This document summarizes Koonsys' iNOP network optimization software and service. It describes Koonsys' history and timeline, the traditional and innovative services it offers to wireless and wired network operators, its customers and partners. It then discusses trends in the telecom industry requiring cost savings and network expansion. iNOP is presented as the unique solution that addresses both needs through a techno-economic model combining technical and financial optimization of transmission networks. The document outlines how iNOP works through advanced algorithms, potential project results, deliverables and sample case studies showing capacity increases, cost savings and other benefits achieved for various mobile operators.
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3. iNOP optimization
software launched
KOONSYS
founded
First contract
with MNOs
First international
contract
All Hungarian wireless MNOs
contracted
iNOP strategy
accepted
2004 2015 2016
First iNOP service
completed
2005 2006 2009 2010 2012
iNOP in media
International launch
Koonsys timeline - History
4. Traditional services Innovative services
WirelessNetwork
Operators
✔ High Level Network design
✔ Detailed RAN & TRM Network Planning
✔ Measurements (drive test, statistical)
✔ RAN Optimization (statistical & physical)
✔ Planning tool development & support
✔ Consultancy & Expert pool
✔ iNOP Intelligent Network Optimization
✔ Smart City planning
✔ Revenue boosting solutions
✔ GIS and OAM support tools
Wired
telecommunication
✔ High Level Network design
✔ Consultancy
✔ FO network design
✔ Expert pool
✔ Optical hub site optimization
Product and service portfolio
7. By 2025
900 billion USD CAPEX infrastructure investment
will be done by mobile operators in the next 5 years to roll out faster networks.
1 2 3 4
Capacity
1 2 3 4
Lifecycle
CAPEX Spending: Tech Capacity vs Lifecycle
• 4 billion new broadband users
• Data traffic per subscriber will
increase by over 500-fold
• Over 100 billion devices will
be connected
8. MNOs are under double pressure
Cost savings
• ARPU decrease
• Margin erodes due to competition
• No decrease in EBIDTA is accepted
• Technology life cycle shortens – as
well payback time
• Customer acquisition cost increase
Network expansion
• New technologies deployed
• Mobile data boom
• Smartphones enable data
intensive services
• 5G, IoT is behind the corner
9. iNOP is the only state of the art
network optimization solution in
the market addressing both cost
savings and network
enhancement problems.
10. What is iNOP and why it is unique?
• iNOP is a new and unique concept in the
market for transmission networks
• iNOP is an E2E Solution as a Service for
telecom carriers
• iNOP is a techno-economic model
combining both technical and economic
aspects of transmission network
optimization
• iNOP is a software integrating engineering
know-how, complex mathematical
algorithms and financial measures
11. Same optimization methodology has been successfully used by Fortune top companies
iNOP uses industrial best practices
iNOP is the only telecom solution which implements best optimization practices
of other industries like
o Supply chain management
o Logistics
o Production
o Workforce management
o Energy management etc.
12. iNOP solves transmission problems at all network lifecycle stages
• Ensure TRM capacity for all BS
• Future proof TRM network
• Optimal spending of CAPEX
• Minimized OPEX
LaunchnewRANtechnology
RANexpansion
• Minimum # of new HUB sites
• Optimal spending of CAPEX
• TRM capacity for all BS
• Optimized $/Mbps
TRMcapacityupgrade
• TRM capacity bottlenecks
• Overloaded HUB sites
• Minimize CAPEX spending
• Optimized $/Mbps
Maturenetwork
• Reduce OPEX
• Increase spectrum efficiency
• Reduce network complexity
13. iNOP helps to find substantial savings
Typical CEE MNO budget
$ 568,700,000 per year
Subscribers Base 3-5M
ARPU $12-15
Technology 2G/3G/4G
Infrastructure ~4000 BTS
Staff ~1000
If iNOP finds 10% savings it values over
2 million USD per year for the operator
EBID
20%
CAPEX
9%
OPEX
$403,777,000
71%
Support and
Overhead
13%
IT
20%
CustomerMgmt
16%Marketing/ Prod.
Dev.
