system
design
derive an FCC compliant multi-radio based architecture based on this
understanding
design algorithms to efficiently allocate variable spectrum to access
points based on their demand
Related Work
5

The KNOWS [29] project at Microsoft has developed a
hardware prototype, a carrier sense MAC and algorithms
for dynamic spectrum access.
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In [21], the authors consider a problem very similar in nature
to ours
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doesn’t consider the propagation characteristics, co-channel
interference and out-of-band emissions
issues of out-of-band emissions and frequency dependent
interference graphs do not come into play
In [7], the authors design and implement a Wi-Fi-like system
with Wi-Fi components that operates over UHF whitespaces

also demonstrates how spectrum fragmentation and spatial
variation of spectrum have implication on network design.
[29] Y. Yuan, P. Bahl, R. Chandra, P. A. Chou, J. I. Ferrell, T. Moscibroda, S. Narlanka, and Y. Wu. KNOWS: Kognitiv Networking Over White Spaces.
In IEEE DySPAN 2007.
[21] T. Moscibroda, R. Chandra, Y. Wu, S. Sengupta, P. Bahl, and Y. Yuan. Load-Aware Spectrum Distribution in Wireless LANs. In IEEE ICNP 2008.
[7] P. Bahl, R. Chandra, , T. Moscibroda, R. Murty, and M. Welsh. White Space Networking with Wi-Fi like Connectivity. In ACM SIGCOMM 2009.
Background
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Radio Propagation
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Out of Band Emission
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Path loss is directly proportional to the square of the carrier frequency
Specifically lower frequencies propagate much farther than high frequencies
Radio transmissions are never entirely confined to their operating bandwidth
Some power leaks into the adjacent parts of the spectrum causing adjacent
channel interference
Adjacent Channel Interference (ACI): The spectrum mask allows us to compute the
adjacent channel interference precisely.
FCC Regulations
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
Channel Occupancy Database
Fixed Device, Portable Devices
Interference to DTV Receivers
Design Rules
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
Determining Transmit Power
 Design
Rule 1
 Consider
a white space W, which is to be shared between
several APs. Ensure that each AP gets at least 6MHz and set
the transmit power for each AP to 40 mW (16 dBm).
Design Rules (cont’d)
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Guard Band
 Design
 The
Rule 2
guard band depends on the frequency of operation.
 For channels 21-51, the guard band between frequency
allocations on two different radios on the same AP should be
separated by at least 20MHz.
 Thus for the choice of spectrum mask parameters L = -50 dB
and α = -2.28 dB/MHz, adjacent channels with no guard
band can be allocated to adjacent access points
Design Rules (cont’d)
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Interference Graph
 Design
Rule 3
 The
interference map of an AP in a higher frequency band
can be inferred from the interference measurements in a
lower frequency band using Equation 11 along with
appropriate ambient interference measurements.


Consider two APs AP1 and AP2, and suppose AP1 is transmitting
using power P.
Suppose Pr(f1) is the received power at AP2 when the transmission
happens using carrier frequency f1, and similarly Pr(f2) is defined.
Design Rules (cont’d)
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
Aggregate Spectral Efficiency (ASE)
 Design
Rule 4
 For
any frequency band, the RSSI measurements from the
clients can be used to compute the ASE.
 The ASE in one frequency band can be computed from the
ASE in another frequency band
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
Consider a carrier frequency f1 for an AP. Assume the kth client
perceives SINRk(f1)(dB). Then the spectral efficiency for the kth
client is k(f1) = a + bSINRk(f1).
Assume there are N clients and each client has equal
opportunity to communicate with the AP. Then the ASE is given by
System Architecture and Spectrum
Allocation Problem
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
Architecture

Access Point
Each access point comprises multiple transceivers
 One transceiver is dedicated for communications over a common
control channel

