Hundreds Of Venues Worldwide Require State of the Art Wireless Networks
When you think of stadiums, you envision a huge venue with a central field or track surrounded by tiered seating. These iconic structures host not only thrilling events but also present unique challenges, particularly in terms of network coverage.
The world’s largest stadium, located in Pyongyang, North Korea, boasts an astounding capacity of 150,000 spectators. Following closely behind is Kolkata, India, with a stadium that can hold 120,000 fans. Surprisingly, only a few stadiums worldwide can accommodate over 100,000 visitors.
As of 2014, there were 934 stadiums worldwide with a seating capacity of 30,000 or more. These were distributed as follows: 228 in North America, 129 in Central and South America, 243 in Europe, 98 in the Middle East and Africa, and 236 in the Asia-Pacific region. The United States alone boasted 217 stadiums with over 30,000 seats, with the vast majority dedicated to American Football.
Challenge | Poor Network Connectivity and Call Blocking Throughout Stadiums and Their Transit Areas
While stadiums come in various shapes and sizes, certain design and deployment considerations are consistent.
Let’s look closer at a case study venue with a 60,000-seat capacity and five distinct seating levels. The first level, closest to the stadium entrance, houses retail shops and concession stands for the general public. This level also includes conference rooms, though they are not accessible to the public. One level below, at ground level, you’ll find the press rooms and team dressing rooms.
Despite the grandeur of these structures, one common issue is network coverage. While the seating areas typically receive fair to good coverage from surrounding macro sites, the story is quite different below ground, in back offices, conference rooms, and concession areas. Macro sites often report high call blocking during events, sometimes peaking at a staggering 60% during busy hours.
The network challenge extends beyond the stadium walls. It also affects the areas where spectators gather before and after events, including parking lots, train stations, pedestrian walkways, and more.
These transit areas often face similar call-blocking issues.
Solution | Customized Distributed Antenna Systems To Extend Signals and Increase Network Availability
To address these network challenges, stadium operators and telecommunication providers must ensure coverage and capacity within the stadium itself and in the surrounding transit areas. The network should seamlessly support high traffic volumes during events and provide reliable service before and after them.
A Distributed Antenna System (DAS) should be implemented, extending signals throughout the stadium and surrounding areas. The DAS signal must outshine the residual macro signal, ensuring that subscribers seamlessly connect to the stadium network rather than the surrounding macro network.
Design Requirements
Building the perfect stadium network demands meticulous planning and execution. Meeting these design requirements ensures that fans enjoy seamless connectivity during events, from cheering on their favorite team to sharing thrilling moments on social media.
The design requirements for a 60,000-seat venue are as follows:
RF Coverage
The stadium network signal must dominate throughout the venue, surpassing the macro signal by 5 to 7 dB, including nearby transit areas.
Capacity
The network should accommodate a wide range of services, from voice calls to high-definition video, considering the unique challenges posed by the stadium environment, such as crowd noise and dynamic usage patterns.
Handoff Management
Efficient handoff management is crucial to prevent call blocking, particularly in transit zones outside the stadium. Seamless transitions between the macro and stadium networks are essential for uninterrupted connectivity.
Interference Management
Addressing interference from various sources, including non-serving sectors within the stadium’s Distributed Antenna System (DAS) and external macro network signals, is vital for network capacity and performance.
Best Practices
When orchestrating the blueprint for a network, adhering to specific principles becomes paramount in achieving the most efficient design. These principles encompass the following:
Site Survey
The initial on-site inspection systematically documents comprehensive data concerning the venue’s physical infrastructure, architectural nuances, and various structural aspects. A wealth of information is collected in diverse formats, including photographs, videos, measurements taken with data acquisition tools, voice recordings, and textual annotations. Potential antenna placement, cable routing, and equipment installation sites are also meticulously scouted.