7%
Sales
17%
Network
$109,019,790
27%
Civil infrastructure
15%
RAN
16%
NW overhead
10%
NW Mgmt
6%
VAS
17%
Core
15%
TRM
$22,894,156
21%
15. Traditional engineering vs. iNOP optimization
Traditional
Engineering
Optimization
with iNOP
Optimization on link level
Technical network parameters are
affected
Only minor topology changes
Best technical solution for Each
link
Limitations to handle complex
network
Optimization on network level
Best network based on technical &
financial targets set by the
operator
Even major changes in
topology are possible
No limits in complexity
TRM
Network
Daily
Challenges
Planning new Links
Increased
Bandwidth
Needs
Cost
Pressure
Optimized
Topology
16. How iNOP optimizes the network?
Technical and financial
network data is extracted
from network
Millions of variations are
analyzed by advanced
mathematical algorithms
Network is translated into a
mathematical problem
Best solution is selected by
iNOP based on pre-defined
KPIs
Mathematical solution is
translated back to an
executable network plan
1 2 3
4 5
18. iNOP deliverables
Network Status before and after iNOP Optimization
TCO Status before and after iNOP Optimization
Recommendations and detailed comparison
of original and new network Before & After
Comparison
Optimized Network Characteristics
ROI, CAPEX Needs & KPI Fulfillment Reports
Detailed figures of potential CAPEX & OPEX
Savings
iNOP Optimization plan and program based
on customer’s targets and needs
Ready to Execute implementation program
21. Customer’s
demand arise
for NW
Optimization
Extracting data
from
Customer's
systems
Data
preparation
and cleaning
Setting
optimization
targets
Running iNOP
Iteratively
evaluation and
refining the
plan
Implementatio
n of network
plan
1 to 2 weeks 2 to 4 weeks 1 day 0.5 to 6 hours 2 to4 weeks
Iteration if needed
Typical iNOP Optimization Project
iNOP project duration 5-10 weeks
22. iNOP input data requirements
Technical data
• Site and network information
• LoS matrix or map data
• Technology, capacity requirements
• Spectrum availability and preference
• Restrictions, redundancy requirements
Financial data
• Equipment and implementation costs
• Frequency fee
• O&M costs
• Vendor support fee
• Rental fees etc.
24. Case study 1 – Tier1 EU based mobile operator
Client
Background
• 20+ years operating fixed and multi-technology wireless networks
• Core network – Fiber; Last mile – P2P Microwave
• # microwave hops: Total 4000 : For pilot: 400 urban / 350 rural
Pain
• Organically grown and increasingly complex network
• Leading to excessive frequency fees to National Infocommunications Authority
• EBIDTA pressure from shareholders
Client Goals
• Fast and easy to implement OPEX reductions
• Frequency fee target reduction of 20%
• Network optimization plan for long term
Findings
• Microwave hops – reduction of 23% possible
• Frequency fee – reduction of 40% possible
• Capacity / hop – increase of 28% possible
• Pilot Study - ROI of 440% within 3 months
25. Original Change
Extrapolated to entire
network
Number of microwave hops 779 516 -33 % -23 %
Frequency fee
$35,000
USD / per month
$7,200
USD / per month
79.5 % 39.8 %
Average capacity per hop
176 Mbps
223 Mbps
338 Mbps
277 Mbps
Avg. 54 % 27.4 %
Average length of connections (urban)
Average length of connections (rural)
3,56 km
7,75 km
2,1 km
6,5 km
41 %
16 %
Not relevant
Case study 1 - figures
26. Case study 2 – Tier2 EU based public operator
Client
Background
• Fiber optic and multi-technology wireless networks
• Core TRM network – Fiber and P2P Microwave; Last mile – P2P Microwave
• # microwave hops: Total 1500 : For pilot: 253 rural
Pain
• Network expansion bottleneck, cannot meet market demand
• How to spend CAPEX, tower infra/technology change/re-build of the network?
• EBIDTA and Time to Market pressure
Client Goals
• Frequency fee target reduction of 15%
• HOP minimization and freeing up tower infrastructure/antenna space
• Network optimization plan for short/mid/long term network development
Findings
• Microwave hops – reduction of 8% possible
• Frequency fee – reduction of 33% possible
• Capacity / hop – increase of 50% possible
• Pilot Study - ROI of 440% within 3 months
27. Original Change
Extrapolated to entire
network
Number of microwave hops 253 231 8,7 % 6,4%
Frequency fee $109,000 $73,000 33 % 24,3%
Average capacity per hop (rural) 73 Mbps 148 Mbps 50,7 % 42.5 %
Average length of connections (rural) 14,6 km 13,2 km 10 % N/A
Case study 2 - figures
28. Case study 3 – Tier1 MNO in Middle-East
Client
Background
• Fiber optic and multi-technology wireless networks
• Core TRM network – Fiber and P2P Microwave; Last mile – P2P Microwave
• # microwave hops: Total >11000 : For pilot: 244 dense urban
Pain
• Network expansion capacity bottleneck, cannot meet market demand
• Overloaded FO HUB sites
• EBIDTA and Time to Market pressure
Client Goals
• Provide required transmission capacity on all BS sites
• Have future proof transmission network for later (4.5G) expansion.
• Relative OPEX savings with low additional investment
Findings
• Capacity / hop – increase of 260% possible
• Relative OPEX reduction (cost/Mbps) – 51% is possible
• HUB overload reduction – on most critical HUBs 25% reduction is possible
29. Original Change
Number of microwave hops 244 244 0 %
Relative OPEX (cost/Mbps) 100% 59% -41%
Average capacity per hop 152 Mbps 399 Mbps 262 %
Overloaded HUB sites 7 2 -72%
Case study 3 - figures
30. Case study 4 – Tier1 MNO in Europe
Client
Background
• Fiber optic and multi-technology wireless networks
• Core TRM network – Fiber and P2P Microwave; Last mile – P2P Microwave
• # microwave hops: Total >20000 : For pilot: 407 urban and hilly rural
Pain
• Network expansion to 4.5G has capacity bottlenecks
• EBIDTA pressure
• Complicated network structure, long chains
Client Goals
• Provide required capacity on all BS sites for 4.5G expansion.
• Simplify network topology
• Relative OPEX savings ($/Mbps) with low additional investment
Findings
• Capacity / link –35% increase is possible
• Relative OPEX reduction ($/Mbps) – 16% is possible
• Simplified network– 5% less links, 19% shorter hops
31. Original Change
Number of microwave hops 407 387 -5 %
Relative OPEX (cost/Mbps) 100% 84% -16%
Average capacity per hop 268 Mbps 363 Mbps 35%
BS connected to FO HUB in 1 or 2 HOPS 54% 80% 48%
Case study 4 - figures