Fixed Wireless to the Home - icics.webi.it.ubc.cawireless networks, there are some differences that...

Fixed Wireless to the Home

Derek McAvoy, May 12, 2017

| 5/12/2017

Industry Overview

• Fixed Wireless to the Home has been getting increased attention lately due to recent developments in 5G technology• Verizon and AT&T have been promoting the use of mmWave technology as an alternative method to

deliver TV and Internet services to the home, thus competing against incumbent cable service operators and incumbent wireline operators

• In many cases, mmWave 5G technology is more cost effective than fibre to the home

• While not grabbing as much headlines, sub-6GHz wireless technology is also being considered for providing high speed Internet services • mmWave 5G is most economical in urban and dense suburban morphologies

• For light suburban and rural morphologies, the economics for sub-6GHz are more favourable

• While there are many similarities between mobile wireless networks and fixed wireless networks, there are some differences that will make fixed wireless networks more spectrally efficient than mobile wireless networks• That’s a good thing, since home Internet usage is far higher than mobile Internet usage

| 5/12/2017

3 Pillars

• 3 Pillars of Information Theory• Signal-to-Noise Ratio

• Bandwidth

• Number of channels

• 3 Pillars for Wireless Operators• Capacity

• User Experience (data speeds)

• Coverage

• 3 Pillars of Wireless Engineering• Queuing Theory

• Information Theory

• Stochastic Geometry

• 3 Pillars of Big Data• Regression

• Monte Carlo Simulation

• Deep Learning

A lot of analysis is required to determine the capabilities of wireless networks. The only pillar that is not used/considered is Deep Learning.

| 5/12/2017

3 Pillars of Information Theory

With the advent of turbo coding and LDPC codes, today’s communication systems can come fairly close to the Shannon Capacity limit.

Note that to increase capacity, one can either

1. Increase the bandwidth

2. Increase the signal-to-noise ratio (SNR)

3. Increase the number of channels or the proportion of the channel used

Capacity / Channel = Bandwidth * log2(1 + Signal / Noise)

Capacity = Channel * Bandwidth * log2(1 + Signal / Noise)

Shannon Capacity Equation

•Signal-to-Noise Ratio•Bandwidth•Number of channels

| 5/12/2017

3 Pillars for Wireless Operators

• There is much confusion regarding the capacity of the channel and the speed of the channel as experienced by the customer• For example, a service provider might sell an Internet service that will offer data speeds of at least

25 Mbps during the busiest hours of the day

• Although it is possible that the subscriber will see data speeds in excess of 25 Mbps during the busy hour, it is very likely the subscriber will download far less than 25 Mbps during the busy hour

• Subscriber may not be at home• The application the subscriber is using may require far less than 25 Mbps• The typical subscriber uses ~1 Mbps of traffic during the busy hour (equivalent to 100 Gbytes/month)

• When many users are sharing a common channel, there is a trade-off between increasing network traffic and providing faster user data speeds (Queuing Theory)• Eg. Suppose the channel can support 100 Mbps. Marketing wants to sell a 25 Mbps service. The

typical subscriber uses 1 Mbps during the busiest hour of day. To be able to provide an average data speed of 25 Mbps, at most 75 subscribers can be supported:

• 75 subs * 1 Mbps = 75 Mbps• Average user data speed = 100 Mbps – 75 Mbps = 25 Mbps

• More subscribers can be supported at the expense of average user data speeds.• 90 subs * 1 Mbps = 90 Mbps• Average user data speed = 100 Mbps – 90 Mbps = 10 Mbps

• There is also a trade-off between capacity and % coverage

•Capacity•User Experience (data speeds)•Coverage

| 5/12/2017

3 Pillars of Wireless Engineering

• Information Theory and Queuing Theory was touched upon earlier

• Although the location of the base station and subscribers appear to be important for certain analyses, to gain general insights on certain wireless techniques, the location of the base stations is not that important• Might as well use regularly spaced base stations to simplify analysis

