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Present & Future: Current Progress In Wireless & Communications Research Group

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"Present & Future: Current Progress In Wireless & Communications Research Group", ANGKASA Seminar Series 2/2012, 4th June, 2012, UKM

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Present & Future: Current Progress In Wireless & Communications Research Group

  1. 1. ANGKASA Seminar Series 2/2012 PRESENT & FUTURE: CURRENT PROGRESS IN WIRELESS & COMMS. RESEARCH GROUPIr. Dr. Rosdiadee Nordin, Associate Fellow ANGKASA
  2. 2. Rosdiadee Nordin, Gita Mahardhika, Nasharuddin Zainal Faculty of Engineering and Built Environment, UKM Ahmad Khaldun Ismail, Nurul Saadah, Yap Yah Yun, Ainun Abdul Ghani Faculty of Medicine, UKMPRESENT: Applied, Cross-Discipline, Quali. + Quanti.TransERV: Improvement of EmergencyMedical Response via GPS Navigation(UKM-GUP-2011-326)
  3. 3. INTRODUCTION• Emergency response vehicle (ERV): essential pre- hospital service• Emergency response performance affects emergency patients’ survivability [1], [2], [3]• GPS is applicable for improving performance of land transportation, including emergency response vehicle [4][1] T. H. Blackwell and J. S. Kaufman, "Response Time Effectiveness: Comparison of Response Time and Survival in an UrbanEmergency Medical Services System," Academic Emergency Medicine, vol. 9, 2002.[2] E. B. Lerner and R. M. Moscati, "The golden hour: Scientific fact or medical "Urban Legend"?," Academic Emergency Medicine,vol. 8, p. 3, July 2001 2001.[3] J. P. Pell, et al., "Effect of reducing ambulance response times on deaths from out of hospital cardiac arrest: cohort study,"BMJ, vol. 322, pp. 1385-1388, 2001.[4] G. Mintsis, et al., "Applications of GPS technology in the land transportation system," European Journal of OperationalResearch, vol. 152, p. 11, 2004.
  4. 4. CURRENT PRACTICE • GPS system limited to tracking only, not as navigation tool
  5. 5. OBJECTIVEReduce emergency transport/response time via GPSnavigationMETHODCompare ambulance travel time based on twonavigation systems (conventional map vs GPS)
  6. 6. RESEARCH ENVIRONMENT (1)• Coverage area of Emergency Department, Universiti Kebangsaan Malaysia Medical Centre (15 km radius)• 40 emergency calls, i.e. different coordinates• Simulation during working days (Mon-Fri, 8 am-5 pm)• Emergency call served by two different methods: – First trip, ambulance went to emergency scene using map navigation – Second trip, ambulance was following directions and paths given by GPS device – Limited to 30 mins (max.) interval to reduce bias
  7. 7. RESEARCH ENVIRONMENT (2)• Each trip consists of response travel and transport travel – Response: from hospital (base) to scene – Transport: from scene to base• VARIABLE(1) : Response/transport time and distance – map navigation – GPS navigation• VARIABLE(2): – During travel using map navigation: • Response and transport time estimated by the emergency team – During travel using GPS navigation: • Response and transport time calculated calculated by the GPS device
  8. 8. RESEARCH ENVIRONMENT (3)• VARIABLE (3): Profile of paramedics and drivers (19 respondents) includes: – Years of experience – Familiarity with ambulance coverage area – Opinions on relevance of GPS application on emergency vehicles• Performance Measurement – Average speed = Actual distance (km) travel time (hr) – Qualitative opinion of emergency team
  9. 9. RESULT (1)
  10. 10. RESULT (2) Empirical CDF Empirical CDF 1 1 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.6F(x) F(x) 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 Response average speed using map 0.1 Transport average speed using Map Response average speed using GPS Transport average speed using GPS 0 0 10 15 20 25 30 35 40 45 50 55 60 15 20 25 30 35 40 45 50 55 x x CDF of response average speed, CDF of transport average speed, improvement of 3.21% reduction of 3.08%
  11. 11. GPS improves transport timeResult (3): Emergency team’s opinion Unsure GPS improve response time 16% No Unsure 16% 21% Yes 68% No 16% Yes 63% Ambulance service should be equipped with GPS Unsure No 5% 11% Yes 84%
  12. 12. FUTURE WORKS
  13. 13. CONCLUSIONS• GPS navigation has higher average speed compare to map navigation• Quantitatively, GPS is stated as useful by most emergency team (paramedics and drivers)
  14. 14. *Ibraheem Abdullah Mohammed Shayea, *^Rosdiadee Nordin, *^Mahamod Ismail *Faculty of Engineering and Built Environment ^ANGKASA Space InstituteFUTURE: FundamentalCarrier Aggregation (CA) Techniquesin LTE- Advanced (4G) Network(GUP-2012-036)
  15. 15. FUTURE OF WIRELESS NETWORKS• Existing LTE standard (Release 8&9) suffers from limited capacity and lower transmission data throughput• LTE-A (Rel. 10) [1] is the potential candidate for IMT-A’s Fourth Generation (4G) network• Need several new technology ‘enablers’ to allow higher throughput• 3GPP has identified following new technologies: – Coordinated Multipoint (CoMP) – Enhanced MIMO – HetNet – Self-Organized Network (SON) – Carrier Aggregation (CA)[1] 3GPP, TS36.211 V10.4.0 (2011-12) Evolved Universal Terrestrial Radio Access (E-UTRA); Physical channelsand modulation
