njhy520o - umts planning process

Mason Communications Training: WCDMA Radio Planning CourseModule 5: UMTS Network Design

Section 5.2: UMTS Planning Process

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© Mason Communications Ltd 2001

5 Network Design5.2 The Planning Process

WCDMA Radio Planning Course

Mason Communications Training: WCDMA Radio Planning Course

Module 5: UMTS Network Design




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UMTS Planning Process

5.2.2© Mason Communications Ltd 2001

Where are We Now?

Part IIPart I

Introduction to UMTS

UMTS Overview

Access Methods

WCDMA Introduction

UMTS Model Architecture

UMTS Specifications

Diversity

Intro to Radio Planning

Antennas Part I

Comms Theory

Path Loss

DiversityBasic Radio Principles

Intro to Planning Tools

Intro to LinkBudgets

CourseWash Up

Mobile RadioChannel

Local Mean Signal

Narrowband Channel

Course Overview

Wideband Channel

UMTS Design Elements

Antennas Part II

WCDMA Physical Layer

UMTS Network Design

UMTS Link Budgets

Site PlacementInterference

Radio Resource Management

CourseWash Up

Statistics

Notation

Course Overview

Diversity

Matched Filters and

Rake ReceiversUMTS Planning

Process

Where are We Now?

The Course Map shows which section we are now on.



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What is in This Section?

UMTS Radio Planning

Summary

UMTS Network Design

UMTS Link Budgets

Site Placement



CourseWash Up

UMTS Planning Guidelines

What is in This Section?



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In Detail

• UMTS Radio Planning– UMTS Radio Planning Process– Guidelines for Planning– Multi-Operator Interference



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Why is this Section Important to You?

• Without a Radio Planning Tool, your job would be impossible !



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How Will You Learn?

Discussion

Demonstrations

• Demo of simple Monte-Carlo Simulator

• Demo of Static and Dynamic Traffic used for Planning Tools

• Go through a Paper to describe what's behind Monte-Carlo Simulation



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Where Are We Now?

UMTS Radio Planning

NetworkDesign

Operator’s Design Guides

Polygons

Site Placement

Antenna Placement

Frequency Planning

Forward Capacity Planning

LinkBudgets

The Planning Process

Summary




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The UMTS Planning Process - Introduction

• Radio Planning is the logical extension to Link Budget Planning. That is the application of the Link Budget to the Planning Tool, using real terrain data, and real subscribers.

• We demonstrated in section 4.1 that the UMTS Link Budget is verydifferent to GSM. In UMTS Capacity and Coverage are closely coupled

• UMTS Link Budget influenced by Inter-Cell interference and therefore by locations of Subscribers

• UMTS Downlink Link Budget influenced by loss of Orthogonality inCode Domain to separate user channels from same cell/sector

• UMTS services are variable in terms of bit rate, latency, activi ty factor, quality, etc. There exists a 4 Dimensional probability space of a subscriber’s service type (demand), subscriber is active (time), subscriber speed (speed) and location (space). This needs to be understood in order to plan a UMTS network.

The use of the Radio Planning tool aids visualisation of the Link Budget over a geographic area. We ultimately wish to visualise service areas, problem areas, and use these visualisations to assist in planning a network of base stations in the most efficient manner possible. The Planning process using the Radio Planning tool is therefore the logical extension of the application of the Link Budget using real terrain information, and real subscriber definitions.

We demonstrated in the “Link Budgets” section, section 4.1 that the UMTS Link Budget is not trivial. The UMTS Link Budget is a function of cell loading and therefore range and capacity are closely coupled.

Furthermore the UMTS Link Budgets, particularly on the Downlink, not only depended upon cell load, but relative positions of subscribers in the home cell and neighbouring cells. The positions of subscribers dictated the inter-cell interference seen at a base station, and at the subscribers location.

Also, we saw that on the Downlink that the user channels on the same cell or sector are separated in the code domain using OVSF codes. OVSF codes have poor cross-correlation properties, and as a result any time dispersion in the downlink radio channel can manifest itself as interference to other channels. The degree of time dispersion was dependent upon environment and location of subscribers.

Finally, in UMTS we do not have a single service (as with GSM) but a whole multiplex of services, bit rates, QoS criteria, and latency criteria to consider. Each subscriber may wish to use different services, at different times, using different datarates, and having different Quality Criteria. These subscribers occupy UMTS resources, at different times and in different spaces, with say probabilities of occupying a certain space at a certain time and using a certain service. This profile in demand, space, and time is vitally important in UMTS planning. The paradox at the moment is we have no historical nor reliable prediction data with which to characterise such profiles.



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• The story so far:• There are no 3GPP Radio Planning Guidelines• There exists only a handful of technical papers on the

subject of UMTS Radio Planning• No one has really established (or could establish) “Best

Practice” in UMTS Radio Planning• There are a handful of Radio Planning Tools emerging on

the market• All the tools approach planning in slightly different

ways (their view of the planning process imposed on their tool)

ETSI produced radio planning guidelines in ETSI GSM TR03.03 now transferred to 3GPP GSM TR43.03 under the transfer of GSM Specifications to 3GPP. TR 43.03 is basically the same as 03.03 but now considers the co-existence of UMTS and GSM equipment at the same site, since GSM is now essentially a technology under the umbrella of 3GPP.

3GPP have not produced any Radio Planning Guidelines as yet. Much of the effort has been concentrated into getting the UMTS Specification out with little supporting documentation on how to deploy and plan it. This was very much the same story with GSM in the early days (I.e. 03.03 didn’t come out until 1993, a year after the UK had launched its two initial GSM Networks).

There exists a number of technical papers on UMTS Planning. A bibliography will be given at the end of this section. These papers are very much academic papers of a year or so old based upon initial simulator results.

As such “Best Practice” in UMTS Planning does not exist at this time and it is difficult to present how the UMTS Radio Planning process should be carried out – This is the Operator’s Challenge.

There are a number of 3G/UMTS Radio Planning Tools on the market. Most of these are first attempts at UMTS Radio Planning and all seem to have established individual ways of tackling the UMTS planning challenge. As a result an Operator who uses a certain planning tool will have their planning process very much dictated by the planning tool methods.



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• All UMTS Planning Tools appear to solve much of the UMTS coverage/capacity prediction through Monte-Carlo simulations. This is a common element seen in UMTS Planning and was introduced in section 4.1.

• What we discover is that the UMTS planning process is extremely complex and convoluted, with many more possible output arrays than with 2G/GSM planning.

• Furthermore we have the “Fuzzy Universe” where a Pixel does not tell us whether a particular UMTS is available or not but now we have a probability of a service being available based upon Monte-Carlo simulation.



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UMTS Planning – Snapshot Convergence

Consider a typical Urban Area of

5km x 5km

Commercial

Industrial

Dense Urban

Urban

Open Space

This may consist of a number of land-use types

Based upon land-use we can understand traffic density.

Consider a Snapshot of subscribers



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Assume that all subscribers want 144kbps duplex data

service.


We could deploy 5 Base Stations like this.

Perform Best Server plot

BS1

BS2

BS4

BS3

BS5



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Perform UL Coverage only

Calculation:144kbps Link Budget and UL Noise Rise = 3dB at each BS

(i.e. 50% Loading)

OK - All areas covered!

Perform DL Pilot/Common Channel Coverage only

Calculation:BS Total Power = 20W

DL: 1W CPICHDL: 0.1W SCH

DL: 1W P-CCPCH


Perform Soft Handover Areas calculation

Up to 12dB Margin shownConsider all subs in SHO if

>2 CPICH powers within 6dB



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Calculate UL Powers for all Subscribers assuming no

Interference

UL Intercell and Intracell Interference needs

calculating at each BS

Noise Rise at each BS calculated

Subscriber UL MS powerSub1 0.071

Sub2 0.032

Sub3 0.046Sub4 0.041

Sub5 0.004

Sub6 0.069

Sub7 0.053

… …

Sub41 0.067

Sub42 0.027

BS Noise RiseBS1 2.890

BS2 1.715

BS3 2.976

BS4 1.394BS5 2.970

BS1

BS2

BS4

BS3

BS5

This is what we would wishto have in terms of

connectivity



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Re-calculate UL Powers for all Subscribers to overcome

Noise Rise at Parent BS

Re-calculate UL Intercell Interference at each BS

Noise Rise at each BS calculatedSubscriber UL MS power

Sub1 0.079

Sub2 0.045

Sub3 0.092

Sub4 0.061

Sub5 0.005

Sub6 0.101Sub7 0.079

… …

Sub41 0.112

Sub42 0.029


BS2 1.766BS3 2.999

BS4 1.564

BS5 2.999

BS1

BS2

BS4

BS3

BS5


connectivity



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Sub2 0.052

Sub3 0.110

Sub4 0.065

Sub5 0.007

Sub7 0.085

… …

Sub41 0.119

Sub42 0.034

Sub6 0.129

BS1

BS2

BS4

BS3

BS5


connectivity


BS2 1.830BS3 2.901

BS4 1.724

BS5 2.999

Sub6 MS power > 0.125WPut to outage



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Sub2 0.052

Sub3 0.110

Sub4 0.065

Sub5 0.007

Sub7 0.085

… …

Sub41 0.119

Sub42 0.034

Sub6 0.000

BS1

BS2

BS4

BS3

BS5


connectivity


BS2 1.830BS3 2.901

BS4 1.724

BS5 3.056

BS5 exceeds 3dB Noise Rise. Put one of its subscribers (Sub1) to outage

Sub6 Sub6

Sub1



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Subscriber UL MS power

Sub2 0.052

Sub3 0.110

Sub4 0.065

Sub5 0.007

Sub7 0.085

… …

Sub41 0.119

Sub42 0.034

Sub6 0.000

BS1

BS2

BS4

BS3

BS5


connectivity


BS2 1.830BS3 2.901

BS4 1.724

BS5 2.277

Sub1 0.000

Sub6

Sub1

Sub6

Sub1



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BS1

BS2

BS4

BS3

BS5

Run Interference/Power Convergence Algorithm

(Many iterations)

