LTE RF Design and Optimization
Short Description
LTE...
Description
LTE RF Design and Optimization
Optimi Operator’s Workshop Oct. 6th & 7th, 2009
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CUSTOMER CONFIDENTIAL
LTE RF Design and Optimization Layout
Introduction Overall RF Design and Optimization Process Design Input Design Objectives Pathloss Model Benchmarking of LTE Design Objectives Site Selection and RF Optimization Summary
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CUSTOMER CONFIDENTIAL
Introduction UTRAN 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
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CUSTOMER CONFIDENTIAL
Overall RF Design and Optimization Process
Fine Tuning
General Overview
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RF Planning Tool Predictions
Path-loss predictions are obtained based on propagation models maybe combined with drive tests and OSS
Static Simulator Nominal Design
SINR, data rate and quality network information is provided based on pathloss [more details in next slides]
Optimizer Tuned Configuration
Sites are selected and tilt, azimuth, power, etc. are tuned to improve the performance within the specified constraints
Static Simulator Improved Performance
Results are analyzed via a static simulator. The process can be repeated for a finer tuning
RF Planning Tool Re-assessing Predict.
After optimization predictions may be re-calculated for the sake of providing better accuracy
Static Simulator Optimized Performance
Optimized results are obtained using re-calculated predictions from the RF planning tool
CUSTOMER CONFIDENTIAL
Design Input Basic Parameters
Physical Parameters Terrain attributes, clutter type, antenna location (latitude and longitude) and antenna configuration (azimuth and tilts)
Generation of Predictions Propagation 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 Parameters TX power, antenna gain, noise figure, etc.
Duplexing Mode Frequency Division Duplex (FDD) different channels for DL and UL Time Division Duplex (TDD) sharing in time a single frequency for DL and UL
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CUSTOMER CONFIDENTIAL
Design Input Link Level Mapping Table 7 MCS-1 [QPSK,R=1/8] MCS-2 [QPSK,R=1/5]
Throughput, bits per second per Hz
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MCS-3 [QPSK,R=1/4] MCS-4 [QPSK,R=1/3]
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MCS-5 [QPSK,R=1/2] MCS-6 [QPSK,R=2/3] MCS-7 [QPSK,R=4/5]
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MCS-8 [16 QAM,R=1/2] MCS-9 [16 QAM,R=2/3]
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MCS-10 [16 QAM,R=4/5] MCS-11 [64 QAM,R=2/3] MCS-12 [64 QAM,R=3/4]
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MCS-13 [64 QAM,R=4/5] Shannon
1
0 -10
-8
-6
-4
-2
0
2
4
6
8
SNR, dB
3GPP TR 36.942 V8.2.0 6
CUSTOMER CONFIDENTIAL
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Design Input Standard Propagation Models Lee Model Empirically derived area model that is commonly used in the United States Wireless applications in the 800MHz and 1900MHz range. Applied at higher frequencies, but adjustments must be made to the slope and intercept
Hata Model Most-popular empirically-derived propagation model for the 800MHz to 2GHz frequencies Widely used in Asia accurately describing the dense urban environments better Based on the Japanese propagation environment, different from USA or Europe areas.
COST 231 Model Up-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 Model An extension of the earlier work by AT&T Wireless and Erceg et al. Widely used for technologies at frequency band higher than 2GHz Selected to test WiMAX due to its accurate estimations at NLOS environments
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CUSTOMER CONFIDENTIAL
Design Input Multiple Input Multiple Output (MIMO)
TX/RX Diversity
eNode-B …
…
…
UE SINR Gain
Spatial Multiplexing
eNode-B …
…
…
UE Slight decrease in SINR Large Throughput Boost
Feedback (Closed-Loop) – Better SINR 8
CUSTOMER CONFIDENTIAL
Design Input Multiple 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
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CUSTOMER CONFIDENTIAL
Design Input Uplink 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
{
PTX = min Pmax , P0 ⋅ N RB (n) ⋅ Lα
}
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 requirements Interference to neighbors decrease Overall system performance tend to improve
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CUSTOMER CONFIDENTIAL
Design Input Resource 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
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CUSTOMER CONFIDENTIAL
Design Input Resource 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 coordination Cell-edge band location follows the well-known 3-color pattern within a site Distance between highly interfering users increases cell-edge
cell-center
System bandwidth
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CUSTOMER CONFIDENTIAL
Design Input Resource Block Planning (III) - ICIC
No ICIC
ICIC with 3 dB offset
Worse SINR in CC
Better SINR in CE
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CUSTOMER CONFIDENTIAL
Design Objectives
