LTE femtocell density modelling - de.mathworks.com fileLTE femtocell density modelling Michael Fitch...

LTE femtocell density modelling

Michael Fitch

Chief of wireless research

Technology Services and Operations

BT Adastral Park, IP5 3RE

October 2014

© British Telecommunications plc

What is a femtocell ?

BRAS LTE EPC

Internet

BT broadband

Home

hub

LTE femto

cell

A femocell is a very small cell designed to cover a large house

with broadband - and to about 30m outside the house for voice and web browsing.

Typical transmit power is < 100mW at 2.6GHz.

DSLAM

Long Term Evolution Evolved Packet Core

Broadband Remote Access Server

Digital Subscriber Line Access Multiplexer


Benefits of doing the modelling

• For BT, it gives guidelines on the conditions and confidence under which we can deploy femtocells,

• For the consumer, it gives confidence of the experience of voice and data

• Gives installation guidelines and shows the importance of having interference mitigation mechanisms in place


The applications we used in the modelling

UE type Range from

femtocell

Location Max bit-rate

needed

Set-top

Box (STB)

Up to 8m Inside only 20 Mbit/s

Voice (VoLTE) Up to 30m Inside and

outside

LoS

25kbit/s

Tablet Up to 8m Inside only 4Mbit/s

Smart phone

(Googler)

Up to 8m Inside only 500kbit/s

Smart phone

Openzone / Hotspot

Up to 30m Outside only

LoS

500kbit/s


The question • What is the maximum density of femtocells that:

– will support the applications

– and give adequate inside-to-outside coverage

– and give an improved user experience


London Bayswater is a very dense area (10,000 premises in 1 km2), and was chosen as the area to use in the model

Number of BT

served premises

is 3062


So let us set up a model…

• MATLAB was chosen for this task, because

– of the easy ability to run many times and collect statistics

– the structure of the coding using functions enables straightforward debugging and calibration

– the reading and writing of large files is uncomplicated

• The model is based on 3-D geometry and pathlosses


Up to 30m

(LoS)

1

3

4

2 5

Up to 8m

(inside)

Arrangement of different UE

types

1. Set top box (inside)

2. Voice (inside and outside)

3. Tablet with HD (inside)

4. Googler (inside)

5. Hotspot (outside only)


Up to 30m

(LoS)

1

3

4

2 5

Up to 8m

(inside)

Wanted paths are either

totally inside or inside-to-

outside

Wanted paths

1. Set top box (inside)

2. Voice (inside and outside)

3. Tablet with HD (inside)

4. Googler (inside)

5. Hotspot (outside only)


Up to 30m

(LoS)

1

3

4

2 5

Up to 8m

(inside)

Unwanted inside

to outside interference

(nLoS and LoS)

Unwanted inside

to inside interference

(nLoS and LoS)

Interference from neighbouring

femtos is inside-to-inside or

inside-to-outside

Wanted paths


Outline method of modelling outage probability • Femtocell locations are chosen at random from the test area, with a density

of 0.01 to 1,

• The horizontal position is dithered, otherwise all femtocells would be in the exact centre of the property,

• One UE of each type is placed around each femtocell, 1.5m from the floor

• For each UE the 3D matrix of pathlosses is calculated, and the UE is attached to the home one (STBs) or the best one (other UEs) unless the best one is full, then it drops back to second best etc. UEs are attached in priority order,

• For every UE, SINR is calculated, required resource blocks is calculated and the femtocell loadings are tracked, max load on any femto = 90%,

• An abstraction of the scheduler assumes that interference can be mitigated from the two nearest neighbours, until the load-demand product exceeds a threshold


Model flow

Input a probability of a

broadband line having

a femtocell

Randomly place

cells Put one of each type of

UE around each cell

Start with highest

priority UE Calculate pathloss

to every femtocell and

sort

Lowest pathloss is

wanted femtocell.

Calculate wanted signal

Calculate unwanted

signal by summing

signals from other cells

Calculate wanted /

unwanted and look up

spectral efficiency

Calculate resource

blocks taken by UE

and keep track of loading

When loading > max

then UE cannot get

what it needs

Increment outage

count for that UE type


Model flow



a femtocell

Randomly place


UE around each cell

Start with highest



sort

Lowest pathloss is

wanted femtocell.


Calculate unwanted

signal by summing


Calculate wanted /


spectral efficiency

Calculate resource

blocks taken by UE


When loading > max

then UE cannot get

what it needs

Increment outage


Repeated for other UEs


Model flow



a femtocell

Randomly place


UE around each cell

Start with highest



sort

Lowest pathloss is

wanted femtocell.