-79.4 -79.395 -79.39 -79.385 -79.38 -79.375 -79.37 -79.36543.63

43.635

43.64

43.645

43.65

43.655

-79.4 -79.395 -79.39 -79.385 -79.38 -79.375 -79.37 -79.36543.634

43.636

43.638

43.64

43.642

43.644

43.646

43.648

43.65

43.652

43.654

Hypothetical cell site pattern

Actual cell site locations downtown Toronto

•Queuing Theory•Information Theory•Stochastic Geometry

| 5/12/2017

3 Pillars of Big Data

• Regression is used to estimate the location of subscribers given base station operational measurements and configuration• Regression is important when designing for a particular area

• For defining strategy, regression may not be so important

• See previous slide regarding hypothetical vs real network

• Monte Carlo Simulation is used to estimate the key performance indicators (capacity, user data speed, coverage) for various network settings/techniques• Although it may be possible to analyse networks using analytical techniques

(especially when network configuration is regular and subscriber locations are homogeneous), Monte Carlo simulation is a quick and easy method that produces results in a timely manner

• Deep Learning: not used

• The main importance of Big Data is to generate insight• Big Data could also be used to improve network operation, but currently it is

used to define future network strategy and answering regulatory questions

•Regression•Monte Carlo Simulation•Deep Learning

min

Formula to determine subscriber location

| 5/12/2017

LTE OFDM Downlink Frame Structure

The proportion of time that the LTE carrier is actually carrying data is referred to as the PRB utilization (0 -%100).

When there is no data being transmitted, the LTE radio is still transmitting reference symbols. Reference symbols account for ~10% of the bits.

| 5/12/2017

SINR, C/I, SNR Definition

• SINR = S / (I + N)• S – Signal Strength

• I – Power of interference

• N – Thermal Noise (kTB plus receiver front end noise figure)

• C/I = C / I = S / I• C – Carrier Strength

• Signal Strength of Desired Signal• Same as variable S in the SINR equation

• I – Power of interference

• SNR = S / N• S – Signal Strength

• N – Thermal Noise (kTB plus receiver front end noise figure)

• Why do we need all 3 variables?• Although data speeds are a function of SINR, it helps in the analysis to understand how network

performance is affected by thermal noise and interference individually

• Some networks are noise limited, while other networks are interference limited

| 5/12/2017

LTE Data Speeds for Various Configurations

Although the abscissa is specified as SNR, the same graph is used when the SINR is specified

From Rysavy Research Transition to 4G 3GPP Broadband Evolution to IMT-Advanced

| 5/12/2017

Two Use Cases

• Use Case 1: Wireless Internet to the home in Urban / Dense Suburban morphologies using LTE Small Cells• Although there has been much press about serving residences with 5G mmWave, perhaps it is

possible to use 4G LTE to provide a usable service in urban / dense suburban neighborhoods.

• Use Case 2: Wireless Internet to the home in rural / light suburban morphologies• There is a lot of 3.5 GHz spectrum in Canada that can be used to provide fixed Internet in rural

areas

| 5/12/2017

Use Case 1: Fixed Wireless Using 16 Small Cells

Omnidirectional Small Cell Omnidirectional CPE

| 5/12/2017

4 Main Graphs – Default Case

02468

1012141618

0 0.2 0.4 0.6 0.8 1

Use

r Dat

a Sp

eeds

(Mbp

s)

PRB Utilization

Average Cell Edge

02468

1012141618

0 20 40 60 80 100

Use

r Dat

a Sp

eeds

(Mbp

s)

Network Load (Mbps)

Average Cell Edge

02468

101214161820

0 0.2 0.4 0.6 0.8 1

(dB

)

PRB Utilization

SINR C/I SNR

0

0.2

0.4

0.6

0.8

1

1.2

0 0.2 0.4 0.6 0.8 1

Spec

tral

Effi

cien

cy (b

ps/H

z)

PRB Utilization

All PRB Active PRB

10 d

B

| 5/12/2017

Default +10dB

0

5

10

15

20

25

0 0.2 0.4 0.6 0.8 1

Use

r Dat

a Sp

eeds

(Mbp

s)

PRB Utilization

+10 dB Default

0

5

10

15

20

25

0 20 40 60 80 100 120

Use

r Dat

a Sp

eeds

(Mbp

s)

Network Load (Mbps)

+10 dB Default

0

5

10

15

20

25

30

0 0.2 0.4 0.6 0.8 1

(dB

)

