1 1. LTE network Planning and Analysis LTE coverage prediction tool allows prediction of RSRP, RSRQ, RS-SINR, coverage probability and average data rate rasters. Inter-cell interference and MIMO antenna performance are included into coverage predictions. Multiple MIMO configurations are supported including transmitter and receiver diversity, spatial multiplexing and beamforming. Fractional frequency reuse can be used to minimize inter-cell interference by assigning different subbands to neighboring sectors. Monte Carlo traffic simulations allow detailed user traffic modeling by statistical analysis of mobile user distribution snapshots. 1.1. LTE Coverage Prediction For LTE networks the following coverage rasters can be calculated: RSRP (Reference Signal Received Power) is defined as the linear average over the power contributions of the resource elements that carry cell-specific reference signals within the considered measurement frequency bandwidth. It is analogous to constant power, data traffic independent pilot signal in UMTS/CDMA type networks. RSRQ (Reference Signal Received Quality) is defined as the ratio N×RSRP/(E-UTRA carrier RSSI), where N is the number of RB’s of the E-UTRA carrier RSSI measurement bandwidth. Best server rasters, showing true cell dimensions indicating areas covered by the strongest signal from each of the selected sectors. RS-SINR is equal to the ratio of RSRP and RS interference from adjacent BS plus noise powers. DL data rate layer shows average data throughput per user available at each location on the map considering local propagation conditions and corresponding adaptive modulation level. Coverage probability coverage map shows percentage of time over which signal strength is higher than the threshold value calculated based on multipath fading statistics.
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1. LTE network Planning and Analysis
LTE coverage prediction tool allows prediction of RSRP, RSRQ, RS-SINR, coverage probability and average data
rate rasters. Inter-cell interference and MIMO antenna performance are included into coverage predictions.
Multiple MIMO configurations are supported including transmitter and receiver diversity, spatial multiplexing
and beamforming. Fractional frequency reuse can be used to minimize inter-cell interference by assigning
different subbands to neighboring sectors. Monte Carlo traffic simulations allow detailed user traffic modeling
by statistical analysis of mobile user distribution snapshots.
1.1. LTE Coverage Prediction
For LTE networks the following coverage rasters can be calculated:
RSRP (Reference Signal Received Power) is defined as the linear average over the power contributions
of the resource elements that carry cell-specific reference signals within the considered measurement
frequency bandwidth. It is analogous to constant power, data traffic independent pilot signal in
UMTS/CDMA type networks.
RSRQ (Reference Signal Received Quality) is defined as the ratio N×RSRP/(E-UTRA carrier RSSI), where N
is the number of RB’s of the E-UTRA carrier RSSI measurement bandwidth.
Best server rasters, showing true cell dimensions indicating areas covered by the strongest signal from
each of the selected sectors.
RS-SINR is equal to the ratio of RSRP and RS interference from adjacent BS plus noise powers.
DL data rate layer shows average data throughput per user available at each location on the map
considering local propagation conditions and corresponding adaptive modulation level.
Coverage probability coverage map shows percentage of time over which signal strength is higher than
the threshold value calculated based on multipath fading statistics.
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Figure 1. Reference signal received power coverage prediction
Figure 2. Signal to interference plus noise ratio of reference signal
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Figure 3. Average data rate in downlink map including effects of MIMO and interference
1.2. MIMO Antenna Performance
Multiple antenna configurations can be used to increase signal coverage, traffic throughput and reduce
interference. Transmitter, receiver diversity and beamforming configurations are supported. The prediction of
MIMO equipped sector configurations results in coverage gain, throughput increase factor or SINR gain.
Figure 4. MIMO performance parameters
1.3. LTE Monte Carlo Traffic Simulations
Statistical Monte Carlo traffic simulations are used for predicting cell capacity based on mobile user distribution
snapshots. LTE capacity simulation takes into account MIMO antenna and OFDMA modulation gains.
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Proportionally fair scheduling takes advantage of high SNR regions to maximize cell capacity. Simulation results
can be represented via graphs or coverage maps.
Figure 5. Results of Monte Carlo traffic simulation tool – dependence of the average cell throughput on the number of users per cell
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2. Network Planning Process Using Cellular Expert
LTE network planning and optimization tasks supported by Cellular Expert are part of integrated wireless
network planning process including other types of networks. Network design and analysis procedures takes into
account real terrain and obstacles data, network configuration and radio equipment data, and provides tools for
optimal network design to achieve best coverage and throughput results. The planning steps are divided into
the following tasks:
Project data preparation including setting up elevation and obstacle layers used for propagation
modeling. At this stage radio equipment data should be collected and imported into database, including
antenna radiation patterns, radio models and feeders. Cellular Expert workspace settings should be
adjusted setting database source and prediction results locations.
Network design and analysis consists from broad range of tasks available for LTE related network
planning and optimization. These include initial site location planning using direct line-of-sight visibility
analysis and quick path profiling, best site location to serve fixed customers or hot-spots, sector tilt and
azimuth optimization, propagation modeling and coverage prediction. After coverage predictions, traffic
capacity modeling can be performed using Monte Carlo simulations.
Backhaul planning allows connecting base station via microwave links with full point-to-point radio link
analysis: propagation loss prediction, antenna height optimization, reflection analysis, link power budget
analysis, interference prediction, multipath and rain fading performance. In addition, frequency
allocations can be optimized to avoid interference using automatic frequency planning tool.
3D visualization capabilities provide easy way for exporting network design data and coverage
prediction results into three-dimensional environment for more intuitive analysis.
Data sharing is possible via web interface allowing remote user to connect via web browser and preview
network design, coverage prediction results and to make adjustments to network parameters. Also
network configuration data can be exchanged via XML or Excel data files between multiple users or
organizations.
Reporting and documentation provides means for printable reports generation which contain network
design parameters, base station and radio link layouts, and path profile analysis results. The reports can
be exported into multiple standard document formats for documentation purposes.
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3D Visualization
Data Sharing
Web Viewer
Prediction Maps
File Exchange
Reporting and Documentation
Map Layout Reports
Path Profile Reports
Microwave Link Reports
LTE Network Design and
Analysis
Line-of-Sight Visibility
Fixed Customers
Coverage Prediction
Sector Tilting
Traffic Simulation
Data Preparation
GIS Data
Radio Equipment
Workspace
Backhaul Planning
Path Profiling
Microwave Link Design
Radio Link Performance
Prediction
Figure 6. Wireless Network Design and Analysis Process using Cellular Expert