BS1

BS2

BS4

BS3

BS5



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B S 1

B S 2

B S 4

B S 3

B S 5

D i s t r i b u t i o n o f U L P o w e r s

P o w e r ( m W )

No.

of S

ubs

05

1 01 5202530354045

10

20 30 40 50 60 70 80 90 100

110

120

130

05

1 01 52 0

B a s e S t a t i o n D L P o w e r

B S 1 B S 2 B S 3 B S 4 B S 5

Pow

er (

W)

H O P o w e r

• M u s t a l s o p e r f o r m D L C o n v e r g e n c e o f I n t e r c e l l a n d I n t r a c e l l I n t e r f e r e n c e ( U L i l l u s t r a t e d o n l y i n p r e v i o u s s l i d e s )

• C o n v e r g e n c e o f U L a n d D L I n t e r f e r e n c e r e v e a l s :

• 5 B S ’ s s u p p o r t s 3 3 s u b s a t 1 4 4 k b p s d u p l e x c i r c u i t s w i t c h e d t r a f f i c ( 4 . 7 5 M b p s )

• D L P o w e r p r e s e r v e d i n t h i s c a s e , a n d c o u l d i n p r i n c i p l e a l l o c a t e m o r e D L p o w e r p e r l i n k t o s u p p o r t h i g h e r D L ( i . e . a s y m m e t r i c ) d a t a r a t e s .

• P l e a s e N o t e t h a t t h e n e t w o r k e x a m p l e s h o w n c o u l d h a v e m a n y c o m b i n a t i o n s w h i c h s a t i s f y t h e I n t e r f e r e n c e c o n d i t i o n s . T h i s i s o n l y o n e c o n v e r g e d s n a p s h o t .

• W e c o u l d r u n t h e c o n v e r g e n c e a l g o r i t h m a g a i n a n d p u t o t h e r r a n d o m s u b s c r i b e r s t o o u t a g e , t h e r e b y r e v e a l i n g a d i f f e r e n t c o n v e r g e d s t a t e . W e w o u l d h o p e h o w e v e r t h a t a p p r o x . 3 3 s u b s w o u l d b e s u p p o r t e d , i . e . t h e c a p a c i t y s h o u l d n ’ t a l t e r .

U M T S P l a n n i n g – S n a p s h o t C o n v e r g e n c e4 . 7 5 M b p s

Mason Communicat ions Train ing: WCDMA Radio Planning CourseModule 5: UMTS Network Design


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N J H Y 5 2 0 O . P P T

U M T S P l a n n i n g P r o c e s s

5 . 2 .2 1© M a s o n C o m m u n i c a t i o n s L t d 2 0 0 1

T h e U M T S P l a n n i n g P r o c e s s – S i n g l e S n a p s h o t

• C a s e S t u d y o f U M T S N e t w o r k D e s i g n f r o m P a p e r : “ S t a t i c S i m u l a t o r f o r S t u d y i n g W C D M A R a d i o N e t w o r k P l a n n i n g I s s u e s ” , I E E E V T C 9 9 , p p . 2 4 3 6- 2 4 4 0 .

• 1 2 x 1 2 k m 2 A r b i t r a r y A r e a

• N o k i a S t a t i c S i m u l a t o r u s e d

• S u b s c r i b e r M i x :

• 1 5 0 0 x 8 k b p s V o i c e a t 5 0 k m / h

• 3 0 x 1 4 4 k b p s L C D a t 3 k m / h

• A s s h o w n l e f t

• 1 9 T r i- s e c t o r e d M a c r o S i t e s d e p l o y e d u p o n u n i f o r m g r i d a s s h o w n l e f t .

• N o M o n t e- C a r l o s i m u l a t i o n . M a n y u s e r s – s i n g l e S n a p s h o t s h o u l d b e r e l i a b l e .

S o u r c e : I E E E ©8 k b p s U s e r1 4 4 k b p s U s e r

T h e n e x t f e w s l i d e s d i s c u s s s o m e o f t h e r e s u l t s , a n a l y s i s a n d s et t i n g- u p o f a U M T S n e t w o r k

s imula t ion ca r r i ed ou t in a pape r en t i t l ed “S ta t i c S imula to r fo r S t u d y i n g W C D M A R a d i o

N e t w o r k P l a n n i n g I s s u e s ” , I E E E V T C 1 9 9 9 , p p . 2 4 3 6 -2 4 4 0 .

T h e S i m u l a t o r c o n v e r g e s o n l y o n e S n a p s h o t o f t h e N e t w o r k , t h a t sh o w n i n t h i s s l i d e . A s

t h e r e a r e m a n y u s e r s t h e r e s u l t s o f t h i s S n a p s h o t s h o u l d a g r e e re a s o n a b l y w e l l t o c a r r y i n g

o u t m a n y S n a p s h o t s a n d c o l l a t i n g t h e a v e r a g e c o n d i t i o n s a s i n a f u l l M o n t e-C a r l o a n a l y s i s .



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S o u r c e : I E E E ©

Environmental Parameters UnitsPath Loss Model Okumura-HataSlow Fading std. Deviation 6 dB

Slow Fading correlation between base stations 50%Multipath channel profile ITU Vehicular A

Downlink orthogonality factor, αa v g 0.5

Simulation ParametersMax. allowed Uplink loading limit 50%Downlink Pilot Channel Power 30 dBm

Downlink Other Common Channel Powers 30 dBmSoft handover window 6 dBLoad Control in Uplink Links Randomly put to outage from overloaded cellsBS Power Control in Downlink Links Randomly put to outage from overloaded cells

Subscriber Parameters 8kbps Voice 144kbps DataNumber of Subscribers 1500 30

Mobile station speeds 50 3 km/hVoice Actitivity 0.67 1

Equipment Parameters Base Stations 8kbps Voice 144kbps DataNoise figures 5 7 7 dBmAntenna Types 65° Omni OmniAntennas Gains 17 1.5 1.5 dBi

System Losses 3 1.5 1.5 dBMax. Tx Power 43 21 21 dBm

M o s t i m p o r t a n t s i m u l a t i o n p a r a m e t e r s

T h e a c t u a l s i m u l a t o r a n d p r o c e s s f o r s i m u l a t i o n i s d e s c r i b e d i n “ S t a t i c S i m u l a t o r f o r

S t u d y i n g W C D M A R a d i o N e t w o r k P l a n n i n g I s s u e s ” . T h e s a m e s i m u l a t or a n d s i m u l a t i o n

p r o c e s s i s a l s o d e s c r i b e d i n “ W C D M A f o r U M T S ” p a g e 1 7 1 . T h e t o o l i s e s s e n t i a l l y a

S n a p s h o t g e n e r a t o r a n d M o n t e- C a r l o a n a l y s i s t o o l . T h e r e a r e f o u r p h a s e s i n t h e S n a p s h o t

s i m u l a t i o n p r o c e s s d e s c r i b e d i n t h e p a p e r :

I n i t i a l i s a t i o n P h a s e

U p l i n k I t e r a t i o n P h a s e

D o w n l i n k I t e r a t i o n P h a s e

P o s t P r o c e s s i n g P h a s e



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• T a r g e t i n U p l i n k I t e r a t i o n i s t o a l l o c a t e M S T x P o w e r s s u c h t h a t I n t e r f e r e n c e L e v e l s C o n v e r g e .

• M S T x P o w e r s i n i t i a l l y d e t e r m i n e d s o t h e y f u l f i l E b / N o a t B S R x .

• M S T x P o w e r s c o r r e c t e d b y t a k i n g i n t o a c c o u n t a c t i v i t y f a c t o r s , S H O G a i n s , a n d F P C H e a d r o o m .

• A n y M S T x P o w e r s > M a x a r e t h e n e x c l u d e d f o r t h i s s t e p o f i t e r a t i o n

• O n c e a l l M S T x P o w e r s c a l c u l a t e d , t h e I n t e r f e r e n c e a t e a c h B S i s r e-e s t i m a t e d .

• R e p e a t C y c l e - r e - a l l o c a t i o n o f M S T x P o w e r s

• R e p e a t u n t i l C o n v e r g e n c e i n P o w e r a n d I n t e r f e r e n c e !

A l l o c a t e M S T x t o s a t i s f y E b / N o

M S T x P o w e r s c o r r e c t e d b y S H O a n d F P C

H e a d r o o m

A n y M S T x P o w e r s > M a xF o r m a n y i t e r a t i o n s ?

I n t e r f e r e n c e a t e a c h B Sr e c a l c u l a t e d

I n s i g n i f i c a n t c h a n g eS i n c e l a s t i t e r a t i o n

( C o n v e r g e n c e ? )

M S p u t t o O u t a g e

End

S t a r t

E x t r a c t f r o m “ S t a t i c S i m u l a t o r f o r S t u d y i n g W C D M A R a d i o N e t w o r k P l a n n i n g I s s u e s” © I E E E .

