Status of Next Generation
Cellular and Wireless Local Area
Networks and Current Research
Activities
Mohsen Guizani
Computer Science Department
Western Michigan University
mguizani@cs.wmich.edu
Western Michigan University
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•
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WMU is located in Kalamazoo, Michigan
WMU is one of 15 Michigan state schools
WMU has more than 28,000 students
The Computer Science is home to about 400
students
• CS has 18 faculty members, 5 full
professors, 7 associate professors, and 6
assistant professors.
Outline
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Introduction
Cellular Coverage in the United States
Current Problems in the Telecommunications Industry
Review of Cellular Technologies
Wi-Fi: Competing or Complementary Technology?
The Future
Current Research Activities
Conclusions
Current Research Activities
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Research Goal
1x EV-DV Architecture
Resource Allocations Techniques
Cross Layer Design Overview
Intelligent Network QoS Protocols
Intelligent Network QoS Validation Protocol
Wireless QoS Based Routing Protocol
Introduction
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A combination of factors has led to the current
wireless situation in the US, which is rather poor in
many respects
 Rapid technological change
 Rapid change in way people use technology
 Poor business and investment decisions
 Unrealistic expectations for new technologies
 Competition on features and packages rather than
underlying infrastructure
More thinking and intelligent decision making in
future should enable vastly improved wireless service
Cellular Coverage in the US:
Reason for Poor Coverage
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Coverage is similar (often poor) because all providers
use the same antenna towers
Much of the engineering behind tower placement is
done in the old days of 3 watt cell phones at 800
MHz in cars with external antenna; in this day and
age, the is much lower-powered units inside buildings
or cars with no external antennas
NIMBY (“not in my backyard”) syndrome: Wealthy
neighborhoods refuse to allow unsightly antenna
towers
Cellular Coverage in the US
(Continued)
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Call by one of the authors from Baltimore, MD to
Washington DC Dulles International Airport
interrupted seven times due to coverage gaps—partly
ascribed to the fact that there are five major cellular
providers each of which has to build an entire
network
The Yankee Group estimates that it would take $50B
to $100B to bring cellular system up to snuff
 Carriers do not have that kind of money
 Would not solve political problems
 Convenience trumps service quality
 Relatively few people have abandoned landline
phones
Cellular Coverage in the US
(Continued)
50
45
40
35
30
25
20
Verizon
MCI PreBankruptcy
$45.4
$41.0
15
Sprint
SBC
Qwest
10
$19.2
$17.9
$17.5
5
0
MCI PostBankruptcy
$5.5 *
BellSouth
AT&T
$15.0
$14.4
Source: Wall Street Journal, 4/15/04
Cost Constraints
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Minimal revenue per minute of air time
 Brutal competition
 Availability of free airtime and long distance
packages
No “killer app” has ever materialized
 Not cameras and ability to send photos
 People want dependable voice communications
Cellular phones unsuitable as wireless modems
 Promoters did not consider human factors
 E-mail already well-served by dedicated devices
such as the popular Blackberry by RIM
Cost Constraints (cont.)
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Access to the Internet is done while at rest

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Coverage problems would interrupt most
operations if in motion

