LTE RF Design and Optimization

1 CUSTOMER CONFIDENTIAL

LTE RF Design and Optimization

Optimi Operator’s WorkshopOct. 6th & 7th, 2009


LTE RF Design and OptimizationLTE RF Design and OptimizationLayout

Introduction

Overall RF Design and Optimization Process

Design Input

Design Objectives

Pathloss Model

Benchmarking of LTE Design Objectives

Site Selection and RF Optimization

Summary


IntroductionIntroductionUTRAN Long Term Evolution (LTE)

LTE belongs to the next generation of mobile systems recently standardized in 3GPP

Orthogonal Frequency Division Multiplexing (OFDM)

Adaptive modulation and coding with hybrid ARQ

Fast packet scheduling with full flexibility in time and frequency

Full spectrum flexibility with BW ranging from 1.4 to 20 MHz

Standardized MIMO support with up to 4 antennas on each side


Overall RF Design and Optimization ProcessOverall RF Design and Optimization ProcessGeneral Overview

Static SimulatorNominal Design

OptimizerTuned Configuration

Static SimulatorImproved Performance

RF Planning ToolPredictions

RF Planning ToolRe-assessing Predict.

Fin

e T

un

ing

SINR, data rate and quality network information is provided based on pathloss [more details in next slides]

Static SimulatorOptimized Performance

After optimization predictions may be re-calculated for the sake of providing better accuracy

Optimized results are obtained using re-calculated predictionsfrom the RF planning tool

Sites are selected and tilt, azimuth, power, etc. are tuned to improve the performance within the specified constraints

Results are analyzed via a static simulator. The process can be repeated for a finer tuning

Path-loss predictions are obtained based on propagation models maybe combined with drive tests and OSS


Design InputDesign InputBasic Parameters

Physical ParametersTerrain attributes, clutter type, antenna location (latitude and longitude) and antenna configuration (azimuth and tilts)

Generation of PredictionsPropagation models, drive tests, OSS data, call traces, etc.

eNode-B Parameters: PA power, pilot power, cyclic prefix, IoT level, network load, noise figure, etc.

UE ParametersTX power, antenna gain, noise figure, etc.

Duplexing ModeFrequency Division Duplex (FDD) � different channels for DL and UL

Time Division Duplex (TDD) � sharing in time a single frequency for DL and UL


Design InputDesign InputLink Level Mapping Table

3GPP TR 36.942 V8.2.0

0

1

2

3

4

5

6

7

-10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20

SNR, dB

Th

rou

gh

pu

t, b

its p

er

seco

nd

per

Hz

MCS-1 [QPSK,R=1/8]

MCS-2 [QPSK,R=1/5]

MCS-3 [QPSK,R=1/4]

MCS-4 [QPSK,R=1/3]

MCS-5 [QPSK,R=1/2]

MCS-6 [QPSK,R=2/3]

MCS-7 [QPSK,R=4/5]

MCS-8 [16 QAM,R=1/2]

MCS-9 [16 QAM,R=2/3]

MCS-10 [16 QAM,R=4/5]

MCS-11 [64 QAM,R=2/3]

MCS-12 [64 QAM,R=3/4]

MCS-13 [64 QAM,R=4/5]

Shannon


Design InputDesign InputStandard Propagation Models

Lee Model Empirically derived area model that is commonly used in the United StatesWireless applications in the 800MHz and 1900MHz range. Applied at higher frequencies, but adjustments must be made to the slope and intercept

Hata ModelMost-popular empirically-derived propagation model for the 800MHz to 2GHz frequenciesWidely used in Asia accurately describing the dense urban environments betterBased on the Japanese propagation environment, different from USA or Europe areas.

COST 231 ModelUp-banded version of Hata Model adjusted for 1800-1900MHz frequency band.

Enriched with correction terms: street width, orientation, building height, etc.

Flexible model frequently used both as a macroscopic and a microcell model.

SUI ModelAn extension of the earlier work by AT&T Wireless and Erceg et al. Widely used for technologies at frequency band higher than 2GHzSelected to test WiMAX due to its accurate estimations at NLOS environments


Design InputDesign InputMultiple Input Multiple Output (MIMO)

eNode-B

… … … UE

eNode-B

… … … UE

SINR Gain

Slight decrease in SINRLarge Throughput Boost

Feedback (Closed-Loop) – Better SINR

TX/RX Diversity

Spatial Multiplexing


Design InputDesign InputMultiple Input Multiple Output (MIMO) (II)

MIMO capability is key feature in LTE to achieve

Ambitious requirements for throughput

High spectral efficiency

Receive and/or Transmit Diversity

Same information is sent/received over multiple antennas

Gain in SINR

Open-Loop Spatial Multiplexing

Different information is sent/received over multiple antennas

Decrease in SINR due to higher interference but large boost in throughput

Closed-Loop Spatial Multiplexing

Same approach as before, but getting advantage of feedback information

Improves de SINR at a cost of more complexity


Design InputDesign InputUplink Power Control (PC)

