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Resource Management in Wireless Networks

Resource Management in Wireless Networks. Anurag Arepally Major Adviser : Dr. Robert Akl Department of Computer Science and Engineering. Outline. Wireless Networks History Resource Management Issues Call Admission Control in 3G UMTS WCDMA Systems

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Resource Management in Wireless Networks

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  1. Resource Management inWireless Networks Anurag Arepally Major Adviser : Dr. Robert Akl Department of Computer Science and Engineering

  2. Outline • Wireless Networks History • Resource Management Issues • Call Admission Control in 3G UMTS WCDMA Systems • Dynamic Channel Assignment in IEEE 802.11 Systems • Future Work

  3. Wireless Networks History(1/8) • Mobile Communications • Third Generation Partnership Project (3GPP) • UMTS / WCDMA Overview • IEEE 802.11 • WLAN Overview

  4. 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

  5. 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

  6. 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

  7. Wireless Networks History(5/8) • Universal mobile telecommunications system (UMTS) • Proposed by ETSI • Backward compatible with 2G networks • UMTS Terrestrial Radio Access (UTRA)

  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)

  9. 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

  10. 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)

  11. 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

  12. 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

  13. Global CAC(1/6) • Multi-cell UMTS networks • Feasible call configuration • Call arrival and admission module • Average interference • Actual interference • Call removal module

  14. 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

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

  16. Global CAC (4/6) • Call arrival and admission module for i = 1,…,M, g = 1,…,G.

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

  18. Global CAC (6/6) • Actual Interference for i = 1,…,M, g = 1,…,G . • Call removal module

  19. 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

  20. 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

  21. Optimized Local CAC (3/6) where is the Erlang traffic in cell i with service g. • Calculation of N where : vector of blocking probabilities : matrix of call arrival rates

  22. Optimized Local CAC (4/6) The above optimization problem is solved offline to obtain the values of N. max subject to for i = 1, …, M .

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

  24. Optimized Local CAC (6/6) • Simulator model • Call arrival and admission module • Call removal module

  25. 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, 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

  26. Simulation 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

  27. Three Mobility Models No Mobility probability that a call with service g in progress in cell i remains in cell i after completing its dwell time. Low Mobility 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. probability that a call with service g in progress in cell i departs from the network. High Mobility

  28. Simulated Network Capacity

  29. UMTS Throughput Optimization with SF = 256

  30. Average Throughput in each cell for SF = 256

  31. UMTS Throughput Optimization with SF = 64

  32. Average Throughput in each cell for SF = 64

  33. UMTS Throughput Optimization with SF = 16

  34. Average Throughput in each cell for SF = 16

  35. UMTS Throughput Optimization with SF = 4

  36. Average Throughput in each cell for SF = 4

  37. 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(M2G) • Optimized local CAC is O(1) • Performance difference is less than 5%

  38. Dynamic Channel Assignment in IEEE 802.11 systems • Channel interference • Overlapping Channel interference factor • Dynamic channel assignment • Analysis of simulation results • Conclusions

  39. Channel Interference • Two Types • Adjacent channel interference • Co-channel interference • Overlapping channel interference factor

  40. Channel Interference

  41. 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

  42. Dynamic Channel Assignment(2/3) • Dynamic channel assignment problem is given as : min subject to if otherwise, for

  43. Dynamic Channel Assignment(3/3) • We use two versions for analysis of our algorithm • Algorithm I (pick rand) • Algorithm II (pick first)

  44. Analysis of Simulation Results(1/10) • Signal level maps

  45. Analysis of Simulation Results(2/10) • Signal level maps

  46. Analysis of Simulation Results (3/10) • Dynamic Channel Assignment for WLAN with 4 APs

  47. Analysis of Simulation Results (4/10) • Channel Assignment map for WLAN with 4 APs

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

  49. Analysis of Simulation Results (6/10) • Channel Assignment map for WLAN with 9 APs

  50. Analysis of Simulation Results (7/10) • Dynamic Channel Assignment for WLAN with 16 APs

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