Clients
 Central Controller

periodically computes the interference graphs in the different
whitespaces.
 computes the ASE in the different whitespaces based on control
channel aggregate RSSI measurements provided by the AP
 an efficient allocation of the available whitespaces based on
interference maps, ASEs, ACI constraints, transmit power constraint

System Architecture and Spectrum
Allocation Problem (cont’d)
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System Architecture and Spectrum
Allocation Problem (cont’d)
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
Spectrum Allocation Problem in DTV-band

Our goal is to assign spectrum to all/some of the radios of
each AP in the different WS’s.
There are NWS distinct white spaces (WS), where the jth white
space has center frequency fj and total available bandwidth Wj .
 We wish to distribute the white space bandwidth among NAP
distinct AP’s.
 Each AP has Nrad different radios.
 For the jth white space, associated with APi is a set of other AP’s Nij
(called neighbors of APi in white space j) that cannot transmit
simultaneously with APi over the same spectrum on any of the Nrad
radios.

System Architecture and Spectrum
Allocation Problem (cont’d)
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System Architecture and Spectrum
Allocation Problem (cont’d)
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 Associated
with APi are two parameters
 Demand
in terms of data rate, denoted by di
 ASE over whitespace WSj, denoted by ηij

we can set ηij = 0 if WSj is not available to APi
 System
Constraints and Objective
 Operating
Spectrum Width
 Minimum Spectrum Width

bm= 6MHz
 Co-channel

Reuse Constraint
From the interference graph
 Adjacent-channel
Reuse Constraint
System Architecture and Spectrum
Allocation Problem (cont’d)
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 Objective
Function
 In
proportional fairness based schemes, the goal is to
maximize overall system utility where the logarithm of the
data rates are taken as a measure of utility

 The

In such a scheme, the objective is to find data rate ri to APi
problem of maximizing system capacity
our objective will be to maximize the total data rate across all
AP’s, subject to the constraint that no AP gets more than the
requested demand
System Architecture and Spectrum
Allocation Problem (cont’d)
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
Problem Statement
 Proportionally
Fair White-Space Spectrum Allocation
Problem (PF-WSA)
 To
find: an allocation of spectrum to the Nrad radios of the
AP’s subject to the system constraints OSW, MSW, CCI, and
ACI such that, if ri is the data rate achieved by APi,
  then Σi dilog(1 + ri) is maximized.
Algorithm
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
Spectrum allocation for single WS and single radio
per AP
 The
problem can be solved easily for a clique
 Greedily
assign spectrum to AP’s that give higher increase in
the utility per unit of spectrum
 Identify cliques formed by neighbors of a node for all nodes
u, and then greedily assign spectrum by giving higher
priority to those cliques that give the best improvement in
the objective function.
 Our
 mi:
goal is to maximize Σi Ui(ri)
a minimum threshold
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Sum the used bandwidth and update
20-22: Request = Demand, remove ym
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28. If the last iteration alone contributes to the utility more than the other iterations
combined, we allocate bandwidth only to the greedy choice in the last iteration
Algorithm (cont’d)
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
Solving PF-WSA for a general interference graph
 1.
Computing the total utility in the neighborhoods
 2. Allocating spectrum to the best neighborhood
 3. Repetition of the steps
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Algorithm (cont’d)
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Multiple White Space and Multiple Radio
 the
idea of local search where we iteratively improve
upon the solution by improving the solution for
individual WS’s
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Simulations
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Two objectives
 Evaluate
the performance of our algorithms versus an
upper bound for the PF-WSA problem
 Evaluate the performance benefit from doing dynamic
spectrum allocation in the DTV whitespaces as opposed
to doing dynamic spectrum allocation in the 2.4GHz
ISM band
Simulations (cont’d)
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Conclusion and Comments
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

Designing system for short range unlicensed access
is a complex and challenging task
four design rules that allow us to manage this
complexity, and based on these rules,
 we
proposed an architecture and algorithms for
efficient demand-based spectrum allocation

Comments
 Thorough
 From
 The
system design procedure
the issue analysis to different case solution
future of DTV whitespace