Classic PC schemes aim all users received with the same SINR

3GPP agreed the use of Fractional PC for Physical Uplink Shared Channel (PUSCH) to compensate for slow channel variations

� Pmax is the maximum user transmit power� P0 is a sector-specific parameter� NRB is the number of allocated RBs� L is the downlink pathloss� α is the pathloss compensation factor

Users with higher pathloss operate at lower SINR requirementsInterference to neighbors decrease

Overall system performance tend to improve

{ }αLnNPPP

RBTX⋅⋅= )(,min

0max


Design InputDesign InputResource Block Planning (I)

Resource Block (RB) planning is a key factor on interference control

A smart allocation can significantly improve the system performance

The radio access technology may impact the RB planning strategy

OFDMA (in DL) allows allocation of non-contiguous bandwidth

SC-FDMA (in UL) forces to allocate contiguous bandwidth

Traditional RB schemes

Full reuse: all sectors within a site share the same bandwidth� Higher peak throughput at a cost of higher interference

One-third reuse: bandwidth shared among the sectors within a site� Lower peak throughput but getting an improvement on SINR

Advanced RB schemes

Dynamic RB Planning: automatic solution to minimize the interference

Inter-Cell Interference Coordination (ICIC): wiser allocation scheme in between full and one-third reuse


Design InputDesign InputResource Block Planning (II) - ICIC

Wise allocation of users generating higher interference to improve the system performance

Cell-edge users, which are assumed to interfere the most, have a limited band to be scheduled

Rest of the bandwidth for cell-center users

Interference coordinationCell-edge band location follows the well-known 3-color pattern within a site

Distance between highly interfering users increases

System bandwidth

cell-center

cell-edge


Design InputDesign InputResource Block Planning (III) - ICIC

No ICIC ICIC with 3 dB offset

Worse SINR in CC

Better SINR in CE


Design ObjectivesDesign ObjectivesLTE Metrics

Time Time SlotSlot

Res

ou

rce

Res

ou

rce

Blo

ck

Blo

ck

(RB

)(R

B)

Ca

rrie

r C

arr

ier

Ba

nd

wid

thB

an

dw

idth

ResourceResource ElementElement (RE)(RE)

RSRP

Average RX power of one REtransmitting RS

RSRQ

RSRP x # RBs

Carrier RX power + Noise


Design ObjectivesDesign ObjectivesCoverage (I)

Indicating if a certain location may have access to the network

Defined by Reference Signal Received Power (RSRP)

Linear average over the power contributions of the REs that carry cell-specific

Reference Signals (RSs) within the considered frequency bandwidth


Design ObjectivesDesign ObjectivesCoverage (II) – Radio Link Budget [Downlink]

3.0RX/TX Diversity Gainm

= d – i – j – k + l + m – n146.8MaximumMaximum Pathloss [Pathloss [dBdB]]

N

l

k

j

i

h

g

f

e

d

c

b

a

= a + b – c 56.0EIRP [dBm]

0.0

0.0

1.0

3.0

-91.8

10.0

-101.8

-106.8

5.0

0.0

13.0

43.0

Body Loss [dB]

RX Antenna Gain [dBi]

Control Channel Overhead [dB]

Interference Margin [dB]

= g + hReceiver Sensitivity [dBm]

for 16QAM 2/3SINR [dB]

= e + fReceived Noise Floor [dBm]

= k (Boltzmann) x T (300K) x B (5MHz)Thermal Noise [dBm]

UE Noise Figure [dB]

Cable Loss [dB]

TX Antenna Gain [dBi]

Transmit Power [dBm]5 MHz – MIMO 1x2 – 10 Mbps


Design ObjectivesDesign ObjectivesCoverage (III) – Radio Link Budget [Uplink]

0.0RX/TX Diversity Gainm

= d – i – j – k + l + m + n127.8MaximumMaximum Pathloss [Pathloss [dBdB]]

n

l

k

j

i

h

g

f

e

d

c

b

a

= 1 + 2 – 3 24.0EIRP [dBm]

2.0

13.0

0.0

2.0

-90.8

6.0

-96.8

-106.8

10.0

0.0

0.0

24.0

MHA Gain

RX Antenna Gain [dBi]

Cable Loss [dB]

Interference Margin [dB]

= g + hReceiver Sensitivity [dBm]

for QPSK 2/3SINR [dB]

= e + fReceived Noise Floor [dBm]

= k (Boltzmann) x T (300K) x B (5MHz)Thermal Noise [dBm]

eNode-B Noise Figure [dB]

Body Loss [dB]

TX Antenna Gain [dBi]

Max Transmit Power [dBm]5 MHz – SISO 1x1 – 5 Mbps


Design ObjectivesDesign ObjectivesQuality

Giving an idea of the level of interference, highly impacting the performance

Defined by Reference Signal Received Power (RSRQ)

RSRP over the wideband received signals from all base stations in the carrier

bandwidth plus thermal noise


Design ObjectivesDesign ObjectivesCapacity

Traffic maps representsActive subscriber’s population spatial distribution

Overall offered load that need to be served by the network

Demand grid, i.e. user spatial location, is based on clutter typesActive users in a dense urban area is much higher than in forest areas