T h e t a r g e t i n t h e u p l i n k i t e r a t i o n i s t o a l l o c a t e t h e m o b i l e s t a t ions’ t r ansmi t powers so , t ha t t he i n t e r f e r ence l eve l s

a n d t h u s t h e b a s e s t a t i o n s e n s i t i v i t y v a l u e s c o n v e r g e . T h e t r a n s m i t p o w e r o f t h e m o b i l e s t a t i o n s t o e a c h b a s e s t a t i o n

a r e e s t i m a t e d s o t h a t t h e y f u l f i l l t h e b a s e s t a t i o n s E b / N o r e q u i r e m e n t s . T h e m o b i l e s t a t i o n ' s t r a n s m i t p o w e r s a r e

b a s e d o n t h e s e n s i t i v i t y l e v e l o f t h e b a s e s t a t i o n , s e r v i c e ( d a ta r a t e ) a n d s p e e d o f t h e m o b i l e s t a t i o n a n d t h e l i n k

l o s s e s t o t h e b a s e s t a t i o n . T h e s e a v e r a g e p o w e r s a r e t h e n c o r r e c t e d b y t a k i n g i n t o a c c o u n t t h e v o i c e a c t i v i t y , t h e

s o f t h a n d o v e r ( S H O ) g a i n s a n d a v e r a g e p o w e r r a i s e d u e t o f a s t t r a n s m i t p o w e r c o n t r o l ( T P C ) . T h e l a t t e r t w o o n e s

a r e i m p o r t e d i n f o r m o f l o o k u p t a b l e s b a s e d o n e x t e n d e d l i n k l e v e l s i m u l a t i o n s a n d S H O a n a l y s e s ( d i s c u s s e d i n

L i n k B u d g e t s S e c t i o n ) . F o r e a c h c h a n n e l t y p e a s e p a r a t e s e t o f t a b l e s h a s t o b e g e n e r a t e d . I n f l u e n c e o f t h e f a s t T P C

c a n b e s e e n i n a n i n c r e a s e o f t h e a v e r a g e t r a n s m i t p o w e r a n d i n t h e h e a d r o o m ( f a s t f a d i n g m a r g i n ) a M S n e e d s

a b o v e t h e a v e r a g e t r a n s m i t p o w e r t o f o l l o w t h e f a s t f a d i n g . S H O g a i n s o n t h e c o n t r a r y h e l p t o a l l e v i a t e t h e s i t u a t i o n

b y r e d u c i n g t h e a v e r a g e n e e d e d t r a n s m i t p o w e r a n d t h e h e a d r o o m . F o r t h e a m o u n t o f r e d u c t i o n i n a v e r a g e t r a n s m i t

p o w e r a n d h e a d r o o m i n t h e S H O c a s e , t a b l e s h a v e b e e n g e n e r a t e d fr o m l i n k l e v e l s i m u l a t i o n s f o r v a r i o u s m o b i l e

s p e e d s , b i t r a t e s a n d a v e r a g e l e v e l d i f f e r e n c e o f t h e S H O l i n k s . N o t s i m u l a t e d i n t e r m e d i a t e v a l u e s a r e i n t e r p o l a t e d .

W h e n t h e t r a n s m i t p o w e r s o f t h e m o b i l e s s t a t i o n s t o e a c h b a s e s t a t i o n a r e e s t i m a t e d t h e b e s t s e r v e r i s d e t e r m i n e d a s

t h e b a s e s t a t i o n , t o w h i c h t h e m o b i l e s t a t i o n h a s t o t r a n s m i t w i t h m i n i m u m p o w e r . T h e m i n i m u m t r a n s m i t p o w e r s

a r e t h e n c o m p a r e d t o t h e m a x i m u m a l l o w e d t r a n s m i t p o w e r o f a m o bi l e a n d t e r m i n a l s e x c e e d i n g t h i s l i m i t a r e

e x c l u d e d d u r i n g t h i s i t e r a t i o n s t e p . I f t h i s h a p p e n s a s p e c i f i e d n u m b e r o f i t e r a t i o n s i n a r o w , t h e M S i s f i n a l l y p u t t o

o u t a g e . A f t e r t h e t r a n s m i t p o w e r s o f a l l m o b i l e s t a t i o n s h a v e b e e n a l l o c a t e d , t h e i n t e r f e r e n c e a t e a c h B S c a n b e r e -

e s t i m a t e d a n d n e w l o a d i n g v a l u e a n d s e n s i t i v i t y i s e s t i m a t e d .

N o w t h e m o b i l e s t a t i o n c a n b e r e- a l l o c a t e d t o a n e w b a s e s t a t i o n , t h e m o b i l e s t a t i o n t r a n s m i t p o w e r s a r e

re e s t i m a t e d a n d t h e i n t e r f e r e n c e a n a l y s i s i s p e r f o r m e d a g a i n . T h i s i s r e p e a t e d u n t i l t h e c h a n g e s i n t h e B S

s e n s i t i v i t y v a l u e s a r e s m a l l e r t h a n s p e c i f i e d . I n c a s e t h e l o a d i n g o f a c e l l e x c e e d s t h e s p e c i f i e d v a l u e a n o t h e r c a r r i e r

c a n b e a u t o m a t i c a l l y a d d e d a n d m o b i l e s t a t i o n s a r e m o v e d t o t h e new ca r r i e r . D i f f e ren t s t r a t eg ie s to sha re the

t r a f f i c b e t w e e n t h e a d d i t i o n a l c a r r i e r ( s ) a r e i m p l e m e n t e d . T h e m e t h o d s i n c l u d e a ) m o v i n g r a n d o m l y m o b i l e s t a t i o n s

f r o m t h e w h o l e n e t w o r k t o a n e w c a r r i e r , b ) r a n d o m l y m o v i n g m o b i l e s t a t i o n s f r o m o v e r l o a d e d c e l l s t o a s e c o n d

c a r r i e r o r c ) m o v i n g m o b i l e s t a t i o n s a t o v e r l o a d e d c e l l s a c c o r d i n g t h e i r n e e d e d t r a n s m i t p o w e r . W h i l e m e t h o d a )

e n s u r e s t h a t t h e w h o l e t r a f f i c d i s t r i b u t i o n i n t h e n e t w o r k i s n o t c h a n g e d c o m p a r e d t o t h e i n i t i a l s i t u a t i o n , i t h a s t h e

d i s advan t age , t ha t t he s econd ca r r i e r i s t aken i n to accoun t s imu l t aneous ly a t a l l ba se s t a t i ons even i f i t i s no t

n e e d e d .



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• T a r g e t i n D o w n l i n k I t e r a t i o n i s t o a l l o c a t e B S T x P o w e r s s u c h t h a t I n t e r f e r e n c e L e v e l s C o n v e r g e .

• B S P i l o t P o w e r s s e t . T h e s e c a n b e b a s e d u p o n U p l i n k L o a d i n g , o r s e t i n d i v i d u a l l y .

• B e s t S e r v i n g C e l l d e t e r m i n e d b y b e s t P i l o t s i g n a l . A l l o t h e r P i l o t s > T h r e s h o l d a n d w i t h i n S H O a r e a l s o i n c l u d e d

• B S T x P o w e r s i n i t i a l l y d e t e r m i n e d s o t h e y f u l f i l E b / N o a t M S R x .

• B S T o t a l T x P o w e r > M a x ? D r o p r a n d o m l i n k s , D r o p H i g h e s t P o w e r L i n k s o r D r o p L o w e s t P o w e r l i n k s i n l o a d e d c e l l s ?

• A l l L i n k s m a d e – C a l c u l a t e C / I f o r e a c h l i n k

• A n y C / I ’ s > r e q u i r e d – B S T x P o w e r s f o r t h a t M S L i n k a d j u s t e d

• R e p e a t C y c l e - r e - a l l o c a t i o n o f B S T x P o w e r s u n t i l C o n v e r g e n c e a c h i e v e d

S e t B S P i l o t P o w e r s1 . A l l t h e s a m e

2 . B a s e d u p o n U p l i n k3 . S e t I n d i v i d u a l l y

M S T x P o w e r s c o r r e c t e d b y S H O a n d F P C

H e a d r o o m

A n y M S T x P o w e r s > M a xF o r m a n y i t e r a t i o n s ?

I n t e r f e r e n c e a t e a c h B Sr e c a l c u l a t e d

I n s i g n i f i c a n t c h a n g eS i n c e l a s t i t e r a t i o n

( C o n v e r g e n c e ? )

M S p u t t o O u t a g e

End

S t a r t

E x t r a c t f r o m “ S t a t i c S i m u l a t o r f o r S t u d y i n g W C D M A R a d i o N e t w o r k P l a n n i n g I s s u e s” © I E E E .