Within this survey, it is essential to record the prevailing macro radio coverage at the venue for all wireless carriers slated to be integrated into the network across all relevant frequency bands. This phase assumes pivotal significance, as the stadium’s network must effectively supersede the lingering macro coverage by a comfortable margin. Failure to do so could result in an undesirable scenario where spectators’ User Equipment (UE) remains connected to the macro network while inside the venue, contrary to the primary objective of offloading the macro networks.
In the course of the site survey, in addition to amassing RF data, the engineer is tasked with pinpointing potential locations for antenna installation, identifying a suitably spacious room for housing the in-building network’s headend, and establishing viable cable routes connecting the headend to the antennas.
Directly annotating this wealth of information onto a floor plan serves a dual purpose: it expedites information sharing with other departments and stakeholders while streamlining the data interpretation process. Furthermore, it is essential to identify multiple prospective antenna sites to provide flexibility during the subsequent detailed RF coverage design phase, enabling the consideration of various alternatives for controlling radio signals and enhancing capacity.
3D Modeling
Stadiums are complex architectural structures with diverse radio frequency propagation conditions. Among these conditions, the seating bowl stands out as a prominent one. It is conceptualized as an inclined surface to consider the varying elevations of seating rows. In this area, user equipment (UE) enjoys a direct Line of Sight (LOS) to the antennas above the seating sections.
The design must encompass capacity hotspots beyond the seating bowl area. These encompass spaces like corporate suites, media boxes, retail outlets, and concession stands, all of which can experience heightened capacity demands. Additionally, it’s crucial to account for capacity hotspots that are restricted to specific groups, like conference rooms, press areas, and team locker rooms. The diagram below illustrates various examples of these capacity hotspots for reference.
These areas are typically physically separated from the seating bowl, necessitating the installation of dedicated antennas to ensure adequate coverage. RF propagation characteristics within stadium hotspots exhibit considerable variation. Within the bowl, the Distributed Antenna System (DAS) signals have a clear Line of Sight (LOS) with user equipment (UE). Beneath the bowl, specifically in the retail area, LOS conditions are prevalent, but concrete walls introduce multiple reflected signals. The wall density in the back-of-the-house regions housing conference rooms and locker rooms is substantially higher, resulting in significant signal diffraction and non-line-of-sight (NLOS) propagation.
Given the distinct propagation characteristics in hotspots compared to the seating area, it becomes imperative to accurately construct 3D models for these hotspots as well.
The process of creating a 3D model of a venue varies in duration, taking approximately five hours for smaller venues and up to 20 hours for larger, more intricate venues. The availability of electronic CAD drawings, rather than traditional paper blueprints, can also impact the time required for completing the 3D model. Frequently, we design systems for buildings still under construction, making it essential to work exclusively with 3D models as we may not have physical access to the venue. Thorough venue modeling holds significance for propagation analysis and accurate Bill of Materials estimates, including the quantities of coaxial cable or fiber needed.
Sectorization
Sectorization serves a dual purpose within radio network design. Firstly, it significantly enhances network capacity by providing each sector with dedicated channel cards capable of handling both voice and data traffic. Sectors are assigned specific coverage areas and subscriber quotas, with precise parameters like the number of channels per sector, data rates, call and data connection types, and durations considered in capacity planning.
Secondly, sectorization aims to minimize signal interference by restricting sector coverage, thereby reducing interference from non-serving sectors. This optimization positively impacts capacity, the Signal-to-Interference-plus-Noise Ratio (SINR), and the maximum achievable data rate (MADR). In Line of Sight (LOS) areas like the seating bowl, sector overlap reduction is achieved by deploying highly directional antennas.
There are several common sectorization approaches. Horizontal (ring) or vertical (wedge) sectorization is most commonly used when the number of sectors is limited. The diagram below illustrates examples of such sectorization schemes. The advantage of these methods is that they minimize the need for extensive User Equipment (UE) handovers when spectators move horizontally or vertically.
However, a hybrid ring-and-wedge sectorization becomes the preferred choice if a substantial number of sectors are needed.