Cannot really do anything while driving or walking

Screen is too small
Competing technologies such as Wi-Fi are
much better
Problems
Problem
Telecommunications firms are
deeply in debt (or out of
business) because of two
miscalculations stemming
from over-estimating revenue
potential of fiber optics
Technology provided capacity
far in excess of users to
absorb
Reasons
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No “killer app” has
materialized
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Poor understanding of human factors—how
quickly people will change their way of doing
things
The difficulty of solving the “last mile”
problem—aging copper plant; coaxial system
designed for one-way transmission
$100M will buy a fiber from US to UK
With WDM technology this could be >2 Tbits
per second—few users
The only one is sight is HDTV (video on
demand)—may well happen, as HDTV is slowly
being adopted; however widespread demand
is still 3 to 5 years in the future
Will not be from low-bandwidth devices such
as videophones
Problems (Continued)
Problem
Reasons
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Telecommunications
companies rested on their
laurels
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Infatuation with technology
and disregard of human
factors has led to other
telecommunications company
fiascos, such as Iridium and
Global Star
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Did not upgrade “last mile”
Rollout of DSL was initially slow—many areas
could not be served; has limits in any case
Pressure built as CATV companies began to
offer broadband
Only recently have telecommunications
companies begun to move out on POE
Proponents underestimated speed at which
conventional cellular systems would be
deployed
Never showed that a large base of users would
pay $5 per minute—not enough Antarctic
explorers, oil drilling rigs, Sahara desert
trekkers, Mt. Everest climbers; village chief in
third world country could not afford it
Problems (continued)
Problem
Reasons
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Other:
Narrowband
Integrated
Services Digital
Network (ISDN)
(2B+D)
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Developed in the late 1970s
Supposed to be vehicle to convert telephony
worldwide in the 1980s
Priced very high
Few could see any real benefits—calls connected
faster, but audio quality about the same
128 Kbits per second was enormous by 300 bd
standards in the 1980s—few places to dial-up then
 By the time “killer app” arrived, the Internet, ISDN
was wrong paradigm
 Connection-oriented service (pay by minute) for
connections protocol
 56K modems were extremely cost-effective and
not that much slower
Problems (continued)
Problem
Other:
DSL technologies
offer much higher
bandwidth than ISDN
at lower cost for
typical usage
Other:
Telecommunications
companies overbid for
3G wireless spectrum
to the tune of billions
of dollars
Reasons
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Rollout delayed by ISDN push
Now a successful service
Supposed to provide great advantages,
unfortunately based on several assumptions
 Technology was proven
 Users had need for features it offered, such
as video
1G Cellular Technology
Advanced Mobile Phone Service (AMPS)
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Analog
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Widest coverage, much wider than digital systems
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Phased out by 2008
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Of concern to users of OnStar, which employs it—
digital systems’ coverage poor by comparison
Being phased out because newer systems can
support more customers per unit of bandwidth—
bandwidth is most precious resource
2G: GSM, CDMA, IS-95-a, iDEN
Global System Mobile (GSM)
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Initially Group Speciale Mobile; renamed Global System Mobile
to give it an international flavor
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Combined TDMA/FDMA system
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Offered by AT&T, T-Mobile, and Cingular in the US
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Advantage: With unlocked tri-band phone, users can have
cellular service worldwide
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Problem: Outside the US, reciprocal agreements with US
providers expensive—$~4 per minute for airtime
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Better solutions: Get subsidy unlock code for phone used in
US—buy SIM card when abroad from kiosk; buy cheap tri-band
phone in the US, then buy SIM card when abroad
2G (Continued)
Coded Division Multiple Access (CDMA)
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Offered by Sprint and Verizon in the US
Verizon recently launched high-speed data
service based on Phase 1 Evolution Data Only
(1xEV-DO) in Washington, DC and San Diego,
CA
Can handle the largest number of users per
unit BW; most economically attractive
2G (continued)
Time Division Multiple Access (TDMA)
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Use declining
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Offered by AT&T and Cingular in the US
Integrated Digital Enhanced Network (iDEN)
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Developed by Motorola
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Based on TDMA
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Offered by Nextel in the US
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Likely to be phased out in favor of CDMA-2000
2.5G
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So-called 2.5 or 3rd generation wireless
technologies unlikely to be profitable,
especially given prices paid for
spectrum
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Main thrust is higher speed data
Cannot compete with Wi-Fi
Nextel is planning to bypass altogether
What is needed is data rate of >2 Mbps
Beyond
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Various generations of cellular telephony more important to
providers than users
 Maximize revenue per unit bw
 Users care more about features, cost, dependability
 Many features being pushed are of dubious value
 Multimedia Messaging Service (MMS)
 Short Messaging Service (SMS)
 Walkie-talkie feature
 Reduces connect time to ~2 second versus 15
second dial time
 Games
 Downloadable ring tones
 Replaceable covers
Wi-Fi: Is It Really a Good Idea?
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IEEE 802.11b
Caught on very fast; manufacturers
incorporate Wi-Fi chips in laptops; hopes are
that this will be the new “killer app”
Wireless LAN equipment sales have been
growing—Gartner Group says 2002 spending
on all vendors is ~$2.3B; end-user spending
increasing by about 50 percent for the last
two years
Wi-Fi: Security Issues
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Algorithm is used, Wired Equivalent Privacy
(WEP) discredited