T h e a i m o f t h e d o w n l i n k i t e r a t i o n i s t o a l l o c a t e t h e c o r r e c t b a se s t a t i o n t r a n s m i t p o w e r s t o w a r d s e a c h m o b i l e

s t a t i o n u n t i l i t h a s r e a c h e d t h e t a r g e t e d C / I v a l u e . Target C/I = [Eb/No] MS . W/R, w h e r e [ E b / N o ] M S. i s t h e r e c e i v e d

E b / N o r e q u i r e m e n t o f t h e M S d e p e n d i n g o n s p e e d a n d s e r v i c e , W i s t h e m o d u l a t i o n b a n d w i d t h a n d R i s t h e d a t a

r a t e . T h e e s t i m a t i o n o f t h e c o r r e c t t r a n s m i t p o w e r r e q u i r e s i t e ra t i o n , s i n c e t h e C / I a t e a c h m o b i l e s t a t i o n i s

d e p e n d e n t o n a l l t h e p o w e r s a l l o c a t e d t o t h e o t h e r m o b i l e s t a t i o n s . I n t h e i n t e r f e r e n c e c a l c u l a t i o n , t h e O r t h o g o n a l i t y

a o f t h e W C D M A d o w n l i n k i s t a k e n i n t o a c c o u n t , r e d u c i n g t h e o w n c e l l i n t e r f e r e n c e b y ( 1 - α) a s w e l l a s t h e g a i n

d u e t o t h e S H O b y c o m b i n i n g a l l S H O c o n n e c t i o n s a t a m o b i l e s t a ti o n . F i n a l l y a s e r v i c e d e p e n d e n t v o i c e a c t i v i t y i s

a p p l i e d , w h i c h c a n b e d i f f e r e n t f r o m t h e u p l i n k v a l u e o f t h a t M S.

I n d o w n l i n k d i r e c t i o n t h e b e s t s e r v e r i s d e t e r m i n e d a s t h e b a s e s t a t i o n w h o s e P e r c h c h a n n e l i s r e c e i v e d b e s t . T h e n

a l l o t h e r b a s e s t a t i o n s a r e d e t e r m i n e d w h o s e P e r c h c h a n n e l s a r e a l s o r e c e i v e d w i t h i n t h e s p e c i f i e d t h r e s h o l d

( W I N D O W _ A D D ) b e l o w t h e b e s t s e r v e r v a l u e a n d t h e l i n k s t o a l l t h e s e b a s e s t a t i o n s a r e c o m b i n e d . T h e f i r s t s t e p

i n t h e d o w n l i n k i t e r a t i o n t h e r e f o r e i s t h e a l l o c a t i o n o f t h e c o rr e c t P e r c h c h a n n e l p o w e r . D i f f e r e n t s t r a t e g i e s a r e

i m p l e m e n t e d , w h i c h i n c l u d e a ) a l l o c a t i n g e v e r y b a s e s t a t i o n a f ix e d P e r c h p o w e r a s s u c h , b ) c o r r e c t i n g t h i s f i x e d

p o w e r b y t h e a m o u n t u p l i n k i n t e r f e r e n c e a n d c ) a l l o c a t i n g e a c h b a s e s t a t i o n a f r e e s e t t a b l e P e r c h p o w e r .

N e x t s t e p i s t h e a l l o c a t i o n o f t h e i n i t i a l t r a n s m i t p o w e r o f e a c h l i n k . T o g e t g o o d s t a r t i n g v a l u e s t o i n c r e a s e t h e

c o n v e r g e n c e o f t h e i t e r a t i o n a m o b i l e s t a t i o n s e n s i t i v i t y i s i n t r o d u c e d . T h e m o b i l e s t a t i o n g e t s t h e s e n s i t i v i t y o f i t s

b e s t s e r v e r a d j u s t e d b y t h e d i f f e r e n c e i n E b / N o r e q u i r e m e n t s f o r t h e c o r r e c t s e r v i c e a n d s p e e d . W i t h t h i s s e n s i t i v i t y

and the l i nk lo s s t o t he bes t s e rve r t he needed t r ansmi t power to t h e M S i s e s t i m a t e d a n d a l l l i n k s t o t h a t M S u s e

t h e s a m e t r a n s m i t p o w e r .

B e f o r e t h e e s t i m a t i o n o f t h e C / I c a n b e p e r f o r m e d , t h e t o t a l t r a n s m i t p o w e r s o f t h e b a s e s t a t i o n s m u s t b e c h e c k e d .

I n c a s e t h e y e x c e e d t h e a l l o w e d m a x i m u m , s e v e r a l m e t h o d s f o r r e d u c t i o n a r e i m p l e m e n t e d i n c l u d i n g a ) d r o p p i n g

r a n d o m l y l i n k s , b ) d r o p p i n g l i n k s u s i n g t h e h i g h e s t p o w e r s a n d c ) d r o p p i n g l i n k s u s i n g t h e s m a l l e s t p o w e r s f r o m

t o o h i g h l o a d e d c e l l s . M e t h o d a ) g i v e s t h e m o s t r e a l i s t i c c a p a c it y n u m b e r s f r o m t h e t h r e e m e t h o d s . M e t h o d b ) i s

t o o o p t i m i s t i c f a v o r i n g l o w p o w e r l i n k s a n d c ) i s t o o p e s s i m i s t i c p r e f e r r i n g h i g h p o w e r l i n k s . M e t h o d s b ) a n d c )

a l so change t he i n i t i a l t r a f f i c d i s t r i bu t i on , because i n b ) l i nks to M S s a t t h e c e l l e d g e a n d i n c ) l i n k s t o M S s c l o s e t o

the B S s a r e r e m o v e d m o r e l i k e l y . L i n k s a r e r e m o v e d u n t i l t h e t o t a l p o w e r o f a l l t r a f f i c c h a n n e l s s t a y s b e l o w t h e

m a x i m u m b a s e s t a t i o n s t r a n s m i t p o w e r r e d u c e d b y t h e P e r c h p o w e r a n d t h e o t h e r c o m m o n c h a n n e l s . I f o n e o f t h e

d r o p p e d l i n k s w a s a l i n k t o t h e b e s t s e r v e r o f a M S , a l l l i n k s t o t h a t m o b i l e a r e d r o p p e d a n d i t i s e x c l u d e d f r o m t h e

c u r r e n t i t e r a t i o n s t e p . A f t e r t h i s h a p p e n e d a c e r t a i n n u m b e r o f consecu t ive i t e r a t i ons , t he MS i s f i na l l y pu t t o

o u t a g e .

A f t e r a l l l i n k s g o t a l l o c a t e d t h e i r t r a n s m i t p o w e r s , t h e r e c e i v e d C / I fo r each l i nk i s ca l cu l a t ed . In i n t e r f e rence

c a l c u l a t i o n , t h e t o t a l t r a n s m i t p o w e r o f a B S i n c l u d i n g t h e P e r c h a n d o t h e r c o m m o n c h a n n e l s ’ p o w e r s a r e t a k e n

i n t o a c c o u n t . I n t e r f e r e n c e c o m i n g f r o m t h e o w n c e l l’ s B S , i s r e d u c e d b e c a u s e o f t h e d o w n l i n k O r t h o g o n a l i t y b y ( 1 -

α) . The C/ I ’ s o f a l l l i nks t o a MS a re t hen added toge the r i n l i nea r s ca l e and compared t o t he t a rge t ed C / I o f t ha t

m o b i l e s t a t i o n . I f t h e d i f f e r e n c e i s b i g g e r t h a n a s p e c i f i e d t h r e s h o l d , t h e t r a n s m i t p o w e r s o f a l l l i n k s t o t h a t m o b i l e

a r e a d j u s t e d b y t h e d i f f e r e n c e b e t w e e n a c t u a l a n d t a r g e t C / I a n d t h e i t e r a t i o n i s r e p e a t e d .



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S o u r c e : I E E E ©

E x a m p l e s o f t h e r e s u l t s f r o m t h e U p l i n k I t e r a t i o n p r o c e s s a r e s h o w n . T h e s l i d e s h o w s t h e

B e s t S e r v e r i n t h e U p l i n k b a s e d u p o n t h e M i n i m u m M o b i l e S t a t i o n T x P o w e r .



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NJHY520O REV O

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T h e U M T S P l a n n i n g P r o c e s s - S n a p s h o t s

• E a c h S n a p s h o t c o n v e r g e n c e n e e d s t o b e c a r e f u l l y m o d e l l e d .

• T h e r e a r e m a n y w a y s t o c a r r y o u t a S n a p s h o t C o n v e r g e n c e A l g o r i t h m .

• A i r c o m d e s c r i b e t h e i r m e t h o d i n t h e i r 3 g t o o l m a n u a l ( p a g e 6 - 9 )

• V o d a f o n e d e s c r i b e t h e i r t e s t b e d t o o l i n I E E E & C J o u r n a l J u n e 2 0 0 0 p a g e 1 0 1 -1 1 9

• N o k i a d e s c r i b e t h e i r r e s e a r c h t o o l i n v a r i o u s p a p e r s .

• “ W C D M A f o r U M T S ” d e s c r i b e s t h e N o k i a s t a t i c s i m u l a t o r t o o l o n p a g e 1 7 1 .

S n a p s h o t C o n v e r g e n c e i s d e f i n e d a s t h e e v e n t u a l s e t t l i n g o f s u b s c r i b e r a n d B a s e S t a t i o n

c h a n n e l p o w e r s a f t e r s o m e d i s t u r b a n c e i n t h e n e t w o r k , b e i t a s u b s c r i b e r m o v e s , o r c h a n g e s

da ta ra te , o r t e rmina tes a ca l l . We d i scussed ea r l i e r tha t a d i s t u r b a n c e s e t s o f a c h a i n r e a c t i o n

o f e v e n t s o f p o w e r v a r i a t i o n i n s u b s c r i b e r s a n d b a s e s t a t i o n c h an n e l s .

