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College of Engineering
Resource Management in
Wireless Networks
Resource Management in
Wireless Networks
Anurag Arepally
Major Adviser : Dr. Robert Akl
Department of Computer Science and Engineering
Anurag Arepally
Major Adviser : Dr. Robert Akl
Department of Computer Science and Engineering
04/19/23 2/56
OutlineOutline
• Wireless Networks History
• Resource Management Issues
• Call Admission Control in 3G UMTS WCDMA Systems
• Dynamic Channel Assignment in IEEE 802.11 Systems
• Future Work
• Wireless Networks History
• Resource Management Issues
• Call Admission Control in 3G UMTS WCDMA Systems
• Dynamic Channel Assignment in IEEE 802.11 Systems
• Future Work
04/19/23 3/56
Wireless Networks History(1/8)
Wireless Networks History(1/8)
• Mobile Communications
• Third Generation Partnership Project (3GPP)
• UMTS / WCDMA Overview
• IEEE 802.11
• WLAN Overview
• Mobile Communications
• Third Generation Partnership Project (3GPP)
• UMTS / WCDMA Overview
• IEEE 802.11
• WLAN Overview
04/19/23 4/56
Wireless Networks History(2/8)
Wireless Networks History(2/8)
• Mobile Communications
• Access Techniques
• Early 90’s saw the introduction of two access techniques
• TDMA Interim Standard 54 and IS-136 (updated version)
• CDMA IS-95 (code division multiple access)
• 3GPP introduces WCDMA (wideband code division multiple access) based on CDMA
• Mobile Communications
• Access Techniques
• Early 90’s saw the introduction of two access techniques
• TDMA Interim Standard 54 and IS-136 (updated version)
• CDMA IS-95 (code division multiple access)
• 3GPP introduces WCDMA (wideband code division multiple access) based on CDMA
04/19/23 5/56
Wireless Networks History(3/8)
Wireless Networks History(3/8)
• 3GPP formed in late 90’s
• 3GPP develops standards for 3G networks based on global system for mobile communications (GSM)
• 3GPP2 develops standards for 3G networks based on CDMA IS-95
• 3GPP formed in late 90’s
• 3GPP develops standards for 3G networks based on global system for mobile communications (GSM)
• 3GPP2 develops standards for 3G networks based on CDMA IS-95
04/19/23 6/56
Wireless Networks History(4/8)
Wireless Networks History(4/8)
• 3GPP Releases
• Release ’99
• Voice and video use circuit switched network
• SMS, WAP, and MMS use packet switched network
• Release 5 introduced all IP-network
• Release 6 – mobile TV
• Release 7 and long term evolution
• 3GPP Releases
• Release ’99
• Voice and video use circuit switched network
• SMS, WAP, and MMS use packet switched network
• Release 5 introduced all IP-network
• Release 6 – mobile TV
• Release 7 and long term evolution
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Wireless Networks History(5/8)
Wireless Networks History(5/8)
• Universal mobile telecommunications system (UMTS)
• Proposed by ETSI
• Backward compatible with 2G networks
• UMTS Terrestrial Radio Access (UTRA)
• Universal mobile telecommunications system (UMTS)
• Proposed by ETSI
• Backward compatible with 2G networks
• UMTS Terrestrial Radio Access (UTRA)
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Wireless Networks History(6/8)
Wireless Networks History(6/8)
• WCDMA is the preferred access technique for 3G UMTS networks
• Main features of WCDMA
• Based on direct sequence CDMA
• Frequency spectrum of 5 MHz
• Multiplexing is done both in frequency (FDD) and time (TDD)
• WCDMA is the preferred access technique for 3G UMTS networks
• Main features of WCDMA
• Based on direct sequence CDMA
• Frequency spectrum of 5 MHz
• Multiplexing is done both in frequency (FDD) and time (TDD)
04/19/23 9/56
Wireless Networks History(7/8)
Wireless Networks History(7/8)
• IEEE 802.11 committee formed in 1990 for wireless LANs (WLAN)
