Macro Reduction for DAS & Small Cell Savings

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 would need to be -65dBm in design to overcome it. Reducing this macro coverage, reduces the required design thresholds.

Cost Savings: 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 enables engineering teams to view the impact of changes on measured data through simulation which helps engineer to arrive at the optimum macro cell configuration without any actual changes to the physical network. It saves high costs of engineering time and labor involved in making these changes in the field and 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 lower maintenance costs in time.

This mitigation of the surrounding macro cell sites also helps bring down the macro signal level thresholds for acceptable DAS design and reduce significant costs of equipment and labor 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.

Example Equipment List:

Design Material Make Model -85dBm (qty) -75dBm (qty) -65dBm (qty)
DAS Remotes CommScope ION-B Remotes 4 8 19
Antenna CommScope CellMax-O-CPUSEi 16 30 72
Cable (m) CommScope AL4RPV50 776 984 1,425
Connector CommScope L4TNM-PS 32 58 144
Cable CommScope F4-PNMNM-1M 4 8 19
Cable CommScope F4-PNMNM-1M 4 8 19
Splitter CommScope S-4-CPUSE-L-Ni 4 8 19
Estimated Cost: $78,500 $143,000 $359,000

Engineering Quality: 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. A few extra dollars spent upfront getting a quality detailed benchmark will have long term cost savings.

There are numerous ways to do macro reduction. 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. This balance typically comes from detailed data collection inside the venue and out and simulating these 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. Simulation or individual pathloss tools based on the detailed measured field data compared against any conventional planning tool based on typical propagation modeling with acceptable standard deviation error of 8-10 dB is critical to successful alternative solution designs.

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