S n a p s h o t C o n v e r g e n c e n e e d s t o b e v e r y c a r e f u l l y m o d e l l e d i n o r d er t o a c c u r a t e l y m o d e l

w h a t w o u l d h a p p e n i n r e a l i t y , a n d t o a v o i d b i a s t o a n y s i n g l e o r g r o u p o f s u b s c r i b e r s a n d / o r

b a s e s t a t i o n s . V a r i o u s S n a p s h o t c o n v e r g e n c e m o d e l s a r e d e s c r i b e d i n t h e a b o v e p a p e r s



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T h e U M T S P l a n n i n g P r o c e s s – G S M

• I n G S M t h e p r o p a g a t i o n l o s s m o d e l t o l d u s w h e t h e r a p i x e l w a s i n s e r v i c e c o v e r a g e o r n o t .

• I f t h e p l a n n i n g u s e d a L o g -N o r m a l f a d e m a r g i n t h e n e a c h p i x e l r e p r e s e n t e d c o v e r a g e f o r x % o f l o c a t i o n s w i t h i n t h a t p i x e l .

• A s a s u b s c r i b e r m o v e s t h r o u g h t h e e n v i r o n m e n t t h e p i x e l s o r s e r v i c e p r o b a b i l i t y d o e s n o t c h a n g e !

S u b s c r i b e r M o v e m e n t

T h i s s l i d e s i m p l y i l l u s t r a t e s w h a t a R a d i o P l a n n e r w a s u s e d t o se e i n g – a n U n c h a n g i n g

U n i v e r s e ! O n c e s i t e p a r a m e t e r s h a d b e e n l o a d e d a n d a p r o p a g a t i o n l o s s c a l c u l a t i o n

p e r f o r m e d a c r o s s a n a r e a t h e s e r v i c e a t e v e r y l o c a t i o n w a s d e t e r mined , a t l e a s t t o a

l oca t ions p robab i l i t y w i th in the p ixe l ( I . e . l imi t o f p red ic t ion r e s o l u t i o n ) . T h i s p i c t u r e o f

c o v e r a g e o r s e r v i c e a v a i l a b i l i t y r e m a i n e d u n c h a n g e d , e v e n w h e n su b s c r i b e r s e n t e r e d , l e f t ,

h a n d e d o v e r b e t w e e n s i t e s , a n d s i m p l y m o v e d a r o u n d t h e a r e a .



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T h e U M T S P l a n n i n g P r o c e s s : M o n t e - C a r l o o f S n a p s h o t s

• To bui ld up some stat ist ica l confidence on whether a part icu lar location wi l l receive a particular service , many 100 ’s , if not 1 ,000 ’s of snapshots of subscr iber locat ion/demand combinat ions are converged.

• Al l locations are explored, to give a view on service avai labi l i ty or probabi l ity at a location .

1 2 n- 1 n

1 2 n- 1 n

I n U M T S a d i f f e r e n t c o m b i n a t i o n o f s u b s c r i b e r l o c a t i o n s , a n d s p e e d s r e v e a l d i f f e r e n t

I n t e r ce l l I n t e r f e r ence cond i t i ons wh ich may d i c t a t e d i f f e r en t I n t e r c e l l a n d I n t r a c e l l

i n t e r f e r e n c e c o n d i t i o n s i n t h e n e t w o r k , a n d h e n c e c a p a c i t y p o t e nt ia l .

I f w e p e r f o r m e n o u g h S n a p s h o t s w e c a n b u i l d u p a p i c t u r e o f t h e s e r v i c e l i k e l i h o o d a s a

f u n c t i o n o f l o c a t i o n . W e w o u l d e x p e c t t h a t s e r v i c e a v a i l a b i l i t y w o u l d d e t e r i o r a t e t o w a r d s

t h e e d g e o f t h e c e l l w h e r e M S p o w e r s a r e c l o s e r t o t h e i r m a x i m u m, a n d t h e s e M S a r e l i k e l y

t o be con t r ibu t ing the g rea t e s t In t e r ce l l I n t e r f e r ence .



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T h e U M T S P l a n n i n g P r o c e s s : M o n t e - C a r l o o f S n a p s h o t s

Service Probability >80%Service probability >60%Service probability >40%Service probability >20%Service probability <20%

Vary Subscriber locations, services, numbers of subscribers, etc .

Carry out coverage and capacity predictions for each snapshot by convergingPower fluctuations

Produce Composite Plot of service coverage probability(I.e. service probability based upon subscriber time, space, speed and demand probabilities)

1 2 n-1 n

In order to build up a picture of what service coverage might be we would need to explore all possible combinations of subscriber numbers, subscriber locations, subscriber services, subscriber demands and subscriber speeds. With each combination we would carry out a convergence of power control until a steady state is achieved as discussed in the previous slide, and then take a note of which subscribers are in service or out of service, in handoff, etc. This is called a Snapshot of a Monte-Carlo simulation.

We would then combine all these snapshots together in order to build up a picture of service coverage. We would aim to give a statistical probability of a particular area (pixel) being in coverage. For example if a certain location resulted in a subscriber being in service 500 times during and not in service 500 times during a 5000 snapshot Monte-Carlo simulation, we can state that there exists a 50% probability of that service being available at that location. This also means that 4,000 snapshots didn’t produce subscribers at a particular location.

We have to run a sufficiently long Monte-Carlo simulation in order to explore all locations (or pixels) of an area and to get enough exploration of all locations so that we obtain statistical confidence. If we have only a few subscribers over a large area then we have to run many snapshots. Each snapshot should converge reasonably rapidly however. On the other hand if we had many subscribers we need to rum fewer snapshots, however, each snapshot would take longer to converge.

Subscribers could be distributed across an area based upon probability. Likewise service demand could be modelled as a probability, as could subscriber speed, etc. This warrants careful consideration of subscriber distributions.



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The UMTS Planning Process: Monte-Carlo of Snapshots

Commercial

Industrial

Dense Urban

Urban

Open Space

The underlying Subscriber Location probability may be driven from a Clutter based or land-use

based map such as above

CommercialIndustrialDense UrbanUrbanOpen Space

Voice 64kbps 144kbps 384kbps20 10 8 515 7 5 3

15 5 3 2

10 4 2 1

2 1 0.5 0.25

Probability Matrix of Subscriber density by service type and clutter type

Samples of Snapshots taken from Clutter/Subscriber density

function



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The UMTS Planning Process: Monte-Carlo Simulation

• There are generally two Monte-Carlo approaches:• Static Simulation• Dynamic Simulation

Static SimulationMany Snapshots of Subscriber Locations

Establishes Average Conditions of Network

Dynamic SimulationMany Snapshots of Subscriber Locations

Allows Real-Time Analysis

There are two general approaches to UMTS Monte-Carlo Network Simulation. There is Static Simulation and Dynamic Simulation.

The differences of each simulation approach are described in the following slides.



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• Static Simulation randomly distributes subscribers, services, and hence Eb/No targets over the area of interest using Probability Matrices.

• There is no subscriber position and usage correlation between successive Snapshots

• The results from each Snapshot are stored

• The results from all Snapshots are analysed

• Static Simulation aims to provide the Average Conditions of the Network in terms of Coverage, Interference and Capacity

• The Radio Resource Management Algorithms can not be tested.

• Dynamic Simulation randomly distributes subscribers, services, and hence Eb/No targets over the area of interest using Probability Matrices.

• There is subscriber position correlation between successive Snapshots

• The results from each Snapshot are stored

• The results from successive Snapshots are analysed

• Dynamic Simulation aims to provide results of how the RRM Algorithms are operating (e.g. Handovers, Varying existing Service Rates to allow new subscribers into cell, etc.)

• The Average conditions of the Network can be tested but rely on Many more Snapshots to be taken



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• Static Simulation models the convergence of a single Snapshot to arrive at a re-distribution of Powers in the network. There is no time concept

• Static Simulations can be lengthy where the confidence of the results is related to the length of the Monte-Carlo simulation.

• We would use Static Simulation to establish Coverage, Capacity, and Interference for network deployment. This is what the Radio Planner would be using day to day.

• Dynamic Simulation requires that the network be modelled at time increments down to the Fast Power Control, or at the rate where service rates can change. This is 1500 times a second!

• Dynamic Simulations can be very lengthy and results difficult to analyse.

• We would use Dynamic Simulation to establish RRM and Handover strategies for different deployments (e.g. Different RRM may be used on Train Line coverage)



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Train Line CoverageZero Loading on all Cells when there is no Train

Train Line CoverageCell1 loaded and shrinks

Train Line CoverageCell2 becomes loaded and shrinks

Excessive Handover Activity

Time/Distance

HandoverActivity

This slide shows an example of UMTS Service Coverage to a Train Line, and consists of 3 Base Station Sites located along the track. We can assume that the surrounding countryside is virtually uninhabited, and except for a few roads these Base Stations serve the Train line entirely.

If we wish to carry out a network design we may need to think carefully on how we simulate network conditions. In this case we say that the Train Line has so many users per km, but with the condition that all users are contained within 500m (that is the length of the train!). There is tight spatial correlation of subscribers, defined by the bounds of the Train itself.

It may be incorrect to carry out a static simulation as this would generate lots of train positions along the track, and somehow take an average, where in reality the situation is very different. We have one train at a location at one time. This means that the average network conditions (from a static simulation) may be misleading.