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Encryption key length too short
Initialization vector implementation flawed
Scheme can be cracked quickly
Successor, WPA, is patch—not a fix
Vulnerable to broadband jamming, unless it
uses frequency hopping as does Bluetooth
Wi-Fi: Security Issues
(Continued)
Users do not seem to care
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70 percent of installations have not even
implemented what little security measures there are
Incompatibilities among vendor equipment mean that
Wi-Fi hot spots must implement lowest common
denominator, i.e., no security
Wi-Fi user sitting next to “me” at Starbuck’s can
intercept all transmissions to/from my computer
 Doctor files in “my” computer
 Impersonate “me” after “I” have logged off
Wi-Fi: Security Issues
(Concluded)
Lack of scalability
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PKI has not provided desired solution
Efficiently and rapidly propagating
information about revoked encryption keys
through large networks
Problem of where to store private or secret
key safely in a manner that hacking cannot
compromise
Smart cards may be the only viable solution,
but most laptops have no smart card reader
 Could be added through USB port
Wi-Fi: Business Model
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No clear business model
Nobody making money off of Wi-Fi
 Not a cost center, but a gimmick to attract
customers
Issue of illegal use of Wi-Fi connectivity—who is
liable?
 Maryland homeowner recently held liable when
someone used his hot spot for an illegal act
Airports and other such places look to Wi-Fi to recoup
money no longer received from pay phones
 Travelers unlikely to agree to open yet another
account unless all places they frequent use same
account
Wi-Fi: Setup Difficulties and
Network Incompatibilities
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Complex Windows’ network setup menus and options to set the
SSID for each hotspot provider’s Access Point
Most non-technical laptop users are disinclined to do so
 Technical help from kid behind counter at Starbuck’s, etc., is
a losing proposition
Proliferation of different Wi-Fi hotspot providers means that
users must open a separate account for each
 T-Mobile account at 2,100 Starbuck’s or Kinko’s
 Cometa account at MacDonald’s
 FatPort account in Canada
 Surf & Sip account at Foley’s Irish pubs
 Toshiba account at Arizona’s Circle K stores
 Waypoint account at a few select hotels
Wi-Fi: User Fees and Speed
Problems
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User fees
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Disinclination of users to pay more access fees
Many feel they are already paying their Internet
dues through home subscriptions
Lots of free Wi-Fi access points
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From businesses that want to attract customers for their
main product
Speed problems
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Chips implementing 802.11b with WEP force all
users to speed of slowest user at the hotspot
Wi-Fi: Incompatibilities and
Spectrum Shortage
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Incompatibilities between WEP and WPA
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Problem has not received much press because
commercial hotspots have not enabled either—due
to vendor incompatibilities
Spectrum shortage
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802.11a has more spectrum allocated to it (which
allows it to accommodate more concurrent
users)—however has not yet caught on
Dual 802.11b/a access points and especially client
user’s PCMCIA cards are very expensive; suffers
from the same security vulnerabilities
Wi-Fi: Standards and
Scalability
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Standards
 802.11i, 802.11x, and 802.11e “standards” waiting in wings
in various levels of agreement as to their final specs
 Problem is that millions of deployed laptops and hotspots
may make upgrade to better standards impossible
Scalability
 Inherently not scalable
 Operates in crowded unlicensed band with baby monitors,
cordless phones, Bluetooth devices, microwave ovens
 Limited number of channels—3 versus 8 for 802.11a
Wi-Fi: Summary
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Wi-Fi has not really taken anything away from
cellular
Cell phones are not as practical as wireless
modems at 3 Kbps to 8 Kbps
Some CDMA systems (Sprint) encouraged use
of cell phone itself for e-mail and messaging;
however not practical due to the small size of
the keyboard
Human factors: do people really want to
make coffee shops another extension of their
office?
The Future
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Despite problems, wireless is here to stay
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Convenience dictates that it users will demand it
Problems of “last mile” access
Need to set up and tear down networks quickly
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Mobile ad hoc networks (MANETs) for military and for
emergency responder use
Sets the stage for determining who will
emerge victorious in future
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Go beyond solving current problems and
anticipate and solve future problems—foregoing;
societal preferences, economics, scalability, and
regulatory issues
The Future (Continued)
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Realities of wireless solutions
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Must be commercialized within months
Cannot hope for any regulatory protection given in
the past to telecommunications monopolies
Will have to compete fiercely with other
technologies for customer dollars—and hence for
survival
Three issues of importance
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Spectrum
Technology available to address problems
Socio-political issues
The Future (Continued)
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Really is not a spectrum shortage
Even in areas such as Washington, DC,
only about 20 percent of available cell
phone spectrum used during peak
hours
Real problem is more intelligent and
efficient use of available spectrum
Technology Available to
address Problems
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Ultra-wideband
Wi-Max
Wireless mesh networks
Smart antennae
Software radios
Technology Available to
address Problems (cont.)
Ultra-wideband
 Uses short (~1 nsec) pulses which
correspond to about 1 GHz bandwidth
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Such pulses with 1 W peak power and repetition
rate of 108 have average power of 100 mW
spread over 1 GHz
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FCC has allocated 3.1-10.6 GHz band
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Interference in a 1 kHz channel ~ 0.1 mW
Currently in use by satellite uplinks and downlinks
Data rates up to 500 Mbits per second can be
accommodated versus 700 kbps for Bluetooth
Technology Available to
