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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