A dynamic simulation may be much more meaningful. As a train travels along all subscribers are on the train and are linked to one Base Station as shown in the second image. The serving cell shrinks based upon loading. As the Train crosses the SHO boundary, all users will over a short period of time need to be in SHO, and ultimately handed over to the next serving cell, as shown in the third image. This places huge stresses on the Radio Resource Management (RRM) Handover Algorithms, having to perform many handovers at once. It may be prudent to allocate a separate carrier to the train lines and/or connect all the Base Stations along the line to a dedicated RNC.



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Time/Distance

HandoverActivity

Motorway CoverageNominal Loading on all Cells

when there is Traffic

Gradual Leakage and Admissionof Subscriber Traffic

Gradual Leakage and Admissionof Subscriber Traffic


This slide shows an example of UMTS Service Coverage to a Motorway (M6), and consists of 3 Base Station Sites located along the road. We can assume that the surrounding countryside is virtually uninhabited, and except for a few minor roads these Base Stations serve the Motorway entirely.

If we wish to carry out a network design we may need to think carefully on how we simulate network conditions. In this case we say that the Motorway has so many users per km, where the users are reasonably spread out in distance. This creates gradual leakage and entrance to a cell over time.

It should be OK to carry out a static simulation as this would generate lots of car positions along the Motorway, and take an average, unlike the Train Line scenario.

As we have gradual leakage and entrance to a cell, it is expected that the traffic is very evenly distributed and we do not have a centre of subscriber population with which to place a base station. Furthermore, we can expect much less stress to be placed upon the Radio Resource Management (RRM) Handover algorithms.



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The UMTS Planning Process – Dynamic Simulation

Dynamic SimulationMany Snapshots of Subscriber Locations

Allows Real-Time Analysis

Detailed Analysis to establish:

Handover MarginsRRM Rules

Termination CriteriaAdmission Criteria

Use of Carriers(Macro, Micro, Pico)

Antenna Parameter GuidelinesSite Deployment Rules

Train Line CoverageSignificant Handover Activity

Time/Distance

HandoverActivity

Dynamic Snapshot Simulation using Monte-Carlo is designed to test and analyse the Radio Resource Management Strategies.

Static Snapshot Monte-Carlo Simulation tests the positional variability and demand variability of subscribers over time. This allows the average conditions of the Network to be generated.

Dynamic Snapshot Monte-Carlo Simulation tests the positional and ‘vectoral’ variability and demand of subscribers over time. This allows the change in state of the network from one Snapshot to the next Snapshot to be assessed, such as the success of performing a handover, how calls are dropped at network saturation, and admitted during peak periods.

The Radio Network Planner would probably not get involved with such simulations. They take time, are complex to analyse, and are designed to establish rules rather than something to be varied. However, the lead radio planning team would wish to carry out such analyses. A different set of RRM rules for admission, load control, handovers may be better for network designs catering for Motorways, Rail routes, cities, airports, etc.



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The UMTS Planning Process – Static Simulation

Static Simulation Many Snapshots of Subscriber Locations - Establishes

Average Conditions of Network

Dimensioning ExerciseBased upon Link Budgets and

Nominal Cell Loading to identify Approximate Cell Sizes

Average Coverage, Capacity and Interference Predictions

The UMTS Planning Process can take on many forms. This slide illustrates one approach.

Firstly, it is assumed that some form of network dimensioning has taken place whereby nominal cells are placed over an area. This nominal planning can be carried out in a Planning Tool, or on paper using Link Budgets, Maximum Cell Loading, and nominal Intercell Interference margins, etc. Most Planning tools will allow a ‘Nominal Plan’ to be viewed. Such Nominal planning is quick and indicates very roughly the physical cell plan in terms of site locations.

Secondly, the Monte-Carlo simulation is carried out, using Static Snapshot simulation, rather than Dynamic Snapshot simulation. The Subscriber and Service Densities are loaded using a Map Layer of some kind. All other parameters are loaded such as Antenna Gains, link losses, Diversity Gains, Soft and Softer Handover Gains, Soft/Softer Handover margins and thresholds loaded and propagation model defined. The Simulation is ran to a sufficient number of Snapshots such that adequate Statistical Confidence is achieved.

There is usually a whole raft of possible outputs a Planning Tool could produce. These normally are predictions such as:

•Service Coverage Probability (as shown)

•Service Soft Handover Probability

•Service Softer Handover Probability

•Service Hard Handover Probability (if another carrier defined)

•Service Achieved Eb/No

•Carrier Cell Uplink Noise Rise/Load

•Carrier Pilot Power (Ec/Io), etc.



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The UMTS Planning Process - Static Simulation

Static Simulation Many Snapshots of Subscriber Locations - Establishes

Average Conditions of Network

Dimensioning ExerciseBased upon Link Budgets and

Nominal Cell Loading to identify Approximate Cell Sizes

Average Coverage, Capacity and Interference Predictions

Tweaking of Antenna Downtilts, Sectorisation, Azimuth, Handover Margins and Base Station Powers.

Attempt using different combinations of Base Stations

Generally a number of reports, in the form of tables, spreadsheets, etc. can be produced to compliment the Static Simulation Plots.

The output predictions (plots and reports) need to be interpreted to analyse whether or not that capacity and coverage criteria are being met. For example we may find that a certain area may not be satisfying traffic demand. We also may find that this area has a significant portion of the area suggesting handovers. We know that handovers provide resilience in coverage but consume capacity. In this case we may wish to further downtilt antennas serving this area such that we hope to generate less handover probability and trade this for extra capacity. We also may find some areas have weak coverage and we need to tweak antenna directions, and even powers (if this is an option?). Once we have tweaked system parameters we conduct another Monte-Carlo run using Static Simulation and analyse the results again. We have in effect an iterative process.

We may also wish to look at different combinations of candidate base stations, if we feel that coverage and capacity can not be achieved using the current plan, even with tweaking. In this case we may redefine the Nominal Plan, or simply swap out one or two base stations where we suspect problems may be due, and then conduct the process again. We have in effect an another iterative process.

We need to understand that the confidence in the results is highly sensitive to the confidence we have in the traffic demand (in space, time, and demand), or the Traffic Layer. All the tweaking in the world will be useless if the Traffic Layer is in fact something very different in reality. As the Traffic Layer can be a bit of an unknown quantity at this time the radio planner may wish to experiment with say 3 traffic distributions (a pessimistic, base case, and optimistic case).



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The UMTS Planning Process

• There is a multitude of Predictions and reports a Planning can produce for UMTS Planning

• The specific method by which a Radio Planner should tweak parameters, and/or choose different combinations of candidate base station, and Traffic Scenarios is one that is often left to the Radio Planner

• Approaches, methods will develop as experience of UMTS network planning evolves

• As such Planning Methodologies and 3GPP guidelines will follow

• At the present time we have a lot of experimenting to do!



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Where Are We Now?


NetworkDesign


Polygons

Site Placement

Antenna Placement

Frequency Planning


LinkBudgets


Summary

UMTS Radio Planning



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The UMTS Planning Process - Guidelines

• There are a number of Planning Guidelines which can be used to avoid excessive Interference and hence impact on Capacity and Coverage.

• UMTS is specified and we have only a few parameters with which we can tweak to ensure a Good Network Design

• By Applying such guidelines we ensure that we pre-optimise the network design prior to actual planning optimisation, and post-design optimisation (using real measurements, etc.)



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• Place Base Station Sites at the centres of Traffic Demand distributions (e.g. centres of population or work)

• Share sites with other operators using the Adjacent Channels to minimise Adjacent Channel Interference

• Site Base Stations such that there is a low probability of low coupling losses

• Use of Tri-sectored sites using 65o antennas ensures good Intercell interference containment

• Use downtilt as necessary to contain Intercell interference

• Avoid stressing RRM Algorithms by ensuring a mix of fast moving and slow moving traffic

UMTS Planning is all about Minimising Interference



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Guidelines – Site Placement

Consider a typical Urban Area of

5km x 5km

Commercial

Industrial

Dense Urban

Urban

Open Space

This may consist of a number of land-use

types

Based upon land-use we can understand traffic

density.

Consider a Snapshot of subscribers



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Assume that all subscribers want

144kbps duplex data service.

BS1

BS2

BS4

BS3

BS5

We could connect 5 Base Stations like this.

Base Stations close to traffic demand.

Expensive and less available sites.

BS1 BS2

BS4BS3

BS5

Or we could connect 5 Base Stations like this.

Base Stations away from traffic.

Cheap and more available sites.




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Here are our subscribers who want 144kbps duplex data

service.

Base Stations close to traffic demand.

Coverage only Calculation:

UL: 3dB InterferenceDL: 1W CPICH


Base Stations away from traffic.

Coverage only Calculation:

UL: 3dB InterferenceDL: 1W CPICH





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• Intracell and Intercell Interference calculated on both Uplink and Downlink

• UL and DL Eb/No set points adjusted based upon Handover state, and Fast Power Control Headroom

• Assumptions:• 6dB Soft

Handover Window on DL CPICH

• 20W Max Power per BS

• 0.125W Max Power per Sub

• 3dB Max UL Interference Rise

BS1 BS2

BS4BS3

BS5

BS1

BS2

BS4

BS3

BS5

Run Interference/Power Convergence Algorithm



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BS1 BS2

BS4BS3

BS5

BS1

BS2

BS4

BS3

BS5

Distribution of UL Powers

Power (mW)

No.

of

Sub

s

0510

15202530354045

10 20 30 40 50 60 70 80 90 100

110

120

130

05

101520

Base Station DL Power

BS1 BS2 BS3 BS4 BS5

Powe

r (W

)

051015202530354045

10 20 30 40 50 60 70 80 90 100

110

120

130

05

101520

Base Station DL Power

BS1 BS2 BS3 BS4 BS5

Powe

r (W

)

Power (mW)

No.

of

Sub

s

Distribution of UL Powers

HO Power

• Convergence of UL and DL Interference reveals:

• BS at centres of traffic supports 33 subs (4.75Mbps)

• BS away from centres of traffic only supports 22 subs (3.17Mbps)

• 50% improvement in duplex capacity!