address Problems (cont.)
Ultra-wideband (Concluded)
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UBW likely to become standard
of choice for home networks
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IEEE standard is 802.15.3a
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Uses TDMA
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Wireless Personal Area
Network (WPAN)
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245 devices up to 90 m
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Data rates 11 – 55 Mbps,
declining with distance
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AES encryption
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Discussions now about
dividing
Expected shipments of
UWB equipment
Technology Available to
address Problems (cont.)
Wi-Max
 Another emerging technology
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Intended for distances up to 50 km at data
rates up to 70 Mbps
Intended to provide broadband service to
replace “last mile” where this is not costeffective with conventional technology
May also take up some of the functions of
Wi-Fi
Technology Available to
address Problems (cont.)
Wireless mesh networks
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Low-powered systems that pass messages from node to node
on their way to their destination, not unlike what Internet nodes
do with e-mail and other Transmission Control Protocol/Internet
Protocol (TCP/IP) traffic
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Any one node’s RF power output needs to be no more than
what is required to close the link to the next nearest nodes
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Redundant paths enhance the likelihood of end-to-end message
integrity
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Inherent is frequency reuse
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Similar to old Ricochet network which went bankrupt because
high costs of installation could not be recouped with small base
of users
Technology Available to
address Problems (cont.)
Smart antennae
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Two stations communicating by wireless have absolutely no
excuse for using omni-directional antennas
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If each end could beam all of its RF energy towards the
direction of the intended receiver, the RF spectrum would
experience a massive increase in availability with no new
frequency allocations
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Beam forming can be computer-controlled for adaptive beam
forming
 In case of cellular base stations can be fast enough to
accommodate vehicular users
 In case of Wi-Fi can extend range; SF startup, Vivato,
working on 128 beam implementation
Technology Available to
address Problems (cont.)
Software radios
 Software-configurable cell phones
 To handle multiple systems, also Wi-Fi
 Eliminate need to buy new cell phones
every year or so
Socio-Political Issues
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Diverging international standards—China adopting its
own wireless LAN standard, basically Wi-Fi with
improved security
Ad hoc implementations—Some locations installing
their own area-wide Wi-Fi to deal with problem of
multiple accounts (Cerritos, CA)
Voice over IP
 Currently a major trend, or at least major hyped
trend
 Promises many benefits
 But many legal and regulatory issues unresolved,
especially related to emergency response and USF
Conclusion
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Rate of change in telecommunications has been unprecedented
International cellular and wireless LAN industries have had two
decades of gross miscalculations
 Multibillion dollar bankruptcies
 Endless miles of unused fiber optic cables
 Digital cellular coverage in the US which is poor even by
third world country standards
 Wireless LAN standards whose lack of security has been an
embarrassment
 Hodge-podge of mutually incompatible cellular standards
Conclusion (continued)
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Industry now has the opportunity to plan
wisely ahead
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Forego the short-term gimmickry of downloadable
ringing tones and designer-face-plates
Use US technological prowess in evolving
technologies such as software radios, ultrawideband, and smart antennas to forge standards
that will with-stand the test of time and of
consumer acceptance
Current Research Activities
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Research Goal
1x EV-DV Architecture
Resource Allocations Techniques
Cross Layer Design Overview
Intelligent Network QoS Protocols
Intelligent Network QoS Validation Protocol
Wireless QoS Based Routing Protocol
Motivations
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High bit-rate applications (www, file
transfer, full motion video) impose strong
requirements/needs on the system
capacity
Studies confirm a productive gain of
between 7-8 hours a week when business
users are equipped with mobile PCs and
wireless access.
All-IP applications: end to end packetswitched network
Goals
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To develop a new dynamic and intelligent
resource allocation technique for optimizing
the average throughput of the wireless
system.
Maximize the spectral efficiency and the
number of users supported.
Develop QoS based protocol in the upper
layer to assure the level of service required.
Block Diagram
Intelligent Network QoS
Validation Protocol Engine
Network
QoS
MAC/Network QoS Mapping Layer
MAC Layer
Res. Alloc.
Physical Layer
Competing technologies
CDMA Family
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cdmaOne - IS-95A (2G)
- IS-95B (2.5G)
CDMA 2000 1x (3G) 2000
CDMA 2000 3x MC (3G) 2001
1xED-DO (3G) 2002
1xEV-DV (3.5G) 2003
IS-95A
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2G – 1995
Upto 14.4 kbps data rates
Used exclusively for circuit-switched
voice
Used Convolutional channel coding
Used BPSK (fixed) modulation
technique
* BPSK: Binary Phase Shift Keying
IS-95B
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2.5G – 1999
MAC layer enhanced over IS-95A
Up to 115 kbps data rates (64 kbps)
Up to 8 forward or reverse code channels can
be simultaneously assigned to a MSU using
Walsh codes and PN sequence masks
Code channels are transmitted at full data
rates during a data burst.
Used Convolutional channel coding
Used BPSK modulation technique
CDMA 2000 1x
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3G – 2000
Up to 307 kbps data rates (144 kbps)
Q-PCH enables to monitor F-CCCH and Paging
Channel => improve battery life
Radio Configurations (RC) => additional data rates
Quality and Erasure indicator bit (QIB and EIB) on
the reverse power control sub-channel.
Code channels are transmitted at full data rates
during a data burst.
Used Convolutional and Turbo channel coding
Used QPSK modulation technique
CDMA 2000 3x MC