• Unlicensed industrial, scientific, and medical bands – 915 MHz, 2.4 GHz, and 5 GHz
• 802.11a (1999) - 5 GHz, 54 Mbps
• 802.11b (1999) - 2.4 GHz, 11 Mbps
• 802.11g (2003) - 2.4 GHz, 54 Mbps
• IEEE 802.11 committee formed in 1990 for wireless LANs (WLAN)
• Unlicensed industrial, scientific, and medical bands – 915 MHz, 2.4 GHz, and 5 GHz
• 802.11a (1999) - 5 GHz, 54 Mbps
• 802.11b (1999) - 2.4 GHz, 11 Mbps
• 802.11g (2003) - 2.4 GHz, 54 Mbps
04/19/23 10/56
Wireless Networks History(8/8)
Wireless Networks History(8/8)
• WLAN
• Data Transmission
• DSSS (Direct Sequence Spread Spectrum)
• FHSS (Frequency Sequence Spread Spectrum)
• 802.11 MAC uses CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance)
• WLAN
• Data Transmission
• DSSS (Direct Sequence Spread Spectrum)
• FHSS (Frequency Sequence Spread Spectrum)
• 802.11 MAC uses CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance)
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Resource Management IssuesResource Management Issues
• Capacity of the cellular and wireless networks
• Quality of Service (QoS)
• Grade of Service (GoS)
• Different models and approaches have been proposed
• Demand for wireless internet access
• Capacity of the cellular and wireless networks
• Quality of Service (QoS)
• Grade of Service (GoS)
• Different models and approaches have been proposed
• Demand for wireless internet access
04/19/23 12/56
Call Admission Control(CAC)
Call Admission Control(CAC)
• 3G UMTS WCDMA networks
• Voice, video, pictures form different classes of services
• Global CAC
• Optimized local CAC
• Modeling and Simulations
• Conclusions
• 3G UMTS WCDMA networks
• Voice, video, pictures form different classes of services
• Global CAC
• Optimized local CAC
• Modeling and Simulations
• Conclusions
04/19/23 13/56
Global CAC(1/6)
Global CAC(1/6)
• Multi-cell UMTS networks
• Feasible call configuration
• Call arrival and admission module
• Average interference
• Actual interference
• Call removal module
• Multi-cell UMTS networks
• Feasible call configuration
• Call arrival and admission module
• Average interference
• Actual interference
• Call removal module
04/19/23 14/56
Global CAC(2/6)
Global CAC(2/6)
• Feasible call configuration
for i = 1, …, M, g = 1, …, G,
where W bandwidth
Rg information rate in bits / s
Sg received signal
Vg activity factor
No noise spectral density
• Feasible call configuration
for i = 1, …, M, g = 1, …, G,
where W bandwidth
Rg information rate in bits / s
Sg received signal
Vg activity factor
No noise spectral density
, , ,1 1, 1
,
g
gb
G M Go g
o i g g j g g ji g gg j j i g
S
RE
I SN n v n v v
Wκ
= = ≠ =
⎛ ⎞=⎜ ⎟
⎡ ⎤⎝ ⎠ + + −⎢ ⎥⎣ ⎦∑ ∑ ∑
04/19/23 15/56
Global CAC (3/6)
Global CAC (3/6)
( )
0
1 ggeff
g g g
RWc
R S Nτ⎡ ⎤
= −⎢ ⎥⎢ ⎥⎣ ⎦
is the minimum signal-to-noise ratio
gτ
is the maximum signal power
Sg
the number of users in BS i for given service g
,ni g
( ), , ,
1 1, 1
G M Gg
i g g j g g ji g g effg j j i g
n n cν ν κ ν= = ≠ =
+ − ≤∑ ∑ ∑
Feasible call configuration is a set of calls n satisfyingFeasible call configuration is a set of calls n satisfyingthe above equations, for all services g = 1,…,Gthe above equations, for all services g = 1,…,G
This is for perfect power control (PPC).This is for perfect power control (PPC).
wherewhere
04/19/23 16/56
Global CAC (4/6)
Global CAC (4/6)
• Call arrival and admission module
for i = 1,…,M, g = 1,…,G.
• Call arrival and admission module
for i = 1,…,M, g = 1,…,G.
( ) ( ) ( ) ( ), , , ,g
i g i g i g effC t n t I t c= + ≤
( ) ( ) ( ), , , ,i g i g i gt t v tρ λ= +
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Global CAC (5/6)
Global CAC (5/6)
• Average Interference
for i = 1,…,M, g = 1,…,G.