• Lots more power remaining in BS at centres of traffic for additional DL power and hence capacity

• 100% improvement in DL capacity

Guidelines – Site Placement3.17Mbps4.75Mbps



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UMTS Downlink Range as a function of Capacity and Average User i for αα a v g = 0.6 (ITU Vehicular Channel A)

0

1

2

3

4

5

6

0 1000 2000 3000 4000 5000 6000

Throughput (kbps)

Ran

ge (

km)

10%

25%

50%

75%

90%

Average i

UMTS Downlink Range as a function of Capacity and Average User i for αα a v g = 0.9 (ITU Pedestrian Channel A)

0

1

2

3

4

5

6

0 1000 2000 3000 4000 5000 6000

Throughput (kbps)

Ran

ge (

km)

10%

25%

50%

75%

90%

Average i

UMTS Uplink Cell Range vs. Cell Capacity

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 500 1000 1500 2000 2500

Cell Throughput/Capacity (bps)

Ran

ge (

km)

10%

25%

50%

75%

90%

i

GSM Uplink and Downlink Range as a function of Uplink and Downlink Capacity

0.00

0.50

1.00

1.50

2.00

2.50

3.00

0 500 1000 1500

Load (kbps)C

ell R

adiu

s (k

m)

Downlink

Uplink

Po

orl

y O

ptim

ise

dP

oo

rly O

ptim

ise

d

Po

orl

y O

ptim

ise

d

Be

tte

r O

ptim

ise

d

Be

tte

r O

ptim

ise

d

Be

tte

r O

ptim

ise

d



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• Five Reasons for placing sites at centres of demand:

• 1. Minimise DL Power per link. Maximises DL Power availability

• 2. Minimise UL Inter-cell Interference

• 3. Minimise DL Inter-cell Interference

• 4. Minimise SHO and resulting DL Power, and DL Inter-cell Interference

• 5. Minimise UL Eb/No by ensuring UL Fast Power Control has full dynamics

• All the reasons fully detailed in Mason White Paper, included with course.



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Guidelines – Multi-Operator Interference

• The influence on Performance of Adjacent Channel Interference between Two (or more) Operators.

FDD Uplink

FDD Downlink

TDD

10MHz 14.8MHz 10MHz 10MHz14.6MHz


1900

.0

1920

.3

1900

.3

1919

.9

1979

.719

80.0

2110

.021

10.3

2169

.721

70.0

4.9M

Hz

4.9M

Hz

4.9M

Hz

4.9M

Hz

MH

zM

Hz

GSM Planning Tools often provided Frequency Planning Algorithms to aid Frequency Planning based upon criteria such as Interference minimisation. In UMTS there is no real concept of Frequency Planning as all cells use the same physical spectrum. The analogy would be Code Planning. However, as there are 512 codes to choose from the code planning is a trivial task. When/if Multiple-Beam Phased Array antennas become available a base station site may have many sectors, for example 64 sectors as individual beams, hence the allocation of 512 codes for downlink code planning.



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• Adjacent Channel Interference power Ratio (ACIR) is defined as:

Channel(s)Adjacent in the MeasuredPower Power Channel dTransmitte

ACIR =

Wanted Carrier

Transmitter

Wanted Carrier

Transmitter

Transmission StationsReceiver Station

=

The (Mobile or Base Station) Transmitters ability to suppress Power into Adjacent Channels is termed in 3GPP as Adjacent Channel Leakage Ratio (ACLR). For the Mobile Terminal this is specified in 25.101 Section 6.

For both Uplink and Downlink Transmitters 3GPP Specifies that the ACLR for the 1st

Adjacent Channel is 33dB and the ACLR for the 2nd Adjacent Channel is 43dB.

The (Mobile or Base Station) receivers ability to reject Power received from an Adjacent Channel is termed in 3GPP as the Adjacent Channel Selectivity (ACS). For the Mobile Terminal this is specified in 25.101 Section 7.

Adjacent Channel Interference power Ratio (ACIR) is the general term used to represent the measured or received Transmitted Power in the Wanted Channel divided by the Power Received in the Adjacent Channel.



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ACIR

In this scenario the Subscriber has a link to the Operator 1 Base Station. As the subscriber is at a distance the Subscriber terminal needs a significant Tx Power. The Subscriber is also near Operator 2’s Base Station which operates on the Adjacent Channel. The Subscriber (and Operator 2’s Base Station) will see a significant adjacent power or low ACIR.

Wanted Carrier

Transmitter

Transmission Stations Receiver

Station

Sub 1 Tx Power = 21dBm

Operator 1 RxOperator 2 Rx

ACIR

The top part of the slide represents the General situation where two different Operators Base Stations are Transmitting on Adjacent Channels. The Mobile wishes to receive the Blue Channel, but also receives the Adjacent (Red) Channel Power. The Base Stations have ACLR to meet the 3GPP Specifications and hence the shape of the Power Spectra on the left.

At the Mobile Power is received in the Wanted (Blue) and Adjacent Channel (Red) as shown. In fact the shape of the Red Power Spectrum would be ‘squashed’ because of the Mobile ACS of 33dB – the effect of this is not shown and therefore represents the power at the mobile rather than after filtering. The shape of the Red power spectrum in the Wanted (Blue) area would be unaffected of course, as the Mobile receiver is tuned to this wanted channel.

The ACIR for this general situation is shown on the top right. This will vary of course depending upon Base Station Powers, and distances from the Mobile.

The bottom portion of the slide illustrates this for the Uplink case (Base Station Receiving, rather than the Mobile Receiving).



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The worst case scenario for ACIR is presented. This occurs when a Mobile transmits on Full Power veryClose to a Base Station that is receiving on the Adjacent Carrier. The closest a Subscriber terminal can get toA Base Station is limited, as Base Stations are at a height and away from proximity of people. The smallest Propagation loss we can expect is around 50dB between any Subscriber and Base Station.

Sub 1 Tx Power = 21dBm

Operator 1 Rx

Operator 2 Rx

P1 = 21dBm – 50dB = -29dBm

P2 = 21dBm – 50dB –33dB = -62dBmP3 = 21dBm – 130dB = -91dBm

In this slide we examine a Worst Case Scenario regarding ACIR.

We have Mobile 1 subscribed to Operator 1 and Mobile 2 subscribed to Operator 2. Mobile 1 is at the maximum distance from Operator 1’s Base Station and is transmitting on Full Power, which we assume to be 21dBm. The coupling loss (propagation loss plus gains and losses) between Mobile 1 and Operator 2’s Base Station is 50dB (typically the minimum we would expect). Mobile 2 is also at a significant distance away from Operator 2’s Base Station and is transmitting at full power, 21dBm, and has a coupling loss of 130dB.

The Received Power in the Wanted Channel at Operator 2’s Receiver is shown. We would expect the wanted Mobile 2 Power to be 21dBm – 130dB = -91dBm. The Adjacent Channel power at Operator 2’s Base Station Receiver is equal to 21dBm – 50dB = -29dBm. Given that Mobile 1 has a channel filters such that they achieve 33dB ACLR as required by the 3GPP Specification, we would see power from Mobile 1 in the Wanted Channel of around –62dBm.

The received power at Operator 2’s Base Station Receiver from Mobile 2 would be 21dBm – 130dB = -91dBm. This means that the wanted signal is well below the interference. A Link between Mobile 2 and Operator 2’s Base Station could still be maintained depending upon the Processing Gain of the Service carried by Mobile 2. This clearly shows that the Range at least of Operator 2’s Base Station would be severely limited by the presence of a mobile using the Adjacent Channel.

Although this situation looks very bad and could severely cripple range at an Operators Base Station this Worst-Case Scenario should be a rare occurrence, particular if care istaken in choosing the Base Station location in order to minimise the likelihood of low Coupling losses. Also, if such a situation arises it may be possible to handover other subscribers on the crippled cell to other cells, or even another Carrier from the same cell.



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• Given the example shown in the previous slide it is apparent that another operator’s Mobile near a Base Station could cripple Range.

• In fact we also need to consider the Downlink situation. We would find a similar set of events and it is likely that a downlink channel would not exist (Op 1 BS to Mobile 1) due to receiver blocking at Mobile 1 from Op 2 BS.

• This blocking is likely to drop the call to Mobile 1 and therefore Mobile 1 will not cripple Operator 2’s range.

• The dropping of one mobile (Mobile 1) is better than Crippling Range to many other Mobiles!

In the Downlink situation we need to consider a similar set of parameters. In the Downlink we would use the Receivers ability to reject Adjacent Channel Power. 3GPP Specifies that Receivers should have a minimum Adjacent Channel Selectivity (ACS) of 33dB for the 1st

Adjacent Channel, and 43dB for 2nd Adjacent Channel.