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

3G – 2001
Up to 2 Mbps data rates
Using 3 standard 1.25 MHz Chs within a
5 MHz band
Used Convolutional and Turbo channel
coding
Used QPSK modulation technique
1xEV-DO


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
3G – 2002 1st Evolution phase of CDMA2000
Up to 2.4 Mbps data rates
No backward-compatibility with CDMA 2000
2 inter-operable modes: 1x and 1xEV modes
Adaptive Rate Operation with respect to channel
conditions
Adaptive Modulation and Coding (AMC)
Macro diversity via radio selection
Always-on operation of 1xEV-DO terminals in the
active state
Multi-level modulation format (QPSK, 8-PSK, 16QAM)
1xEV-DV
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
3.5G 2003
Forward peak data rate: 3.072 Mbps
Reverse peak data rate: 451.2 kbps
3 new Chs to the forward link for the packet data
operation (F-PDCH, F-PDCCH0, F-PDCCH1)
3 new Chs to the reverse link to support operation of FPDCH (R-RICH, R-CQICH, R-ACKCH)
Adaptive Modulation and Coding on the forward link in
real time to adapt to the RF environment (QPSK, 8-PSK,
16-QAM)
Variable RF frame duration (1.25, 2.5 and 5 ms)
Fast selection of base station to serve forward link
No soft handoff on F-PDCH or F-PDCCH0 and F-PDCCH1
Tracing the DR Evolution
Data Rates Evolution
3500
3072
3000
2400
2500
2000
2000
1500
1000
500
0
14.4
115
IS-95A
IS-95B
307
CDMA2000 1x CDMA2000 3x 1xEV-DO
Data Rate (kbps)
1xEV-DV
CDMA Evolution Path
1xEV-DV Architecture
Logical and Physical Channels

