Case Study - Reduced DAS Costs w/ Macro Reduction

Introduction: RF networks have evolved from tower-top and roof-top macro sites to a combination of macro, iDAS/oDAS (indoor/outdoor Distributed Antenna Systems), small cell and hetnets. The prime motivation for this network evolution is for the improvement in network quality demanded by subscribers. The propagation tools used for the initial design of these networks is typically inadequate in modelling and adapting to the evolving networks types deployed. The macro networks require re-engineering with a more intelligent approach to produce the network quality improvements. Evaluating the macro layer in conjunction with the individual iDAS, oDAS, HetNet solution is critical to minimizing capital build costs as well as ensure quality network performance once introduced to the network.

The extensive costs associated to DAS design and builds comes from the capacity and coverage requirements defined by each venue or area. Capacity may dictate the minimum sectors necessary, however the coverage required to exceed the existing network macro coverage by 6-10dB often increases the overall nodes installed. A quality design with reduced external macro cell coverage enables the engineers to derive a lower level threshold for DAS design which in-turn produces a precise technical design of the DAS / small cell network and provides an acceptable padding between DAS and macro cell coverage overlap. This overall approach results in optimal performance of the DAS networks resulting in optimized ingress and egress points, fewer drop calls, higher data throughput speeds and an improved customer experience.

A process to generate these results comes from the detailed network scan data collected for all contributing cells and technology layers. Simple point inspection of the active serving cell and its neighbors may identify some over serving cells, however it does not provide a quantitative reference for the type of change required or the impact outside of that point. A small upfront capital expenditure in properly designing the DAS with thorough detailed benchmark testing will result in long term cost savings. Although it is best to determine macro reduction prior to DAS design, post integration optimization of the macro network may also result in cost savings by maximizing the use of the DAS without the need for greater node density to overcome macro cell penetration.

Background: DAS designs are done by surveying the existing coverage to determine the minimum coverage level requirements to overcome the existing network. With existing network design often focused on covering the venue externally, existing coverage is typically quite high. Overcoming the macro cell coverage externally covering the venue requires extensive DAS nodes that makes DAS builds extremely expensive to build and operate. Reducing DAS build costs is vital for operators to expand how far capital expenditure money allocation will go across their networks. With this is mind the focus is how to reduce the required design levels to minimize the build costs of the DAS. Removing the external coverage to minimal levels without impacting the coverage around the venues is critical to these steps. Some example costs of associated with three different design levels are seen below.

A solid macro reduction approach saves costs on engineering time by eliminating trial and error approach of macro changes and knowing the required design thresholds upfront. Certain products enable engineering teams to view the impact of changes on measured data through change simulations, allowing engineer to arrive at the optimum macro cell configuration without any actual changes to the physical network. This approach saves the high costs of engineering time and labor involved in making these changes in the field as well as the wait time to record and analyze the impact of changes on network performance and end user experience. Most importantly, lower required design thresholds mean reduced equipment costs at deployment and upgrade and reduced maintenance costs over time.

Based on optimizing macro cells through downtilts, azimuth changes, and sometimes turning off sectors entirely, the DAS design and build costs may be reduced by greater than 30%. This mitigation of the surrounding macro cell sites also helps bring down the macro signal level thresholds for acceptable DAS design. It also significantly reduces costs of equipment and service work needed to overcome an otherwise high DAS signal threshold design & deployment. (* Various studies have shown to reduce up to 30% cost in equipment & labor for a venue of considerable size – a large convention center or a medium size football stadium.) Below is the example of equipment savings on designing an iDAS for three common coverage levels demonstrating equipment costs for each 10dB of lower design threshold required:

Figure 1: Common DAS Design Levels

Table 1: DAS Component Costing at Various Levels

Study: A complete macro reduction analysis was done to determine the impacts of optimizing the surrounding cells in an existing DAS venue. The most important aspect in design of Indoor DAS is ensuring the DAS signal is greater than the Macro site by at least 7-10 dB. This requirement is essential in ensuring the SINR requirements are met and also to ensure the traffic is offloaded to the DAS network.

The image below (Figure 2) shows a typical case of RF Coverage in a stadium environment, where in the initial macro network was designed to cover the stadium, the strong macro penetration leads to a number of issues:

• Macro Cells interfere with DAS coverage impacting SINR.
• Traffic imbalance between DAS and Macro cells.
• High cost for DAS build-out.

Figure 2: Data Collection Density

To overcome these negative consequences, RF Shaping analysis is undertaken to reduce the Macro cell coverage from the DAS venue. Classically, this RF Shaping exercise has been undertaken using propagation tools and/or trial and error based changes to the macro network. The RF propagation tools reliance on highly accurate propagation models and wide standard deviations of 8-10 db making them unsuitable to accurately predict the changes required in macro cells. Engineers have typically resorted to trial and error optimization methods for reducing the coverage by changing some basic cell configuration parameters such as tilts and power. This trial and error method makes the optimization process tedious and inaccurate.