• Average Interference
for i = 1,…,M, g = 1,…,G.
, , ,1
,M
i g j g ji gj
I n F=
=∑
( ) ( ) ( ) [ ], , ,1
, , ,M
i g i g j gj
C t n t n t F j i g=
= + ∑
04/19/23 18/56
Global CAC (6/6)
Global CAC (6/6)
• Actual Interference
for i = 1,…,M, g = 1,…,G .
• Call removal module
• Actual Interference
for i = 1,…,M, g = 1,…,G .
• Call removal module
[ ]( ) [ ]( ) ( ),, , , , 1 ,ji g kU j i g t U j i g t U= − +
( ) ( ) [ ]( ), ,1,
, , ,M
i g i gj j i
C t n t U j i g t= ≠
= + ∑
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Optimized Local CAC(1/6)
Optimized Local CAC(1/6)
• Admissible call configuration
• Calculation of N
• Theoretical Throughput
• Simulator Model
• Call arrival and admission module
• Call removal module
• Simulation Results
• Admissible call configuration
• Calculation of N
• Theoretical Throughput
• Simulator Model
• Call arrival and admission module
• Call removal module
• Simulation Results
04/19/23 20/56
Optimized Local CAC (2/6)
Optimized Local CAC (2/6)
• Admissible call configuration
for i = 1,…,M and g = 1,…,G,
where denotes maximum # of calls
with service g in cell i.
• Blocking probability for cell i with service g is
• Admissible call configuration
for i = 1,…,M and g = 1,…,G,
where denotes maximum # of calls
with service g in cell i.
• Blocking probability for cell i with service g is
, ,i g i gn N≤,i gN
( )
,
,
,
,, , ,
,0
!, ,
!
i g
i g
N
i g
i gi g i g i g N
ki g
k
T
NB B T N
T
k=
= =
∑
04/19/23 21/56
Optimized Local CAC (3/6)
Optimized Local CAC (3/6)
where is the Erlang traffic
in cell i with service g.
• Calculation of N
where
where is the Erlang traffic
in cell i with service g.
• Calculation of N
where
( ),
,1i g
i
ii g
Tq
ρ
μ=
−
( ) ( ) ( ){ }, , , , ,1 1
, , 1 ,M G
i g i g i g i g i gi g
H B Bρ λ λ ρ λ= =
= − − −∑∑B
: vector of blocking probabilities
: matrix of call arrival ratesλB
04/19/23 22/56
Optimized Local CAC (4/6)
Optimized Local CAC (4/6)
maxN
subject to , ,( , ) ,i g i g gB T N β≤
( ), , ,
1 1, 1
,G M G
gi g g j g g ji g g eff
g j j i g
N v N v v cκ= = ≠ =
+ − ≤∑ ∑ ∑
for i = 1, …, M .
( , ),H , ρ λB
The above optimization problem is solved
offline to obtain the values of N.
The above optimization problem is solved
offline to obtain the values of N.
04/19/23 23/56
Optimized Local CAC (5/6)
Optimized Local CAC (5/6)
maxλ , N
subject to, ,( , ) ,i g i g gB T N β≤
( ), , ,
1 1, 1
,G M G
gi g g j g g ji g g eff
g j j i g
N v N v v cκ= = ≠ =
+ − ≤∑ ∑ ∑
for i = 1, …, M .