  16. 16. OBJECTIVE• To investigate the impact of different parameters on the performance of CA technique in the DL for LTE- Advanced System (throughput and system capacity)
  17. 17. INTRODUCTION TO CA• Carrier aggregation provides higher peak data rate for UEs based on CA over a wider transmission bandwidth up to 100 MHz [4] – Up to 1 Gbps for downlink – Up to 500 Mbps for uplink• Possibly to aggregate up to five component carriers with: – Contiguous Carrier Aggregation – Non-contiguous Carrier Aggregation. [4] István Z. Kovács “Carrier Aggregation in LTE-Advanced (from physical layer to upper layers(layers)” Workshop Session 10c, (Nokia Siemens Networks, Denmark), Luis Garcia (Aalborg University). 17 June 2011
  18. 18. COMPONENT CARRIERS TYPES Contiguous carrier aggregation Non-contiguous carrier aggregation• Up to 5 component carriers • Multiple available component carriers, separated along• One FFT module and one radio frequency band front-end [2] • Aggregation of fragmented spectrum [5][2] Daren McClearnon and Wu HuanSystem , “LTE-Advanced: Overcoming Design Challenges for 4G PHYArchitectures “ , Agilent Technologies, June 2, 2011.[5] Yuan G, Zhang X, Wang W, Yang Y. Carrier Aggregation for LTE-Advanced Mobile Communication systems.IEEE Communications Magazine, 2010;(February):88-93
  19. 19. METHODOLOGY (1) Table 1: Scenarios in the Simulation• Five scenarios proposed (Table Scenario NO Description 1) Scenario # 1 Non-CA with 1 CC (CC1) , CC bandwidth = 20MHz• Operating carrier frequency Total System BW = 1 * 20MHz = 20 MHz from 2 GHz for all five carriers’ Scenario # 2 CA with 2 CC (CC1 and CC2) , f1, f2, f3, f4 and f5 located in CC bandwidth = 20MHz the same band with different Total System BW = 2 * 20MHz = 40 MHz system bandwidth for each Scenario # 3 CA with 3 CC (CC1, CC2 and CC3) , CC bandwidth = 20MHz scenario Total System BW = 3 * 20MHz = 60 MHz• Antenna gains and Tx power on Scenario # 4 CA with 4 CC (CC1, CC2, CC3 and CC4) , five carriers are identical, while CC bandwidth = 20MHz shadow fading depends on the Total System BW = 4 * 20MHz = 80 MHz location of the receiver Scenario # 4 CA with 5CC (CC1, CC2, CC3, CC4 and CC5) CC bandwidth = 20MHz antenna Total System BW = 5 * 20MHz = 100 MHz
  20. 20. METHODOLOGY (2) 3000 • Figure 8 illustrates the eNB 9 UE simulation scenario in the 2000 8 10 DL LTE-Advanced system 19 7 11 1000 • Unity Frequency ReuseDistance in meter 6 2 0 18 1 12 Factor (FRF) is used -1000 5 3 • Each eNB coverage is 17 4 13 hexagon in shape located at 16 14 -2000 it center with radius of 750 15 -3000 m. • 40 UEs generated randomly -4000 -3000 -2000 -1000 0 1000 2000 3000 4000 Distance in meter Figure 8: LTE cellular layout
  21. 21. METHODOLOGY (3)• The transmitted power for each subcarrier assumed to be similar across all subcarriers. Cell capacity, which considers the effect of frequency reuse factor can be expressed as:• Where – BW is total system bandwidth (Hz) – BWeff is system bandwidth efficiency – SINRα is achieved SINR, α is frequency reuse factor, assumed to be unity (α =1); i.e. only 1/α of the spectrum can be used by one cell – SINReff is SINR implementation efficiency
  22. 22. RESULTS AND DISCUSSIONS (1) scenario #5, aggregated 5 CCs is 94 Mbps/cell profit rate scenario #5 achieves user throughput gains of 20 (#4), 40 (#3), 59 (#2) and 82 (#1) **Non-CA scenario utilizing 1 CC Mbps/cell User Throughput with CA Technique Propobility of User Throughput with CA technique 1 100 Non-CA 0.9 CA-2CCs 90 CA-3CCs 0.8 CA-4CCs 80CDF function for User Throughput CA-5CCs 0.7 70 User Throughput [Mbps] 0.6 60 0.5 50 0.4 40 0.3 30 0.2 20 0.1 10 0 0 20 40 60 80 100 120 140 160 180 200 0 User Throughput [ Mbps] 1 2 3 4 5 1CC 2CC 3CC 4CC 5CC Figure 11: CDF of average user Figure 12: Average user throughput throughput
  23. 23. RESULTS AND DISCUSSIONS (2) CA achieves around 87.5% gain over Non- CA techniques Active Users Propobility each time Cell Throughput 0.8 200 Non-CA 180 CA 0.7The Percentage of Active UE/cell x 100% 160 0.6 140 Cell Throughput [Mbps] 0.5 120 0.4 100 0.3 80 60 0.2 40 0.1 20 0 1 2 3 4 5 0 1CC 2CC 3CC 4CC 5CC 250 300 350 400 450 500 Normalized Distance [meter] Figure. 13. Average active users per cell Figure. 14. Average cell throughput everywhere in the cell
  24. 24. CONCLUSIONS• Carrier Aggregation has been introduced in LTE-Advanced system (Rel 10) to address the following main features: – Flexible spectrum usage: provide wider system bandwidth up to, e.g., 100 MHz based on 5 CCs with 20 MHz per CCs – Higher transmission data rate: peak data rates up to 1Gbps in DL• Simulation results prove that, implementing CA with higher numbers of CCs improve system performance in term of user throughput everywhere in the cell• Implementing CA enhance system capacity in term of active user’s numbers in the cell in LTE-Advanced systems
  25. 25. What’s next? | | | | | | | BG 1G 2G 3G 4G 5G XG

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