PRB Utilization

SINR C/I SNR

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 0.2 0.4 0.6 0.8 1

Spec

tral

Effi

cien

cy (b

ps/H

z)

PRB Utilization

+10 dB Default

Interference Limited: SINR matches C/I

| 5/12/2017

Use Case 1 (Continued): Fixed Wireless Using Directional CPE

Directional CPE

| 5/12/2017

Directional CPE, 0dB gain

0

5

10

15

20

25

0 0.2 0.4 0.6 0.8 1

Use

r Dat

a Sp

eeds

(Mbp

s)

PRB Utilization

Directional CPE Default

0

5

10

15

20

25

0 50 100 150 200 250

Use

r Dat

a Sp

eeds

(Mbp

s)

Network Load (Mbps)


0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 0.2 0.4 0.6 0.8 1

Spec

tral

Effi

cien

cy (b

ps/H

z)

PRB Utilization


0

5

10

15

20

25

30

35

40

0 0.2 0.4 0.6 0.8 1

(dB

)

PRB Utilization

SINR C/I SNR

Noise Limited: SINR matches SNR

| 5/12/2017


05

1015202530354045

0 0.2 0.4 0.6 0.8 1

Use

r Dat

a Sp

eeds

(Mbp

s)

PRB Utilization


05

1015202530354045

0 100 200 300 400 500 600

Use

r Dat

a Sp

eeds

(Mbp

s)

Network Load (Mbps)


0

0.5

1

1.5

2

2.5

3

3.5

0 0.2 0.4 0.6 0.8 1

Spec

tral

Effi

cien

cy (b

ps/H

z)

PRB Utilization


05

1015202530354045

0 0.2 0.4 0.6 0.8 1

Use

r Dat

a Sp

eeds

(Mbp

s)

PRB Utilization

SINR C/I SNR

| 5/12/2017

Use Case 1 (Continued): Fixed Wireless Using 16 Smalls Cells & 1 Macrocell - Omnidirectional CPE

MacrocellSmall Cell

| 5/12/2017

Fixed Wireless Using 16 Smalls Cells & 1 Macrocell: Omnidirectional CPE

02468

101214161820

0 20 40 60 80 100 120

Use

r Dat

a Sp

eeds

(Mbp

s)

Network Load (Mbps)

1 macro 0 macro

0

1

2

3

4

5

6

0 20 40 60 80 100 120

Use

r Dat

a Sp

eeds

(Mbp

s)

Network Load (Mbps)

1 macro 0 macro

Avg Speed vs Load Cell Edge Speed vs Load

0

5

10

15

20

25

0 0.2 0.4 0.6 0.8 1

SNR

(dB

)

PRB Utilization

SINR C/I SNR

0

5

10

15

20

25

0 0.2 0.4 0.6 0.8 1

SNR

(dB

)

PRB Utilization

SINR C/I SNR

1 Macro

0 Macro

The addition of one Macrocell decreases capacity by 50%!!!!

| 5/12/2017

Use Case 2: Rural Coverage using Macrocells

• Macrocellular towers used to provide mobile service can also be used to provide fixed service

• For certain use cases, the location of subscribers are known• The service provider can select which subscriber locations can be served

• The main criteria would be sufficient signal strength although serving cell congestion could also be used

• 4 scenarios will be considered. Minimum SNR thresholds are:• 3 dB• 6 dB• 7.8 dB• 10 dB

• There is not only a trade-off between traffic and user data speed, there is a trade-off between coverage and traffic and user data speed• The coverage is determined by the minimum SNR threshold

| 5/12/2017

Spectral Efficiency vs Inter Site Distance

When the minimum SNR threshold is between 7.8 –10 dB, spectral efficiency appears to be independent to the inter site distance (~0.8 bps/Hz)

| 5/12/2017

Coverage vs Inter Site Distance

Choosing a larger SNR threshold negatively impacts the percentage of household eligible to receive service.

| 5/12/2017

SINR for Minimum SNR Threshold = 10dB

SINR curves becomes flatter at larger intersitedistances.

Fixed Wireless to the Home - icics.webi.it.ubc.cawireless networks, there are some differences that...

Documents

Transcript of Fixed Wireless to the Home - icics.webi.it.ubc.cawireless networks, there are some differences that...