Resource Block (RB)
Carrier Bandwidth
LTE Metrics
RSRP Average RX power of one RE transmitting RS
RSRQ RSRP x # RBs Carrier RX power + Noise Time Slot
Resource Element (RE)
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CUSTOMER CONFIDENTIAL
Design Objectives Coverage (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
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CUSTOMER CONFIDENTIAL
Design Objectives Coverage (II) – Radio Link Budget [Downlink] a
Transmit Power [dBm]
43.0
b
TX Antenna Gain [dBi]
13.0
c
Cable Loss [dB]
d
EIRP [dBm]
e
UE Noise Figure [dB]
5.0
f
Thermal Noise [dBm]
-106.8
= k (Boltzmann) x T (300K) x B (5MHz)
g
Received Noise Floor [dBm]
-101.8
=e+f
h
SINR [dB]
i
Receiver Sensitivity [dBm]
j
Interference Margin [dB]
3.0
k
Control Channel Overhead [dB]
1.0
l
RX Antenna Gain [dBi]
0.0
m
RX/TX Diversity Gain
3.0
N
Body Loss [dB]
0.0
Maximum Pathloss [dB [dB]] 16
5 MHz – MIMO 1x2 – 10 Mbps
0.0 56.0
10.0 -91.8
146.8
=a+b–c
for 16QAM 2/3 =g+h
=d–i–j–k+l+m–n
CUSTOMER CONFIDENTIAL
Design Objectives Coverage (III) – Radio Link Budget [Uplink] a
Max Transmit Power [dBm]
b
TX Antenna Gain [dBi]
0.0
c
Body Loss [dB]
0.0
d
EIRP [dBm]
24.0
e
eNode-B Noise Figure [dB]
10.0
f
Thermal Noise [dBm]
g
Received Noise Floor [dBm]
h
SINR [dB]
i
Receiver Sensitivity [dBm]
j
Interference Margin [dB]
2.0
k
Cable Loss [dB]
0.0
l
RX Antenna Gain [dBi]
m
RX/TX Diversity Gain
0.0
n
MHA Gain
2.0
Maximum Pathloss [dB [dB]] 17
24.0
-106.8 -96.8 6.0 -90.8
5 MHz – SISO 1x1 – 5 Mbps =1+2–3
= k (Boltzmann) x T (300K) x B (5MHz) =e+f for QPSK 2/3 =g+h
13.0
127.8
=d–i–j–k+l+m+n
CUSTOMER CONFIDENTIAL
Design Objectives Quality
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
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CUSTOMER CONFIDENTIAL
Design Objectives Capacity
Traffic maps represents Active 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 types Active 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 mixes So 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
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CUSTOMER CONFIDENTIAL
Pathloss Model RF Planning Tool
Basic
Purely Predictions
Interpolation and Drive Tests
Very vulnerable to database errors and prediction inaccuracy
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
Advanced
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CUSTOMER CONFIDENTIAL
Benchmarking of LTE Design Objectives Flow Diagram Pathloss
Project Build Sector
Service
User
System
Configuration
Monte Carlo Simulator
Neighbor List
Reports
Analysis Coverage SINR Data Rate Quality ...
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CUSTOMER CONFIDENTIAL
Benchmarking of LTE Design Objectives Monte 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.
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CUSTOMER CONFIDENTIAL
Benchmarking of LTE Design Objectives Reason for Failure
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CUSTOMER CONFIDENTIAL
Benchmarking of LTE Design Objectives Downlink Data Rate
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CUSTOMER CONFIDENTIAL
Site Selection and RF Optimization Definition of Network Planning Criteria
KPIs per clutter RSRP 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 KPIs Coverage: 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 component Monetary cost per RF change and sector Necessary to make sure that the proposed RF design meets the budgetary constraints
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CUSTOMER CONFIDENTIAL
Site Selection and RF Optimization Accomplishing KPI Objectives
The location of potential site comes from An existing network, e.g. UMTS. A “random” deployment over the area of study
KPIs fullfiled with just 60% of initial locations
Site selection minimum number of sites to meet target coverage, quality and capacity. 15 sites
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KPI performance from potential sites
KPI Objectives
CUSTOMER CONFIDENTIAL
KPI performance after site selection
9 sites
Site Selection and RF Optimization Selected Sites
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CUSTOMER CONFIDENTIAL
Site Selection and RF Optimization Optimizing Antenna Setting (I)
Operators have limited amount of resources, but at the same time they 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
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CUSTOMER CONFIDENTIAL
Site Selection and RF Optimization Optimizing Antenna Setting (II)
RSRQ Coverage - 81.87% to 85.11%
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CUSTOMER CONFIDENTIAL
Site Selection and RF Optimization Combined Solution
KPIs are fulfilled with 1 site less
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CUSTOMER CONFIDENTIAL
Other Functionalities Cell-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
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CUSTOMER CONFIDENTIAL
Summary Conclusions 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
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CUSTOMER CONFIDENTIAL
THANK YOU! Comments and Questions?
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CUSTOMER CONFIDENTIAL
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