The RF Shaping exercise of surrounding macro cells needs to achieve the following objectives:

• Accurate simulation of network changes for macro coverage reduction
• Ensure only acceptable on-street coverage loss.
• Identify areas of poor DAS to Macro isolation.
• Recommend changes based on In Building design thresholds.
• Loss of coverage and replacement coverage.
• Ability to simulate changes to the following cell parameters: Antenna Tilt, TxPower, Azimuths, Antenna Models, & Disabling Cell Entirely

OptPCS ICE is developed with the objective of eliminating the ambiguity of trial and error and lack of accuracy of propagation models to create an accurate way to simulate the changes to macro network based on network scan data. ICE (Intelligent Cell Engineering) is a module within OptPCS designed for accurate simulations of cell parameters using scan data. ICE is designed with the ability to reverse engineer the cell parameters in order to simulate the cell parameters and evaluate the impact of those changes. Simulations in the software are run on Individual cell level and composite network level to study the complete impact of the changes. Individual Cell Simulations are run to show the before/after impact of the simulation on the coverage In- Building and On-Street Level. ICE utilizes the following:

• Interference Matrix and Pathloss Database (IMPL) – 3D Database of all cell interactions to every binned outdoor and indoor scan data point.
• Terrain Database: Digital Terrain database of terrain properties i.e. Elevations, Hills, and Natural Obstacles.
• Antenna Database: Database of all Antenna with their properties i.e. Propagation patterns, gain, Front to back Ratio, Bands etc.
• Site Database (S-INFO) - Site configuration i.e. height, Rad centre, Power, Tilt, Azimuth, frequencies, technologies, parameters, etc.

Figure 3: Individual Cell Simulations

The impact of individual cell change simulations are examined from the point of view of the change in coverage bins for Indoor as well as outdoor environment. The objective of the cell simulation is to ensure that we can pull the macro coverage outside the stadium without impacting the outdoor macro coverage significantly. In areas where the coverage is reduced it is ensured that there is enough replacement coverage from other sites. This analysis is part of every Individual cell simulation.

Simulations at the network level provide a holistic view of all the individual simulation results providing a detailed view of the impact of changes made for both outdoor and indoor environment.

Figure 4: Current and Post Indoor Simulations RSRP (dBm)

In networks where the DAS is on air, the analysis on ICE is undertaken to pinpoint the areas where the DAS is not stronger than macro by at least 7 dbm. These areas are carefully analysed and the macro changes are made to ensure that the DAS is made stronger than Macro.

Figure 5: Current and Post Outdoor Simulations RSRP (dBm)

Figure 6: Current/Post DAS vs Macro Delta (dB)

Shown above (Figure 6), the stadium currently has poor DAS isolation with macro cells covering in major portions of the stadium leading to performance issues. By conducting reduction utilizing OptPCS-iCE we can ensure that the required changes will meet the objectives to make sure that the DAS is greater than Macro by at least 7dB.

Findings:

The macro reduction exercise is undertaken to create a balance between maintaining outdoor coverage and pulling coverage out from Indoor environment to ensure the Macro sites don’t cause performance issues on DAS. The case study took an example of the stadium with strong macro penetration. The reduction in macro coverage by 10 dBm leads to lower design thresholds. This lower requirement for design threshold helps bring huge cost benefits. Using simulation software, the process of macro reduction for DAS environment is undertaken with an intelligent approach using real world scan data and the results of the simulations are accurate within 3 dBm of the simulation. The Macro reduction analysis conducted using ICE identified the areas with poor DAS to Macro Isolation, these areas are fixed to ensure no performance issues are seen in the venue.

Table 2: DAS vs Macro Post Optimization

Conclusion: Quality macro cell analysis performed on a venue prior to final design of the DAS enables the engineers to derive a new macro level threshold for DAS design which helps in a precise technical design of the DAS / small cell network and provides for an acceptable padding between DAS & macro signal. This overall approach results in optimum performance of DAS networks, optimized ingress & egress points, fewer drop calls, higher data speeds and great customer experience. This quality of reduction comes from detailed scan data collection of all contributing cells. Simple point inspection of the active serving cell and its neighbors may identify some over serving cells, however it does not provide a quantitative reference for the type of change required or the impact outside of that point.

There are numerous methods to perform macro cell reduction at DAS venues. The best methods will account for both removing the macro cells from the focal area of the DAS as well as maintain coverage for it's remaining footprint requirements. Additionally, the recommendations should be accurate and complete to allow first time implementation and avoid costly time delays. This balance typically comes from detailed data collection both inside and around the venue simulating the impact of macro configuration changes. Tools such as ACPs with individually tuned models from the data or simulation products such as OpPCS iCE will give the best modeled results without continual testing and re-walking on each attempted setting. Having a simulation or individual pathloss tool based on the detailed measured field data compared against any conventional prediction based tool with acceptable standard deviation error of 7-10 dB is critical to successful alternative solution designs.

Proper macro cell reduction brings numerous values in terms of engineering quality and cost savings for Distributed Antenna Systems (DAS) design, deployment and performance. Engineering teams need to focus on macro cells interference mitigation to any iDAS, oDAS or small cells network during the initial design. Macro cells often were designed to provide the coverage at the venues with new DAS. In order for the new solution to effectively offload traffic and provide the network quality it needs to be on average 7-10dB stronger. This means if a venue is covered at -75dBm from Macro cells, a capacity solution would need to be -65dBm in design to overcome it. Reducing this macro coverage, reduces the required design thresholds.

A complete macro reduction process with quality data collection and software analysis allows for:

• Reduced DAS build out costs.
• Accurate simulations and estimation of coverage after cell changes without iterations.
• DAS to Macro delta analysis.
• Works on various DAS environments for outdoor and indoor DAS