Macro Coverage Management
In the early stages of macro network deployments, Wireless Service Providers (WSPs) recognized the revenue potential in venues with high subscriber densities, such as stadiums. Initially, they aimed to provide excellent stadium coverage (“five-bar” signal) by directing sectors of nearby macro sites toward the venue. However, as networks evolved to prioritize data traffic, congestion became a primary concern, particularly in venues like stadiums.
Today, many stadiums have solid coverage within the seating bowl, but there’s a growing need for a dedicated stadium network to manage the traffic effectively and prevent neighboring cell sites from becoming overloaded during stadium events.
A common strategy when designing stadium network coverage is to ensure that the Distributed Antenna System (DAS) signal is at least 5 to 7 dB stronger than the residual macro signal. However, achieving this goal can be challenging if the residual macro signal is already strong, as it may require a substantial number of antennas, making DAS deployment costly. The most efficient way to reduce the impact of the residual macro coverage is by down-tilting antennas on nearby sectors that are directed towards the venue.
In the diagram below, the red line represents the RF signal path with the initial antenna down-tilt. The signal diffracts off the stadium roof, resulting in minimal attenuation and providing a robust signal within the bowl. The signal path penetrates the concrete wall by further down-tilting the sector, as shown in green. This is often preferable, as the concrete wall significantly attenuates the signal before it reaches the seating bowl, reducing interference and improving network performance in the stadium.
Passive Intermodulation (PIM) Management
Neutral-host networks with high transmit power can be vulnerable to Passive Intermodulation (PIM) noise generation, which, when at sufficiently high levels, can lead to several adverse effects, such as reduced coverage, slower network performance, dropped calls, and diminished battery life. LTE networks, in particular, are prone to PIM noise issues because the Signal-to-Interference-plus-Noise Ratio (SINR) is referenced to Physical Resource Blocks (PRBs), which are 180 kHz wide. The thermal noise referenced to this 180 kHz width is typically -121 dBm, and for proper LTE network functioning, the maximum PIM noise should be -127 dBm or lower.
To effectively manage and control PIM noise, it’s essential to take specific steps during the network design phase, as outlined below:
- To achieve the required PIM noise levels, combiners near the power amplifier should meet a PIM specification of -162 dBc @ 2×35 dBm.
- Avoid using braided coaxial cables and N-type connectors, as they are known sources of PIM noise.
- Instead, opt for silver-plated 7/16 DIN connectors with a low PIM rating (165 dBc), minimizing noise generation.
- When selecting antenna locations, ensure they are situated away from metal objects, as metal in close proximity to antennas can generate PIM noise.
- Never use equipment for which the manufacturer does not specify a PIM rating, as this can lead to unpredictable PIM noise issues.
- Before installation, perform on-site PIM testing using an antenna mounted on a pole to proactively identify and address any PIM noise concerns.
By following these measures during the design and implementation of the network, you can effectively mitigate the impact of PIM noise and maintain optimal network performance.
Detailed RF Design
Capacity Sizing
To properly size the stadium network, it’s crucial to determine the number of sectors required to meet each carrier’s capacity demands. The number of sectors per carrier depends on several factors, including the stadium’s seating capacity, the carrier’s subscriber penetration rate (the percentage of the carrier’s subscribers compared to the general population), and the carrier’s mobile traffic profile.
In this iBwave case study, the stadium has 60,000 seats, and the stadium network needs to accommodate three Wireless Service Providers (WSPs), public safety, stadium operations network, and Wi-Fi.
Here are the characteristics of the three WSPs:
WSP A
- Cellular band (850 MHz), 2 UMTS channels
- AWS band (2100 MHz), 2 UMTS channels
- 700 MHz band (700 MHz), 10 MHz LTE-FDD channel
- 40% subscriber penetration rate (24,000 subscribers)
- 75% LTE subscribers (18,000)
- 25% HSPA subscribers (6,000)
- Voice on 3G network
WSP B
- PCS band (1900 MHz), 2 UMTS channels
- 2.5 GHz band, 10 MHz LTE-TDD channel
- 10% subscriber penetration rate (6,000)
- 50% LTE (3,000)
- 50% HSPA (3,000)
- Voice on 3G network
WSP C
- AWS band (1900 MHz), 2 UMTS channels
- PCS band, 5 MHz LTE-FDD channel
- 20% subscriber penetration rate (12,000)
- 75% LTE subscribers (9,000)
- 25% UMTS subscribers (3,000)
- Voice on 3G network
To understand the traffic distribution per user at the stadium, Table 1 provides details for each service type, including the duration of the network connection during busy hour (expressed in milliErlangs, mE) per subscriber and the fixed data rate in kbps. It’s important to note that a subscriber may use multiple service types during the busy hour.
