As rapid growth in data usage continues, mobile service providers (MSPs) are making crucial choices concerning how to add capacity to meet demand and maintain performance. But until recently, they have had very few tools to help them answer two key questions when considering whether and how to use small cells:
- Where is the optimal location for each small cell?
- Will small cells be more cost effective than other expansion options, such as macro cell splitting or adding carriers?
Alcatel-Lucent has recently developed a new data-driven approach that uses Bell Labs algorithms to provide specific answers to these questions. Starting with an exhaustive, systematic analysis of network traffic, this approach can determine the most effective placement for each small cell, in terms of offload and performance. The end-to-end process includes calculating the specific offload potential for designated locations, while making sure that the placement of these small cells can be done in such a way to manage the interference with the macro cell and other small cells.
In addition, MSPs can compare the costs of using small cells for adding capacity with macro cell alternatives. Because the analysis is based on real usage data rather than high-level information such as cell-level performance management reports, it provides a more solid case for small cell deployment within the macro network — and it enables more realistic investment decisions.
Mapping key hotspots
In urban networks, data traffic is highly concentrated in hotspots, where small cells can play a very valuable role in offloading traffic. Although their range is shorter than that of a macro cell, small cells are better at handling dense traffic when properly located.
In fact, Bell Labs modeling has shown that a single small cell in an optimal location can potentially offload up to 55% of the traffic of a macro cell. Of course, these results depend on specific network conditions and cannot be replicated in every macro cell. But they clearly illustrate the importance of identifying the ideal placement for small cells within a macro network.
The first step in finding this location is to develop a “heat map,” as depicted in the example shown in Figure 1. This map systematically correlates locations and usage, showing the size and intensity of all hotspots within the coverage area of a macro cell. When traffic is offloaded from key hotspots, the overall capacity and user experience can be increased within the current spectrum.
Figure 1: Sample heat map
Ideally, a heat map should be based on detailed usage information that includes data call records for all active subscribers in the given cell site coverage area. It should use a large enough sample, for example, two weeks of data of active subscribers to provide confidence in the correct identification of hotspots. This data-driven approach to mapping provides a more realistic and accurate foundation for optimal small cell placement than a mapping based on high-level data.
Quantifying offload potential
Heat maps alone cannot indicate which small cell locations can offload the most traffic. Alcatel-Lucent has developed a method of offload analysis using Bell Labs algorithms, which quantifies the specific offload potential for designated small cell locations. These calculations take into consideration the capacity and footprint of different types of small cells — and avoid placements that would create interference with macro cells or other small cells.
The final offload report graphically illustrates the percentage of traffic that each small cell location could offload from specified hotspots, which have been identified on the heat map. With this detailed information, based on actual usage patterns, MSPs can take the guessing out of small cell placement. Multiple network design options can be evaluated, including macro cell expansion (for example, cell splitting or adding carriers) and small cell deployments, to determine which configurations will work best to meet current and anticipated traffic demand.
Case study: Gaining a detailed view of usage
A data-driven approach to small cell location allows MSPs to visualize hotspots more accurately than they can with currently available performance management tools. As a result, a Tier 1 MSP in North America made use of this new approach to gain a better idea of exactly where data usage was occurring in a particular service area.
The provider wanted this information to help guide a decision concerning the best way to increase capacity. In particular, the company already believed that spending for 20 small cells would provide the best payoff, but they wanted a realistic view of their options, based on actual usage data.
Therefore, Alcatel-Lucent engineers used a per-call trace on the wireless network to capture every call during a two-week period. Then, state-of-the-art tools were used to compute a geo-location estimate for each call recorded, which was correlated with subscriber data use. Call density maps were generated to highlight the hotspots, which showed that the area was a good candidate for small cells.
Systematically comparing costs
As MSPs choose how to add capacity, cost is always a crucial factor. To help identify the most cost-effective option, Bell Labs tools can use detailed usage data, previously collected for heat mapping, to compare the total cost of ownership (TCO) of different offload strategies. By leveraging real subscriber usage information, this financial analysis enables a comprehensive evaluation of options, which is not possible with other network planning tools.
Multiple scenarios can be examined to determine the best growth strategy. For example, the analysis might start with the question: How much capacity offload is needed to make a network operate better? Then, it would calculate the costs of deploying a specified number of small cells and compare that result with a macro cell upgrade designed to provide equivalent capacity. All key variables would be taken into consideration, including CAPEX, OPEX, backhaul expenses, network morphology, spectrum availability and expected growth. Using a multi-year traffic forecast, this network economic analysis can be performed to determine the number of small cells or macro cell upgrades needed in each year. The result is a multi-year TCO that can be used by the MSP to guide their decision-making process.
Figure 2 illustrates the results of financial modeling that compared the TCO of deploying with the costs of adding a second carrier to a macro cell. In this case, the total cost of ownership for small cells was found to grow at a much slower rate than the TCO for macro cells. The modeling for this scenario incorporated the following assumptions:
- Market population: 8 million
- Operator market share: 30%
- Data take rate: 40%, growth 20%
- Data usage: 500 MB/month, growth 10%
- Morphology: Dense Urban (DU) 20%, Medium Urban (MU) 50%, Suburban (SU) 30%
- Small cell coverage: DU 20%, MU 15%, SU 10%
Figure 2: Bell Labs modeling result – TCO sensitivity
Case study: Determining the most cost-effective strategy to meet demand
Anticipating continued growth in data traffic, a Tier 1 MSP in Europe wanted to take advantage of a data-driven approach to select the most cost-effective network upgrade strategy for a five-year plan. The process included development of a heat map, followed by determination of potential network designs that would meet the requirements of projected network growth.
The network upgrade options, which took into account the targeted hotspots, compared a “no small cells” option with a design that expanded the macro cell but added some small cells when the macro ran out of carriers. For capacity, the macro cell strategy required deploying new macro cells to meet anticipated growth.
The findings of this Bell Labs analysis indicated that the macro cell expansion would be financially favorable in the first few years. But it would turn negative when new macro cells were needed. As shown in Figure 3, the small cells deployment would be less costly in later years, where new macro cells were deployed to address carrier exhaustion. Thus, over a three-year planning horizon, small cells would give the MSP superior TCO, when compared to the macro option.
Figure 3: Three-year TCO comparison for macro and small cell upgrade
Addressing mobile data growth
Alcatel-Lucent has developed an end-to-end, cross-vendor process to assist MSPs in developing an optimal strategy to address ongoing mobile data growth, as illustrated in Figure 4.
Figure 4: Alcatel-Lucent small cells geo-location service methodology
Using a systematic, data-driven approach that leverages proprietary Bell Labs algorithms and tools, this process gives MSPs better ways to meet the challenges of rapidly growing data traffic. It includes locating hotspots with greater precision, determining the most cost-effective options for increasing capacity, quantifying the offload potential of specific small cell placements, and choosing locations for small cells where they can deliver the greatest offload without interference.
To contact the authors or request additional information, please send an e-mail to techzine.editor@alcatel-lucent.com.