The Worst-Case Uplink scenario was demonstrated in the previous slide and it was shown that other Operator’s mobiles close to a Base Station could severely cripple potential range of the Base Station’s Uplink. What we may find in reality is that if we looked at the Downlink situation also, we may find that the mobile causing interference and crippling the Uplink Range will drop its call since its downlink may be blocked due to poor ACIR. It is likely that the Mobile Receiver will have a poorer Filter than the Base Station Receiver and hence the Downlink is likely to drop first. In this case we will have removed one mobile from the network, rather than potentially removing or limiting many.



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• If we were to collocate Operators at the same Base Station then we would minimize the chances of this Near-Far multi-operator Interference.

• It is therefore good practice to:

• Co-site Base Stations, particularly with Operators on the Adjacent Channel

• Avoid the possibility of low coupling losses bysiting antennas away from traffic sources

FDD Uplink


1920

.319

19.9

1979

.719

80.0

Share Sites = Good practice

PPOO

Low Probability of Low coupling Losses

High Probability of Low coupling Losses



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• Use of FDD Carrier Pairs Optimisation:Strategic decision by operator to manage his own UMTS spectrum. Can create an optimised network by careful selection and deployment of Macro and Micro cellular layers in a HCS network strategy. Can be tackled tactically but is more difficult.

When Carriers 2&3 used as Macro Layer at an Operators base station site, Operator can move Centre Freqs. closer together. ACLR Managed as same site used, and offers greater ACLR from Adj. Operator #2, who may not be a site sharer.

When Carriers 2&3 used as Macro Layer at an Operators base station site, and Operator shares site with Adj. Operator #2 then ACLR is managed.

Adjacent Operator 2

Adjacent Operator 1

Carrier 1

Carrier 2

Carrier 3



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Guidelines – Antenna Beamwidth

• Base Station antenna beamwidth Optimisation:Strategic decision by operator to offer a range of antennas, and antenna beamwidths to engineer handover boundaries, coverage overlap, and interference containment.

• Base Station sectorisation Optimisation:Strategic decision by operator to offer a range of sectorisation options, to cater for low and high density demand areas. Also relates to antenna beamwidth options.

Uplink Coverage probability and Users Served as a Function of Antenna Sectorisation and Beamwidth

84%

86%

88%

90%

92%

94%

96%

98%

0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0

Network Capacity (Mbps)

Co

vera

ge

Pro

bab

ility

(8K

bp

s)

3-Sectored 120deg3-Sectored 90deg3-Sectored 65deg

3-sectors

4-sectors

6-sectors

4-Sectored 120deg4-Sectored 90deg4-Sectored 65deg4-Sectored 33deg6-Sectored 120deg6-Sectored 90deg6-Sectored 65deg6-Sectored 33deg

From example shown in UMTS Link Budgets section



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Guidelines – Antenna Downtilting

• Base Station Antenna Tilt Optimisation:Very powerful means to optimise coverage, soft handover areas, interference and hence capacity of the network. Careful selection of antennas elevation beamwidths, mechanical and electrical downtilt over a network of sites can improve capacity by over 50%. In principle antenna downtilts could be the key optimisation parameter for a UMTS network. As a result downtilts maybe adjusted very frequently as the network grows, and could in the limit be continuously in adjustment.

Uplink i and Cell capacity as a Function of Antenna Tilt for 3-Sectored 65o antennas

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More Simulators

Link Level Simulators:A Single (few) Links are Modelled

Models:Channel Dynamics ModelledFast Fading ModelledFast Power Control

Determines:Eb/NoSHO GainsFast Power Control Gains

Allows analysis of:Error Correction codesInterleaving schemes

Time resolution:Chips

Who uses this:Equipment Vendors

System Level Simulators:Many Links are modelled

Models:Single Snapshot ConvergenceAverage PowersPath Loss

Determines:Coverage, CapacitySensitivitiesRadio Resource Managementapproaches

Allows analysis of:CoverageCapacity and InterferenceRadio resource Management

Time resolution:1500 times/sec

Who uses this:RF Planning Strategy Teams

Network Level Simulators:Thousands of Links Modelled(Dynamic or Static)

Models:Monte-Carlo Snapshots (Many)Average PowersPath Loss

Determines:Coverage, CapacityQoS Targets

Allows analysis of:CoverageCapacity and Interference

Time resolution:Not Applicable

Who uses this:RF Planners

1996 1998 2000



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• ACTIX– Predictor

• AETHOS– Odyssey

• AIRCOM– ASSET– 3G

• ATDI– HTZ Simulation– ICS Telecom

• CNET– Wings

• CONTACTICA-AXIS– Contactica-Axis

• CRIL INGENIERIE– Ellipse NPT

• DERA/Science Systems

– Crumpet

• FORSK

• Atoll

• GEC-MARCONI– Covmod/Express

• MSI– PlaNet

• MULTIPLE ACCESS– NP Workplace

• NTL– Aspect 4

• QUOTIENT– Quantum

• RCC– Romulus

• SIMOCO– Optair

• SOFTWRIGHT– TAP

Deterministic Prediction ModelsRF Planning Tools - Platforms

The slide lists some of the more common Radio Planning Tool packages available on the Market.



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• Many Radio Prediction and Planning Tools Available

• Some of them are listed, however the list is not exhaustive

• Many tailored to specific technologies or radio services– MSI’s PlaNet - GSM, PCS, CDMA, AMPS, TACS, and

WLL– SIMOCO’s Optair geared towards TETRA Networks– ATDI’s ICS Telecom - Generic

• Unix Workstation Platforms

• PC (Windows&NT) becoming more common

Deterministic Prediction ModelsRF Planning Tools - Platforms

There are many tools tailored for specific technologies, such as GSM, UMTS, FWA or TETRA. Some Planning Tools are much more Generic, not being tailored for any particular technology, and lend themselves to Inter-Technology co-ordination, spectral pollution studies, etc. As such these tools are often used by Regulators, Universities, and Consultancies.

Some tools are designed to be ran on Unix operating systems and some are designed to be ran on PC or NT systems. It is becoming more common that tools run on the Windows or NT PC Operating Systems.



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ASSET & 3G

• Tool selected for use by Hutchinson Orange Switzerland, Esat Digifone•Developed by Aircom•Future plans involve making 3G independent of Asset•Multi standard capabilities e.g. UMTS, TDMA and TETRA•Runs on Windows platform

Asset & 3G from Aircom

1. Modular design;3G module works in conjunction with existing Asset program though it will stand alone in later editions

2. Calculations based on “snapshots” of scenarios

3. Deterministic

4. Uses centralised processing



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QUANTUM 3G

• Developed by Quotient Communications

• Based on Quantum 2G with enhancements for 3G

• Includes a Real estate database to support site selection and acquisition

Quantum 3G developed by Quotient Communications

1. Works on both Unix and Windows platforms

2. Developers claim to be able to configure it to work in a number of processing configurations. Centralised processing however is the most likely config.

3. Deterministic

4. Calculations based on “snapshots”

5. Roadmap has version 4.2 coming out in Q2 2001 with “enhancements”



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ODYSSEY

• Developed by Logica • Runs on both Unix and Windows platform •Supports multiple technologies from GSM to WLL• Distributed Computing Environment• In use by BTCellnet

Odyssey for 3G

1. Uses distributed processing

2. It has an open architecture design, which enables integration with existing systems.

3. Supports both ASCII and Oracle databases on its hybrid system of object oriented design and relational database architecture



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ROMULUS

• Developed by RCC Consultants Inc

• Multi technology support

• Support for multiple propagation models and parameters

• Compatibility with third party applications e.g. Atlas GIS and Mapinfo

ROMULUS

1. Runs on a UNIX based platform

2. Deterministic

3. Includes vehicular traffic data in analysis



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DECIBEL PLANNER

• Developed by Northwood• Multi technology capabilities•Integrates with Map Info•Able to model multimedia services to be offered with UMTS

DECIBEL PLANNER

• Northwood offers tailored data sets, technical support, implementation services and custom development

• Integrates Customer Relationship Management and marketing data

• Uses deterministic propagation models



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PLANET

•Developed by MSI•Works on both Windows and Unix platforms•12 month rolling road map where updates are developed as needed

PLANET

Ø Distributed Processing

• Product Overview after 3yrs

• Calculations take motion of users into consideration

• Analysis is deterministic



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Where Are We Now?

UMTS Radio Planning

Summary

NetworkDesign


Polygons

Site Placement

Antenna Placement

Frequency Planning


LinkBudgets





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Summary

• In this section on The Planning Process you have learnt about• The dynamic nature of UMTS prediction• The need to perform a Snapshot Convergence• The need to perform many Snapshots to get confidence• WCDMA Planning Tools for UMTS

• This section is important to you because• It describes the processes and tools which are fundamental to

your job as a planner

• GSM Planning concentrated upon Coverage

• UMTS Planning concentrates upon Interference Minimisation and Capacity planning



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The End of UMTS Planning Process

UMTS Overview

Access Methods

WCDMA Introduction

UMTS Model Architecture

UMTS Specifications

Path Loss

Course Overview

Comms Theory

DiversityBasic Radio Principles

Intro to Planning Tools

Intro to LinkBudgets

CourseWash Up

Local Mean Signal

Narrowband Channel

Antenna Part I

Wideband Channel

Antennas Part II

WCDMA Physical Layer

UMTS Link Budgets

Site PlacementInterference


CourseWash Up

Statistics

Notation

Course Overview

Introduction to UMTS

Intro to Radio Planning

Mobile RadioChannel

UMTS Design Elements

UMTS Network Design

Diversity

Matched Filters and

Rake ReceiversUMTS Planning

Process

Any MoreQuestions?



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