Calculate unwanted

signal by summing


Calculate wanted /


spectral efficiency

Calculate resource

blocks taken by UE


When loading > max

then UE cannot get

what it needs

Increment outage


Repeated for other UEs

Repeated for other probabilities of deployment to get required density


System assumptions

Parameter Value Comments Femtocell transmit power

(maximum)

13dBm per transmit port

Femtocell transmit power

(minimum)

3dBm per transmit port No UEs in connected mode

Frequency 2600MHz FDD

UE receiver noise figure 7dB

Bandwidth 15MHz

Symbols per second per femtocell 12.6 Million This is 900 sub-carriers * 2000 slots per second * 7

symbols per slot

Transmit overheads 3/14 This is for reference and control signals

Maximum femtocell load 90% The percentage of resource blocks allocated / number

available

Minimum distance a UE can be from any femtocell 1m This limit is tighter than the use-case UEs and is imposed

by the path-loss models

Wall penetration loss (per external wall) 12dB mean, 2dB STD. Minimum loss capped at 2dB. This is for brick or block built housing. Across all building

types, the mean is still 12dB but the STD climbs to 9dB.

Indoor path-loss model ITU-R P.1238-7 + 5dB 5dB correction added as a result of field measurements,

caused by femtocell being low down, 500mm from floor.

Outdoor path-loss model ITU-R P.1411-4 Includes LoS and non-LoS components with 20m

transition region

Minimum required SNR or SNIR -4dB For a UE to be able to attach (based on 1/12 QPSK)


With STB at 10Mbit/s

With STB at 20Mbit/s

Example results - outage probability

No STB


Capacity estimate

• The spread of bit-rates across femtocells is commercially sensitive,

• Below are some broad results that we can share:

Density limit /km2

(femtocells)

Total system capacity /

Tbit/s

300 Max less 30%

900 Max (> 250)

1500 Max less 10%

2300 Max less 30%

No limit A tiny bit less again

So, from the point of view of outages, and of maximising

system capacity, a density of about 1000 per km2 is the

optimum


Some guidelines from the modelling The maximum density is determined by the heaviest user, which in this case is the

set-top box,

STBs should be discouraged from being connected using LTE femtocells

A density of around 1000 per km2 may be a suitable target density

– It allows a good user experience with a low outage probability

– It gives the maximum system capacity


The question – how well answered ? • Can we deploy LTE femtocells at a density that is high enough so we can send

one to every BT broadband customer: - almost

– while supporting the applications in the business case

• Yes except for STBs

– and give inside-to-outside coverage that is comparable to WiFi

• Yes

– and give an improved experience with voice and data

• For voice yes, for data maybe – for further work

– and give a reduction in customer complaints (propensity to call)

• Remains to be seen

– and cost the consumer no more, and cost BT as little as possible…

• Ongoing work


The question – how well answered ? • What is the maximum density of femtocells that:

– will support the applications

– and give adequate inside-to-outside coverage

– and give an improved user experience

• About 1000 per km2


A bit about the MATLAB implementation

• Probability based (no time functions)

– Although we are now developing this, a per-TTI simulation

– LTE toolbox not used in current model

• Biggest challenges

– Handling and sorting large files • Input files are .txt with around 6 million lines

• Fastest way of sorting into histogram is using integer division and direct allocation to kilometre squares

– Working through large matrix calculations • Up to 3000 * 3000 * 5 radio path-losses and summing interference

• Would do better by implementing a nearest neighbour function using tree structure, and then ignoring path-losses that are above a threshold


Example code for sorting broadband lines into tiles

load 'bblocsx.txt'

load 'bblocsy.txt'

num = size(bblocsx);

for i = 1:num

xint(i) = uint32(round(bblocsx(i)));

yint(i) = uint32(round(bblocsy(i))); end

a = max(xint);

b = max(yint);

sq = zeros(a, b);

for i = 1:num

if xint(i)~= 0 && yint(i) ~= 0 % If the square km has a location

sq(xint(i), yint(i)) = sq(xint(i), yint(i)) + 1;

end

end

% m = 1;

% for i = 1:a

% for j = 1:b

% for k = 1:num

% if xint(k) == a && yint(k) == b

% sq(m) = sq(m) + 1;

% end

% end

% m = m + 1;

% end

% end

[a, b] = size(sq);

sqr = reshape(sq, a * b, 1)

[h, values] = hist(sqr(sqr~=0), 100);

c = cumsum(h);

x = sum(h);

Not

efficient!

Efficient!


Many thanks for listening

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