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Presentation held by Mr.Igor Pupaleski as a part of the Broadband Session at the 8th SEEITA and 7th MASIT Open Days Conference, 14th-15th October, 2010

Presentation held by Mr.Igor Pupaleski as a part of the Broadband Session at the 8th SEEITA and 7th MASIT Open Days Conference, 14th-15th October, 2010



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    ONE ONE Presentation Transcript

    • AGENDA • ONE 3G Highlights • ONE 3G Facts • Monte Carlo method theory • Monte Carlo simulation approach • Conclusion and Future Developments
    • ONE 3G Highlights • ONE is the convergent operator in Macedonia providing: Mobile, Fixed, Broadband and DVB -T services • First Mobile operator in Macedonia with 3G license • First Mobile operator offering Mobile Broadband Internet - HSDPA up to 7.2 Mbps • Current 3G Population coverage is more than 81% • 3G Coverage provided to more than 20 cities in Macedonia • Covered main touristic places • Constantly expanding the 3G coverage and capacity
    • ONE 3G Highlights – coverage map
    • ONE WADSL – coverage map •B r o a d b a n d P o p u l a t i o n c o v e r a g e a p p r o x . 9 3 % •C o v e r e d m o r e t h a n 6 4 0 p r i m a r y s c h o o l s f o r i n t e r n e t k i o s k p r o j e c t •B r o a d b a n d i n t e r n e t o f f e r e d t o m o r e t h a n 1 4 0 0 p o p u l a t e d p l a c e s
    • ONE 3G Facts - Data D a t a g r owt h 2010 VS 2009 140% increase 2009 VS 2008 900% increase D a t a sh a r e Total data share - Year 2008 Total data share - Year 2009 Total data share - Year 2010 2G data 2G data 2G data 34% 8% 7% 3G data 3G data 3G data 66% 92% 93%
    • ONE 3G Facts – Data & Voice & Subscribers D a t a t r en d - 3G V S 2G V oic e t r en d - 3G V S ( 2G + 3G) Subscribers 3G subs 15% “P a r et o R u le” 3G su b sc r ib er s ( 15%) ar e g en er at in g 85% of t ot a l d a t a in t h e n et wor k 2G subs 85%
    • Monte Carlo Method Theory • Introduced in the 1940s by physicists Enrico Fermi and Stanislaw Ulam , the Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling to compute their results • The technique is used by professionals in a wide range of fields such as finance, project management, energy, research and development, insurance and Telecommunications. • The method consists in repeating an experience many times with different randomly determined data in order to draw statistical conclusions; in mobile network case, the users are deployed in the network with random position • Simulate network regulation mechanisms for a user distribution and obtaining network parameters Monte Carlo
    • Monte Carlo Concept and Conclusion 1. The behavior of a network depends on many different aspects like power, interference and services used 2. 3G radio network planning is performed through Monte Carlo simulations trying to simulate a “real-life” network 3. Spreading the users on the environment and then compute the necessary power for each user to fulfill the requirements 4. The power is calculated through steps adjusting the power according to the power control algorithms and the simulation stops when the power converge • For a given user and traffic distribution, the coverage predictions are used to compute the offered service based on these simulations • The results of one user and traffic distribution are gathered in a so-called snapshot (a set of Mobile Stations in the network with random position)
    • Monte Carlo Simulation Parameters Service configuration Morphology configuration Terminal configuration
    • Monte Carlo Simulation Approach Input parameters: Traffic repartition: 3 sector UMTS sites, 65 beam width antenna, 3 meters over the roof, Voice = 40% BS power 43 dBm, pilot power 30 dBm, 400 users on 1Km2 Video Call = 1% R99 = 25% HSDPA 3.6 = 30% HSDPA 7.2 = 4% Coverage map computed by Ray-Tracing propagation Model for Urban environments Coverage map with Cell Overlapping (-82 dBm threshold)
    • Monte Carlo Simulation Coverage Map Results Superposition of 40 UMTS Simulation Superposition of 50 UMTS Simulation Overlapping sites removed to avoid interference Snapshots with 10% rejection, 6% due to Snapshots with 7% rejection, 5% due to Snapshots with 2% rejection, 1% due to Low signal quality and 4% due to Overload Low signal quality and 2% due to Overload Low signal quality and 1% due to Overload In the UMTS simulations performed, an average of 400 For a UMTS radio network, more interference users were spread in the area under investigations. On means less capacity and less offered service average 160 users (~40%) are using the voice service, and/or at a lower quality (~25%) are using R99 (384kbps) connections and 120 (~30%) are on 3.6 Mbps.
    • Conclusion and Future Developments • Due to the high growth of 3G (data and voice) capacity optimization of the UMTS network is needed • Monte Carlo method is most suitable for UMTS capacity predictions • Traffic optimization is needed in order to provide best services to our customers • Number of 3G terminals is constantly increasing and the customers are getting more and more demanding • ONE will permanently follow customer requirements in terms of coverage and throughputs • ONE is mobile broadband pioneer with leading contribution in technological development of the country