Accuracy improves by network measurements from active users

Marketing information defines traffic volumes and service mixesSo that it is possible to derive the network offered load

Note that each service has specific requirements and hence need to be assigned to different radio access bearers (RAB)

Requested Data Rate: throughput for a user to be satisfied

Minimum Data Rate: throughput for a user to be in the system


Pathloss ModelPathloss ModelRF Planning Tool

Purely Predictions Very vulnerable to database errors and prediction inaccuracy

Interpolation and Drive Tests Extra accuracy and robustness against database errors

OSS Based No need for Drive Test. Extra accuracy from relaying on OSS data

Geolocation Enhanced accuracy from geolocated events

Basic

Advanced


Benchmarking of LTE Design ObjectivesBenchmarking of LTE Design ObjectivesFlow Diagram

Configuration

Monte Carlo Simulator

Analysis

Project Build

Neighbor List

Pathloss

Coverage

SINR

Data Rate

Quality

Reports

System

Sector

User

Service

...


Benchmarking of LTE Design ObjectivesBenchmarking of LTE Design ObjectivesMonte Carlo (MC) Simulator

Monte Carlo simulation solution is used to characterize the radio

performance of LTE at any time of the design process

Quick identification of the best design among multiple candidates

Clearly pointing the main network problems (highest blocked/dropped field)

Required inputs

System, sector and user parameters

Service and traffic set-up

Provided outputs

Accurate estimations for UL and DL loading, and noise rise

Different raster views and text-formatted reports with information about served,

unsatisfied and drop users, offered and carried loading, etc.


Benchmarking of LTE Design ObjectivesBenchmarking of LTE Design ObjectivesReason for Failure


Benchmarking of LTE Design ObjectivesBenchmarking of LTE Design ObjectivesDownlink Data Rate


Site Selection and RF OptimizationSite Selection and RF OptimizationDefinition of Network Planning Criteria

KPIsKPIs per clutterper clutterRSRP threshold: minimum RSRP level to consider a pixel as covered.

RSRQ threshold: minimum RSRQ level to consider a pixel as in good quality.

Weight in order to differentiate the relevance of a clutter type.

Penetration Loss in order to add extra losses.

Global Global KPIsKPIsCoverage: percentage of covered area from signal level (RSRP) perspective.

Quality: percentage of covered area from quality level (RSRQ) perspective

Traffic Quality: percentage of covered area for minimum SNR based on minimum data rate the service requires

Capacity: percentage of sectors at maximum load

Financial cost componentFinancial cost componentMonetary cost per RF change and sector

Necessary to make sure that the proposed RF design meets the budgetary constraints


Site Selection and RF OptimizationSite Selection and RF OptimizationAccomplishing KPI Objectives

The location of potential site comes fromAn existing network, e.g. UMTS.

A “random” deployment over the area of study

Site selection � minimum number of sites to meet target coverage, quality and capacity.

KPI performance frompotential sites

KPI ObjectivesKPI performance after

site selection

KPIs fullfiled with just60% of initial locations

15sites

9sites


Site Selection and RF OptimizationSite Selection and RF OptimizationSelected Sites


Site Selection and RF OptimizationSite Selection and RF OptimizationOptimizing Antenna Setting (I)

Operators have limited amount of resources, but at the same timethey require to fulfill certain Key Performance Indicators (KPIs).

The optimization process aims to improve the overall network coverage, capacity and quality, and enabling operators to make the most out of their limited network resources.

Network attributes that can be modified:

Antenna type

Antenna height

Antenna tilt (mechanical and electrical)

Antenna azimuth

Transmit power


Site Selection and RF OptimizationSite Selection and RF OptimizationOptimizing Antenna Setting (II)

RSRQ Coverage - 81.87% to 85.11%


Site Selection and RF OptimizationSite Selection and RF OptimizationCombined Solution

KPIs are fulfilled with 1 site less


Other FunctionalitiesOther FunctionalitiesCell-ID Planning

According to 3GPP there are 504 unique physical-layer cell identities The different cell-IDs are grouped into 168 unique physical-layer cell-ID groups

Each group containing three unique identities

Each cell-ID is part of one and only one physical-layer cell-ID group

Cell-ID planning aims to

Maximize the radio distance between cell-IDs

Avoid (or minimize) the amount of neighbors with the same cell-ID


SummarySummaryConclusions and Remarks

LTE is a new technology recently standardized by 3GPP

Network deployment is still in study phase

Operators can clearly benefit from� Efficient site selection (based on current 3G sites)

� Optimized antenna configuration to maximize performance

� More accurate pathloss models

LTE key metrics for optimization

RSRP to indicate the network access (i.e. coverage)

RSRQ giving an idea of the link quality

Capacity which is determined by traffic and distribution of users

Advanced LTE features also have an impact on the design

MIMO capabilities to improve SINR and throughput

RB planning (and ICIC) to control interference

Smart schedulers to optimize RB allocation


THANK YOU!

Comments and Questions?

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LTE RF Design and Optimization