Physical Layer Interface


MAC Layer



Control Information
User’s control
Bearer Data
Other Layers

No new service interfaces
Forward Packet Data Channel

Traffic channel combinations

operate in both mixed voice and data services
and data-only services in the forward and reverse
links.
New Physical Channels

Forward Link

Traffic Channel


F-PDCH
Control Channel

F-PDCCH

Reverse Link

Control Channel


R-ACKCH
RCQICH
Adaptive Modulation and Coding
Adaptive Modulation and
Coding
Reverse Link Feedback (R-CQICH)
Base Station (Tx)
Modulation and
Coding Scheme

CHANNEL
Mobile Station (Rx)
Channel Quality
The base station assigns users the best modulation and
coding rate for the instantaneous channel conditions
(SINR).
Adaptive Modulation and
Coding

Provides higher data rate services by
varying



The RF frame duration (1.25, 2.5 or 5
milliseconds)
The number of bits per RF frame (between 408
and 3864 bits)
The coding algorithm



QPSK (Quadrature Phase Shift Keying)
8-PSK (8-states Phase Shift Keying)
16-QAM (16-state Quadrature Amplitude Modulation) .
F-PDCH Data Rates


Data rates depending on F-PDCH packet size
and RF frame duration.
The RF frame duration

“Number of Slots per Sub-packet” (1 slot = 1.25
ms)
Hybrid ARQ

Automatic Repeat reQuest (ARQ)



Immigrates from MAC layer to Physical layer for
improving performance
A mechanism supporting retransmission of frames
received in error
Hybrid ARQ


Chase combining, each retransmission repeats the
first transmission or part of it.
Incremental redundancy (IR), each retransmission
provides new code bits from the mother code to
build a lower rate code
AMC and hybrid ARQ

On a single carrier, 1xEV-DV can efficiently
serve both data and legacy services
(e.g., voice) by combining of Fast AMC and
Hybrid ARQ


Fast AMC is a link adaptation scheme where the
base station assigns users the best modulation
and coding rate for the instantaneous channel
conditions.
Hybrid ARQ improves throughput and enables fast
AMC by making the initial modulation and code
rate selection process tolerant to selection error.
Cell Selection


The mobile station selects one base station
from its active set
The selection based on the RF quality
measured (SINR) by the mobile station
F-CPCCH
F-CPCCH
F-PICH
F-PICH
R-PICH
R-PICH
(F-DCCH/FCH/SCH)
R-CQICH
(R-DCCH/FCH/SCH)
F-PDCCH
MOBILE
F-PDCH
BTS 1
BTS 2
R-ACKCH
(F-DCCH/FCH/SCH)
(R-DCCH/FCH/SCH)
Flexible TDM/CDM
Multiplexing

1xEV-DV was designed to support all services




Services that use large packets
Services that use small packets
To reach the goal, TDM and CDM are included
into the 1xEV-DV specifications
TDM/CDM multiplexing allows the selection of
both the number of timeslots and the number
of Walsh codes allocated to a user.
TDM/CDM

The TDM/CDM in 1xEV-DV system maximizes system
throughput by providing optimal modulation and
coding rate assignments to all services while
maintaining frame fill efficiency.
A small packet may receive a few of the Walsh codes,
and the remaining Walsh codes can be used by another
user, improving overall system capacity
Code Space

TDM
TDM/CDM
Waste
Used by other
traffic
Required
Required
Frame Duration
Modulation and Coding
Schemes (MCS)
Rate (kbps)
38.4
76.8
153.6
307.2
614.4
307.2
614.4
1,228.8
921.6
1,843.2
1,228.8
2,457.6
Slots Per
Packet
16
8
4
2
1
4
2
1
2
1
2
1
Packet size
(Bits)
1,024
1,024
1,024
1,024
1,024
2,048
2,048
2,048
3,072
3,072
4,096
4,096
Turbo Code
Rate
1/5
1/5
1/5
1/5
1/3
1/3
1/3
1/3
1/3
1/3
1/3
1/3
Modulation
QPSK
QPSK
QPSK
QPSK
QPSK
QPSK
QPSK
QPSK
8-PSK
8-PSK
16-QAM
16-QAM
Effective
Code Rate
1/48
1/24
1/12
1/6
1/3
16/99
16/49
2/3
16/49
2/3
16/49
2/3
AMC Fixed Threshold Method