- Video Conferencing: 5 mE per subscriber, shorter due to crowd noise.
- Video Streaming: 1 mE per subscriber (often banned due to high bandwidth requirements).
- Internet Browsing and Data Downloading: Most traffic at the venue falls into this category.
- Email: Some usage.
Voice traffic is carried over the WCDMA (R99) protocol, while data is carried over HSPA and LTE protocols. When defining the subscriber profile for R99, it’s considered that data traffic switches to R99 only if both HSPA and LTE are unavailable. Consequently, R99 data call durations are very short.
These considerations are essential for accurately sizing and optimizing the stadium network to meet the capacity requirements of the carriers and provide a seamless user experience during events.
The calculation of Signal-to-Interference-plus-Noise Ratio (SINR) coverage in the seating area for HSPA and LTE involves breaking down SINR into intervals based on the achievable modulation scheme within each interval.
In a region where the LTE Physical Downlink Shared Channel (PDSCH) SINR is 20 dB or higher, it is possible to use 64-QAM modulation with a coding rate of R=0.93, resulting in a spectral efficiency of 5.5 bit/s/Hz. When SINR falls between 15 and 20 dB, the spectral efficiency is 3.9 bit/s/Hz. For SINR ranging from 9 to 15 dB, the efficiency is 2.4 bit/s/Hz, and so on.
This breakdown allows for a more detailed analysis of network performance and capacity planning, as it accounts for variations in signal quality and modulation schemes, ensuring that the network can deliver optimal data rates under different conditions.
Understanding the relationship between Signal-to-Interference-plus-Noise Ratio (SINR), modulation schemes, and spectral efficiency is vital for network planning and resource allocation. This information can be obtained from research papers or directly from technology vendors. With this knowledge, it becomes possible to calculate the number of resources required to support each service type outlined in Tables 1 and 2.
These “resources” vary according to the specific technology being used. For instance, in LTE, resources are typically represented by Physical Resource Blocks (PRBs), while in UMTS, resources are HSPA orthogonal codes, and so on. Since spectral efficiency is dependent on SINR, the number of resources needed to support a particular service type within each SINR zone can also fluctuate.
For example, when SINR is high, a single PRB may suffice to support an email service. However, when SINR is low, more than one PRB may be required to maintain the quality of service for the same email application. This adaptive allocation of resources based on SINR helps optimize network performance and capacity, ensuring that each service type receives the necessary resources to function effectively under varying conditions.
Data Capacity Sizing Example
The process of dimensioning LTE capacity for the stadium network involves several steps, a series of calculations, and iterative adjustments to ensure that the LTE network can support the expected traffic and provide a satisfactory user experience within the stadium seating area.
SINR Coverage Map
First, a downlink LTE SINR coverage map is calculated. This map helps determine the SINR distribution across the stadium seating area. This information is essential for capacity planning.
SINR Ranges
The SINR coverage map is divided into several SINR ranges. Four SINR ranges are defined in your example based on the LTE SINR values.
Subscriber Distribution
Assuming a uniform distribution of spectators, the percentage of LTE users within each SINR range is calculated based on the SINR coverage percentages for each range. This step helps estimate the number of LTE users in each SINR category.
Subscriber Count
The total number of LTE and HSPA subscribers for a given operator (in this case, operator A) is divided among the 24 sectors in the stadium. This calculation results in the number of LTE and HSPA subscribers per sector.
