College of Engineering 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

9/5/2015 2/56 Outline Wireless Networks History Resource Management Issues Call Admission Control in 3G UMTS WCDMA Systems Dynamic Channel Assignment in IEEE Systems Future Work Wireless Networks History Resource Management Issues Call Admission Control in 3G UMTS WCDMA Systems Dynamic Channel Assignment in IEEE Systems Future Work

9/5/2015 3/56 Wireless Networks History (1/8) Mobile Communications Third Generation Partnership Project (3GPP) UMTS / WCDMA Overview IEEE WLAN Overview Mobile Communications Third Generation Partnership Project (3GPP) UMTS / WCDMA Overview IEEE WLAN Overview

9/5/2015 4/56 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

9/5/2015 5/56 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

9/5/2015 6/56 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

9/5/2015 7/56 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)

9/5/2015 8/56 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)

9/5/2015 9/56 Wireless Networks History (7/8) IEEE committee formed in 1990 for wireless LANs (WLAN) Unlicensed industrial, scientific, and medical bands – 915 MHz, 2.4 GHz, and 5 GHz a (1999) - 5 GHz, 54 Mbps b (1999) GHz, 11 Mbps g (2003) GHz, 54 Mbps IEEE committee formed in 1990 for wireless LANs (WLAN) Unlicensed industrial, scientific, and medical bands – 915 MHz, 2.4 GHz, and 5 GHz a (1999) - 5 GHz, 54 Mbps b (1999) GHz, 11 Mbps g (2003) GHz, 54 Mbps

9/5/ /56 Wireless Networks History (8/8) WLAN Data Transmission DSSS (Direct Sequence Spread Spectrum) FHSS (Frequency Sequence Spread Spectrum) MAC uses CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance) WLAN Data Transmission DSSS (Direct Sequence Spread Spectrum) FHSS (Frequency Sequence Spread Spectrum) MAC uses CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance)

9/5/ /56 Resource 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

9/5/ /56 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

9/5/ /56 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

9/5/ /56 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

9/5/ /56 Global CAC (3/6) is the minimum signal-to-noise ratio is the maximum signal power the number of users in BS i for given service g Feasible call configuration is a set of calls n satisfying the above equations, for all services g = 1,…,G This is for perfect power control (PPC). where

9/5/ /56 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.

9/5/ /56 Global CAC (5/6) Average Interference for i = 1,…,M, g = 1,…,G. Average Interference for i = 1,…,M, g = 1,…,G.

9/5/ /56 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

9/5/ /56 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

9/5/ /56 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

9/5/ /56 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 : vector of blocking probabilities : matrix of call arrival rates

9/5/ /56 Optimized Local CAC (4/6) max subject to for i = 1, …, M. 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.

9/5/ /56 Optimized Local CAC (5/6) max subject to for i = 1, …, M. Theoretical Throughput

9/5/ /56 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

9/5/ /56 Simulation 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, σ s = 6 dB Bit energy to interference ratio threshold, τ = 7.5 dB Interference to background noise ratio, I 0 /N 0 = 10 dB Activity factor, v = 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, σ s = 6 dB Bit energy to interference ratio threshold, τ = 7.5 dB Interference to background noise ratio, I 0 /N 0 = 10 dB Activity factor, v = 0.375

9/5/ /56 Simulation Results Processing gain, W/Rg dB for spreading factor = dB for spreading factor = dB for spreading factor = dB for spreading factor = 4 Bit energy to interference ratio threshold, τ = 7.5 dB Interference to background noise ratio, I 0 /N 0 = 10 dB Activity factor, v = Processing gain, W/Rg dB for spreading factor = dB for spreading factor = dB for spreading factor = dB for spreading factor = 4 Bit energy to interference ratio threshold, τ = 7.5 dB Interference to background noise ratio, I 0 /N 0 = 10 dB Activity factor, v = 0.375

9/5/ /56 Three Mobility Models probability that a call with service g in progress in cell i departs from the network. 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 Mobility Low Mobility High Mobility

9/5/ /56 Simulated Network Capacity

9/5/ /56 UMTS Throughput Optimization with SF = 256

9/5/ /56 Average Throughput in each cell for SF = 256

9/5/ /56 UMTS Throughput Optimization with SF = 64

9/5/ /56 Average Throughput in each cell for SF = 64

9/5/ /56 UMTS Throughput Optimization with SF = 16

9/5/ /56 Average Throughput in each cell for SF = 16

9/5/ /56 UMTS Throughput Optimization with SF = 4

9/5/ /56 Average Throughput in each cell for SF = 4

9/5/ /56 Conclusions of CAC Different spreading factors and various mobility scenarios Computational complexity for global CAC using average and actual interference is O(MG) and O(M 2 G) 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(M 2 G) Optimized local CAC is O(1) Performance difference is less than 5%

9/5/ /56 Dynamic Channel Assignment in IEEE 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

9/5/ /56 Channel 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

9/5/ /56 Channel Interference

9/5/ /56 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

9/5/ /56 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

9/5/ /56 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)

9/5/ /56 Analysis of Simulation Results (1/10) Signal level maps

9/5/ /56 Analysis of Simulation Results (2/10) Signal level maps

9/5/ /56 Analysis of Simulation Results (3/10) Dynamic Channel Assignment for WLAN with 4 APs

9/5/ /56 Analysis of Simulation Results (4/10) Channel Assignment map for WLAN with 4 APs

9/5/ /56 Analysis of Simulation Results (5/10) Dynamic Channel Assignment for WLAN with 9 APs

9/5/ /56 Analysis of Simulation Results (6/10) Channel Assignment map for WLAN with 9 APs

9/5/ /56 Analysis of Simulation Results (7/10) Dynamic Channel Assignment for WLAN with 16 APs

9/5/ /56 Analysis of Simulation Results (8/10) Channel Assignment map for WLAN with 16 APs

9/5/ /56 Analysis of Simulation Results (9/10) Dynamic Channel Assignment for WLAN with 25 APs

9/5/ /56 Analysis of Simulation Results (10/10) Channel Assignment map for WLAN with 25 APs

9/5/ /56 Conclusions 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

9/5/ /56 Future 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

9/5/ /56 Thank You!! Questions?