AMC has a set of n MCS levels
{M 0 ,..., M n 1}

MCS set has a corresponding throughput vs. av. Channel SINR
denoted by
{Ti ( ), i  0,..., n  1}

These throughput values can be graphically represented, where the
curves intersect with each other.
SINR at intersection points are threshold values, denoted by
{ 0  ,  1 ,...,  n1 ,  n  }
AMC Fixed Threshold Method


These threshold points partition the range of
SINR into n regions, denoted by
[ i ,  i 1 ) for i  0,..., n  1
The kth MCS, namely Mk is assigned to the
region
[ i ,  i 1 )
if the following condition is satisfied
Tk ( )  T j ( ), j  k ,   [ i ,  i 1 ).
AMC Fixed Threshold Method

With this corresponding between the MCS’s and the
average SINR, Mk is selected for the next frame if the
average channel SINR in the current frame lies in the
SINR
region [ i ,  i 1 )
MCSi
Threshold
values, fixed
Channel
Estimate
γi
}
Disadvantages of TM


Error in the estimation of average channel
SINR can cause inappropriate selection of
MCS resulting in a degradation of the
performance
The threshold values associated with the MCSs
are not jointly optimized based on the
overall stochastic behavior of the users’ SINR
 degrade the efficiency of the overall system
resources.
Optimized Method
The threshold values associated with the MCSs are jointly
optimized based on the overall stochastic behavior of the
users’ SINRs  The goal is:
Higher overall throughput
SINR
MCSi
Threshold values,
optimized
Channel
Estimate
γi
}
Percentage of users served by a MCS
Pi  Pr{SINR [ SINRi , SINRi 1 )},


P1 + P2 +  + PN = 1
The SINR is a random variable (r.v.) achieved
by an arbitrary user at a given instant
We prove ordinarily that Pi is a discrete
random function that is dependent on the
users’ joint SINR cumulative distribution
function (CDF) and data rate granularity (N).
Throughput Optimization

Consider the event {SINR  x} where x is a real
number in the interval [0,). We write the
probability of this event as
F ( x)  Pr(SINR  x),

0  x  .
The function F(x) is the CDF of the r.v. SINR. In our
case, F(0) ≡ F() = 0 and F(SINRN+1) ≡ F() =
1. Thus, we can rewrite Pi as
Pi  Pr( SINRi  SINR  SINRi 1 )  Pr( SINR  SINRi 1 )  Pr( SINR  SINRi )
 Pr( SINR  SINRi 1 )  Pr( SINR  SINRi 1 )  Pr( SINR  SINRi )  Pr( SINR  SINRi )
Throughput Optimization

In terms of discrete CDF functions, Pi is
expressed as
Pi  F (SINRi 1 )  F (SINRi )  Pr( SINR  SINRi 1 )  Pr( SINR  SINRi )
SINRi thresholds:
SINRi
thresholds for variable bit rates: The SINRi threshold associated
with a MCSi is determined by
( Eb / No )i
SINRi 
Gp
Bit rate can be calculated
GP can be calculated
RCi is given by
Ri  RCi D p N Ci /T ,
Gp 
N CHIP
W

,
Ri RCi D p N Ci
RCi  RTC i / RPLi
SINRi 
Eb / No i RTCi DP NCi
RPLi NCHIP
Throughput calculations:
i represents the throughput that can be transmitted by a base station
i  Ri NTS ,
Let also eff_i represents the effective throughput that can be received
by the users who can achieve an SINR in the range [SINRi, SINRi+1)
eff _ i  i Pi ,
D N
  P TS
T
 RTCi NCi


F (SINRi 1 )  F (SINRi )  Pr( SINR  SINRi 1)  Pr( SINR  SINRi )