( , ),H , ρ λB
• Theoretical Throughput• Theoretical Throughput
04/19/23 24/56
Optimized Local CAC (6/6)
Optimized Local CAC (6/6)
• Simulator model
• Call arrival and admission module
• Call removal module
• Simulator model
• Call arrival and admission module
• Call removal module
04/19/23 25/56
SimulationSimulation
• Network configuration
• COST-231 propagation model
• Carrier frequency = 1800 MHz
• Average base station height = 30 meters
• Average mobile height = 1.5 meters
• Path loss coefficient, m = 4
• Shadow fading standard deviation, σs = 6 dB
• Bit energy to interference ratio threshold, τ = 7.5 dB
• Interference to background noise ratio, I0/N0 = 10 dB
• Activity factor, v = 0.375
• Network configuration
• COST-231 propagation model
• Carrier frequency = 1800 MHz
• Average base station height = 30 meters
• Average mobile height = 1.5 meters
• Path loss coefficient, m = 4
• Shadow fading standard deviation, σs = 6 dB
• Bit energy to interference ratio threshold, τ = 7.5 dB
• Interference to background noise ratio, I0/N0 = 10 dB
• Activity factor, v = 0.375
04/19/23 26/56
Simulation ResultsSimulation Results
• Processing gain, W/Rg
• 24.08 dB for spreading factor = 256
• 18.06 dB for spreading factor = 64
• 12.04 dB for spreading factor = 16
• 6.02 dB for spreading factor = 4
• Bit energy to interference ratio threshold, τ = 7.5 dB
• Interference to background noise ratio, I0/N0 = 10 dB
• Activity factor, v = 0.375
• Processing gain, W/Rg
• 24.08 dB for spreading factor = 256
• 18.06 dB for spreading factor = 64
• 12.04 dB for spreading factor = 16
• 6.02 dB for spreading factor = 4
• Bit energy to interference ratio threshold, τ = 7.5 dB
• Interference to background noise ratio, I0/N0 = 10 dB
• Activity factor, v = 0.375
04/19/23 27/56
Three Mobility ModelsThree Mobility Models
,ii gq
probability that a call with service g in progress in cell i departs from the network.
,ij gq
,i gq
probability that a call with service g in progress in cell i remains in cell i after completing its dwell time.
probability that a call with service g in progress in cell i after completing its dwell time goes to cell j. It’s equaled zero (=0) if cell i and j are not adjacent.
No MobilityNo Mobility
Low MobilityLow Mobility
High MobilityHigh Mobility
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Simulated Network CapacitySimulated Network Capacity
04/19/23 29/56
UMTS Throughput Optimization with SF = 256
UMTS Throughput Optimization with SF = 256
04/19/23 30/56
Average Throughput in each cell for SF = 256
Average Throughput in each cell for SF = 256
04/19/23 31/56
UMTS Throughput Optimization with SF = 64
UMTS Throughput Optimization with SF = 64
04/19/23 32/56
Average Throughput in each cell for SF = 64
Average Throughput in each cell for SF = 64
04/19/23 33/56
UMTS Throughput Optimization with SF = 16
UMTS Throughput Optimization with SF = 16
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Average Throughput in each cell for SF = 16
Average Throughput in each cell for SF = 16
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UMTS Throughput Optimization with SF = 4
UMTS Throughput Optimization with SF = 4
04/19/23 36/56
Average Throughput in each cell for SF = 4
Average Throughput in each cell for SF = 4
04/19/23 37/56
Conclusions of CACConclusions of CAC
• Different spreading factors and various mobility scenarios
• Computational complexity for global CAC using average and actual interference is O(MG) and O(M2G)
• Optimized local CAC is O(1)
• Performance difference is less than 5%
• Different spreading factors and various mobility scenarios
• Computational complexity for global CAC using average and actual interference is O(MG) and O(M2G)
• Optimized local CAC is O(1)
• Performance difference is less than 5%
04/19/23 38/56
Dynamic Channel Assignment in IEEE 802.11 systems
Dynamic Channel Assignment in IEEE 802.11 systems
• Channel interference
• Overlapping Channel interference factor
• Dynamic channel assignment
• Analysis of simulation results
• Conclusions
• Channel interference
• Overlapping Channel interference factor
• Dynamic channel assignment
• Analysis of simulation results
• Conclusions
04/19/23 39/56
Channel InterferenceChannel Interference
• Two Types
• Adjacent channel interference
• Co-channel interference
• Overlapping channel interference factor
• Two Types
• Adjacent channel interference
• Co-channel interference
• Overlapping channel interference factor