Busy-Hour Traffic Calculation
Using the number of subscribers in each SINR range and the busy-hour traffic per subscriber (from Table 1), you calculate the HSPA and LTE busy-hour traffic in Erlangs for each service type. This step helps estimate the network load for each sector.
Resource Distribution
Next, you determine the number of resources (e.g., PRBs for LTE) needed to support the service types across the SINR ranges. This distribution takes into account the spectral efficiency values associated with each SINR range.
Blocking Probability
With the total number of HSPA and LTE resources in a sector, you calculate the blocking probability for each service type. Blocking probability represents the percentage of network connection attempts denied due to insufficient resources. This step is based on the ITU-R recommendation.
Carried Busy-Hour Traffic
Finally, you calculate the carried busy-hour traffic based on the offered traffic and the blocking rate for each service type. This provides an estimate of the actual traffic that the network can handle, considering the blocking rates.
Iterative Process
If the calculated blocking rates are not acceptable, adjustments can be made, such as increasing the number of sectors to reduce the number of subscribers per sector. The SINR map may need to be recalculated, and capacity calculations should be repeated. This iterative process continues until acceptable blocking rates are achieved.
Voice Capacity Sizing
Voice capacity planning for the stadium network is conducted through the WCDMA portion of the UMTS signal. This process ensures that voice capacity is adequately planned to meet the demands of subscribers across different signal quality levels in the stadium, with a focus on optimizing call-blocking rates to maintain an acceptable level of service.
Eb/N0 Coverage Calculation
Eb/N0 (the ratio of energy per bit to noise power spectral density) coverage is determined. This information is used to understand the signal quality across the stadium seating area.
Eb/N0 Ranges
The Eb/N0 coverage is divided into four different Eb/N0 ranges. Each range corresponds to specific service types that can be used in that particular signal quality range.
Subscriber Distribution
Assuming a uniform distribution of subscribers, the percentage of subscribers connecting to a service within a particular Eb/N0 range is the same as the percentage of coverage within that range. This helps estimate the number of subscribers in each Eb/N0 category.
User Distribution and R99 Traffic
The resulting user distribution is calculated by Eb/N0 range and R99 (Release ’99) traffic (in Erlangs). This step provides insight into the user distribution and traffic load across different signal quality levels.
OVSF Code Allocation
Only OVSF (Orthogonal Variable Spreading Factor) codes with spreading factors up to SF128 are used for the service types mentioned in the table below. The required number of OVSF codes per service type and Eb/N0 range is determined.
Blocking Rate Calculation
Call blocking rates are calculated based on the ITU-R recommendation, and the results are shown in Table 10. These blocking rates represent the percentage of attempted voice calls that are denied due to insufficient network resources.
Acceptable Blocking Rate
In this analysis, it’s found that the R99 voice blocking rate is 1.6% for a sector with 1,000 subscribers throughout the stadium seating area. This rate is acceptable for most macro UMTS networks, which typically target a busy-hour call-blocking rate between 1% and 2%.
RF Design Coverage
For the RF signal to dominate the venue, it should be slightly stronger than the residual signal originating from nearby macro cell sites. Typically, the residual macro signal is already quite strong in open-air stadiums. Your example assumes that the macro LTE Reference Signal receive power (RSRP) falls between -80 and -85 dBm across the seating area. By deploying highly directional high-gain antennas, it’s possible to achieve an RSRP of -75 dBm or even higher over 90% of the seating area.
The choice of modulation scheme in LTE networks is closely linked to the Physical Downlink Shared Channel (PDSCH) SINR. High SINR values enable the use of high-order modulation schemes like 64-QAM, resulting in high spectral efficiency and a high maximum achievable data rate (MADR) within the network.
However, deploying a large number of sectors in the stadium network can lead to numerous sector overlaps. These overlaps may introduce interference and potentially lower SINR values.
About iBWave
iBwave develops solutions to help wireless operators, system integrators, and equipment manufacturers, essentially anyone who has a stake in the network, bring strong, reliable voice and data wireless communications indoors profitably.
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