RPLi
i 1 

N
Simulation Model


Assume there are M possible users’ realizations over a certain
period of time, then P is a member in an M-size set {Pj: j = 1,
2, … , M}.
We consider 19 3-sector cells located on a hexagonal grid and
used the SINR calculations as shown
12
13
14
11
4
5
15
3
1
6
16
10
9
2
7
17
8
19
18
Effective throughput
Effective aggregate throughput for 100 different realizations for users’
locations selected at random within the cell range
User Data Rate vs. Users Density
Effective aggregate throughput as a function of the users density.
Here the radius was changing inversely proportional to the users
density.
Intelligent Network QoS
Validation Protocol
Intelligent Network QoS
Validation Protocol Engine
Network
QoS
MAC/Network QoS Mapping Layer
MAC Layer
Res. Alloc.
Physical Layer
Interaction between the Physical/MAC layers and the
Network QoS validation protocol
Intelligent Network QoS Validation
Protocol (contd.)
Application
Bandwidth
Delay
Jitter
Loss
MAC/Network QoS mapping
MCSi
candidates
MCS1
MCS2
…
MCSi
other
QoS classes
Traffic class
Characteristics
Conventional
Low delay, low date rate, sensitive to
delay variations, e.g. video
conferencing
Streaming
Less sensitive to delay, may require
high bandwidth, e.g. live coverage of
sports
Interactive
Bursty, variable bandwidth requirement,
moderate data loss, e.g. email, Telnet
Background
High tolerant to delay and data loss,
high variable bandwidth, background
file downloading
Intelligent Network QoS
Validation Protocol (contd.)

At the MAC layer


Network resources are allocated based on
the MAC QoS
At the network layer

Network resources are validated based on
the network QoS requirements, which are
traffic type dependent
Cross Layer Design

Goal





Provide efficient methods of allocating network
resources and applications
QoS support in all layers
Dynamic protocol design
Jointly optimize the network performance
Tradeoff

Performance versus complexity and scalability
Cross Layer Design (contd.)

Why?


There exists direct coupling between
physical layer and upper protocol layers
Several upper layer protocols do not get
advantage of the wireless medium
information available within the physical
and MAC layer.
Intelligent Network QoS Protocols

At the network layer

Intelligent network QoS validation protocol

Wireless QoS based routing protocol
Intelligent Network QoS
Validation Protocol (contd.)

Approach




Model the system as an objective function to be
maximized based on network QoS parameters
Not to violate the MAC QoS constraints.
Optimizing the objective function is an NPComplete problem
Use heuristic techniques




Genetic algorithms
Fuzzy logic
Simulated annealing
Etc.
Wireless QoS Based Routing
Protocol

Features





Low overhead control traffic
On demand operation
Optimal route computation
Network configuration change
Distributed operation
Wireless QoS Based Routing
Protocol (contd.)

Communication



An optimum size of the protocol update control
messages
The frequency of neighbor update messages
Modified version of the route discovery
protocol implemented by most of the distance
vector routing protocol
High Level Protocol Design

QoS based routing protocol suite high level
design

Optimization of resource usage


Advertise resource information to all neighboring nodes
Graceful network performance degradation


Restrict the update message flooding to the neighboring
nodes only
New neighboring information exchange policy techniques
using some heuristic algorithms
High Level Protocol Design
(contd.)

Adaptive routing protocol


Granularity of the routing decision


In case of a change in the network or node
resources, update messages will be triggered
based on our neighboring information
exchange policy
Source and destination-based routing
approach: the traffic between a given source
and destination will be routed over the same
route.
On the fly determination of feasible paths
High Level Protocol Design
(contd.)

Performance objectives while computing QoSbased paths


Achieve better network throughput by achieving low
route-request blocking probability while providing QoS
based paths
Optimum routing overhead during the
computation, communication, and routing
information storage

Minimize the routing overhead caused by the rapid
change of some of the network resources as well as the
call setup frequency
High Level Protocol Design
(contd.)

Route computation


Use Kalman-filter or equivalent heuristic
techniques in order to determine the best path
Routing information storage

Maintain a partial routing table
Conclusion

Improve the overall throughput of the
wireless network




SINR AMC MCS Compute the best threshold
Use cross layer design technique
Design a new protocol at the network layer to
assure better QoS based on the traffic type
Design a new QoS based routing protocol


Less control message overhead
Improve call blocking probability
Future Work



Simulation study using OPNET
Performance evaluation of the
developed protocols (control message
overhead, CBP, etc.)
Comparison study of the proposed QoS
routing protocol with the existing
protocols