04/19/23 40/56
Channel InterferenceChannel Interference
04/19/23 41/56
Dynamic Channel Assignment(1/3)
Dynamic Channel Assignment(1/3)
be the set of neighboring APs to AP i
is the overlapping channel factor
is the distance between AP i and AP j
is the channel assigned to AP i
is the interference that AP j causes on AP i
is the total number of available channels
is a function that captures the attenuation loss
is a pathloss exponent
is the transmit power of AP i
is the cardinality of A_i
is the overlapping channel interference factor
between AP i and AP j
be the set of neighboring APs to AP i
is the overlapping channel factor
is the distance between AP i and AP j
is the channel assigned to AP i
is the interference that AP j causes on AP i
is the total number of available channels
is a function that captures the attenuation loss
is a pathloss exponent
is the transmit power of AP i
is the cardinality of A_i
is the overlapping channel interference factor
between AP i and AP j
iΑ
ijd
iF
ijI
iP
iQ
ijw
c
kLoss
m
04/19/23 42/56
Dynamic Channel Assignment(2/3)
Dynamic Channel Assignment(2/3)
• Dynamic channel assignment problem is given as :
min
subject to
if
otherwise,
for
• Dynamic channel assignment problem is given as :
min
subject to
if
otherwise,
for
1 | |ij i jw F F c= − −
1
,iQ
ijj
I=∑
iF
( ),,
ij jij
ij
w PI
Loss d m=
,ij ∈Α { }1,..., .iF K∈
0,ijw ≥0=
04/19/23 43/56
Dynamic Channel Assignment(3/3)
Dynamic Channel Assignment(3/3)
• We use two versions for analysis of our algorithm
• Algorithm I (pick rand)
• Algorithm II (pick first)
• We use two versions for analysis of our algorithm
• Algorithm I (pick rand)
• Algorithm II (pick first)
04/19/23 44/56
Analysis of Simulation Results(1/10)
Analysis of Simulation Results(1/10)
• Signal level maps• Signal level maps
04/19/23 45/56
Analysis of Simulation Results(2/10)
Analysis of Simulation Results(2/10)
• Signal level maps• Signal level maps
04/19/23 46/56
Analysis of Simulation Results (3/10)
Analysis of Simulation Results (3/10)
• Dynamic Channel Assignment for WLAN with 4 APs
• Dynamic Channel Assignment for WLAN with 4 APs
04/19/23 47/56
Analysis of Simulation Results (4/10)
Analysis of Simulation Results (4/10)
• Channel Assignment map for WLAN with 4 APs
• Channel Assignment map for WLAN with 4 APs
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Analysis of Simulation Results (5/10)
Analysis of Simulation Results (5/10)
• Dynamic Channel Assignment for WLAN with 9 APs
• Dynamic Channel Assignment for WLAN with 9 APs
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Analysis of Simulation Results (6/10)
Analysis of Simulation Results (6/10)
• Channel Assignment map for WLAN with 9 APs
• Channel Assignment map for WLAN with 9 APs
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Analysis of Simulation Results (7/10)
Analysis of Simulation Results (7/10)
• Dynamic Channel Assignment for WLAN with 16 APs
• Dynamic Channel Assignment for WLAN with 16 APs
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Analysis of Simulation Results (8/10)
Analysis of Simulation Results (8/10)
• Channel Assignment map for WLAN with 16 APs
• Channel Assignment map for WLAN with 16 APs
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Analysis of Simulation Results (9/10)
Analysis of Simulation Results (9/10)
• Dynamic Channel Assignment for WLAN with 25 APs
• Dynamic Channel Assignment for WLAN with 25 APs
04/19/23 53/56
Analysis of Simulation Results (10/10)
Analysis of Simulation Results (10/10)
• Channel Assignment map for WLAN with 25 APs
• Channel Assignment map for WLAN with 25 APs
04/19/23 54/56
ConclusionsConclusions
• WLAN consisting of 4, 9, 16, and 25 AP s
• Default factory settings ( all AP’s are assigned same channel number)
• Algorithm I (pick rand) and II (pick first)
• Our results show an improvement by a factor of 4 or 6 dBm
• WLAN consisting of 4, 9, 16, and 25 AP s
• Default factory settings ( all AP’s are assigned same channel number)
• Algorithm I (pick rand) and II (pick first)
• Our results show an improvement by a factor of 4 or 6 dBm
04/19/23 55/56
Future workFuture work
• 4G the next revolutionary technology and WLAN complementing WCDMA will lead to integrated wireless networks.
• Dynamic load balancing
• 4G the next revolutionary technology and WLAN complementing WCDMA will lead to integrated wireless networks.
• Dynamic load balancing
04/19/23 56/56
Thank You!!Thank You!!
Questions?Questions?