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Improving carrier ROI through geolocalized network data analysis

2015.05.01 By Yang Li and Liu Junli


Comprehensive assessment and optimization analysis using Huawei's pioneering 6D business model and geolocalized network/service data can help carriers accurately identify hotspots, guarantee coverage quality, and maximize ROI.

According to a Visual Networking Index (VNI) report, mobile data traffic has a CAGR of 61% and will continue growing at this rate until at least 2018, reaching 15.9EB per month by that time, 96% of which will come from smart devices. The growth of mobile services presents an enormous challenge for carrier networks. HetNets are becoming mainstream, and the large-scale application of small-cell base stations has made network architecture even more complex. With the diverse and varying number of factors, such as macro- and micro-coordination and multi-standard co-antennas, in the network environment, coverage, interference, and capacity problems are becoming increasingly prominent, and pressure from customers for network assurance is increasing. Wireless network planning and optimization face a variety of new challenges.

Challenges to wireless planning & optimization

The distribution of data service traffic is much less balanced compared with traditional voice. Statistics show that 20% of sites carry 80% of network traffic. Data traffic at a few of the hottest sites can reach several dozen times that of an average site, and in some traffic-heavy areas, such as CBDs, schools, and malls, weak coverage, high interference and network anomalies still occur, and densely populated urban areas are often additionally marked by a scarcity of sites and spectrum resources. So, how can sites be correctly positioned? How can these heavy-traffic areas be effectively discovered and identified? How can macro/micro site interference be reduced? How can the potential of a network be exploited and ROI maximized, while still meeting the goals and needs of different areas and services? These are all key challenges facing carriers in their network planning.

Secondly, although LTE proliferation, increased site clustering, multi-network coordination, and multi-standard co-antennas represent the future for HetNets, this will also create great challenges for network optimization. Traditionally, network optimization primarily relied on standard measures such as drive tests and statistical analysis based on network and service data (such as traffic statistics, call records, probe statistics, etc.). Among these, drive tests are not only expensive and complicated, but they’re marginally effective and limited in the amount of data they can test and analyze on a sustained basis. In addition, analytical granularity (for dimensions/factors including region, RNC/BSC, site, cell/carrier frequency, service, users, etc.) in the statistical analysis of network and service data greatly affects problem resolution due to a lack of site-related information relating to localized problems (overlapping coverage, pilot pollution, connection failures, dropped calls, etc.). Indeed, when problems do occur, such as network failures or major complaints, frequent drive-tests are needed to simulate these anomalies. Lowering the dependency on drive tests, for example, through simulated drive testing or geolocation to accurately locate network faults to a certain grid, and then analyze the faults with network and service data, will be key to improving carriers' network optimization capabilities.

At present, carriers such as DT, Vodafone, Telefonica, and Telenor are beginning to call loudly for the use of geo-location, and are prioritizing geolocalized analysis in their daily O&M work.

6D modeling: Accurate site planning, effective investment

Huawei was the first in the industry to propose the use of a 6D evaluation model. This involves using the Assisted Global Positioning System (AGPS) to accurately display network traffic location so that geolocalized analysis of data may be conducted using six dimensions – traffic (including data and voice), users, terminal devices, revenue, complaints, and coverage. After, joint analysis of tool platform data and customized value weighting systems are used to design network planning schemes for carriers' different network planning needs, creating custom geolocalized “hotspots” for each carrier, and allowing carriers to prioritize their site investments. Compared with traditional coverage and capacity-based planning, this solution is not only better able to accurately identify hotspots, guarantee network coverage,and satisfy service requirements, it also maximizes ROI.

Accurate network optimization through geolocation

Huawei uses an enormous volume of test reports, site topographical locations, and terminal AGPS information to carry out geolocation and precise tracing. Huawei then compiles and charts this information to enable timely, accurate assessment of network performance at every site. Geo-location allows for the clear display of network coverage, voice data traffic, anomalies, users, and KQI distribution, to enable comprehensive analysis of network health and refined network optimization.

Geolocation of network coverage enables problems such as weak coverage, coverage hole, and coverage overlapping in different bands/frequencies/cells and their root causes to be quickly discovered, and guides engineers in their radio frequency optimization work. Geolocation of network coverage also allows for periodic network coverage assessments to be made. For example, coverage can be compared both before and after optimization, so that changes in coverage may be identified in a timely manner to avoid incorrect/invalid optimization. Geolocation of traffic can accurately identify hotspots, and regions with low or average speeds, making customer satisfaction that much easier to achieve.

Geolocation of anomalies involves identifying the location when an incident occurs, and then combining this information with cell information, the anomalous signal stream, and measurement reports to quickly locate faults. User geolocation, such as geolocalized mapping of changes in a user's mobile location during calls, can be used to collect information about signal quality and anomalies during the process, after which simulated drive tests may be used to promptly resolve user complaints and other problems. Geo-location of service quality refers to geolocalized charting of different service KQIs, such as call delay, number of buffers, etc., to identify locations where problems in service quality occur. This can then be combined with methods such as geolocalized coverage, geolocalized anomaly processing, etc., to aid further mapping analysis.

ACP optimizes efficiency & lowers OPEX

Huawei's Automatic Cell Planning (ACP) is based on geolocalized information and uses intelligent search algorithms to adjust and optimize a cell's RF parameters such as its directional angle, down tilt, as well as its power, station height, and antenna signal, according to data from sources such as cell engineering parameters, traffic, load, test reports, base station information, and drive-tests. Following these initial adjustments, ACP uses information from highly-accurate virtual maps, ray tracing and propagation modeling, and iterative forecast optimizing technology, as well as the weighting of objects and traffic on geographic grid maps, to produce traffic maps of coverage, capacity, and interference. This enables automatic determination of optimal parameters to resolve problems concerning network coverage, capacity, quality, etc. Compared with traditional RF planning and optimization, ACP lowers reliance on engineer experience, and can better conduct quantitative analysis of changes in coverage, capacity and interference in all layers of a network when RF parameters are adjusted. This ensures that the RF parameter adjustment plan produced is appropriate and accurate, while greatly reducing OPEX.

The future of geolocalized network data mining

Network optimization depends on geo-location; if analysis requires location, then accurate position is extremely important. Improving positional accuracy is essential, especially for hotspots and other dense areas, and in indoor settings. Three-dimensional positioning capabilities that identify the specific location of a user or site (perhaps at the granularity of a certain floor of a building) will be required for complicated HetNet environments. Furthermore, due to the fact that a large number of services are delivered indoors, determining how to first conduct geomodeling of actual buildings and construct multi-dimensional geographical data about building interiors and exteriors, and then conduct indoor/outdoor coordination simulations and highly accurate positioning/mapping based upon these, is vital to the expansion and evolution of subsequent services.

In this age of fast mobile internet growth, it's estimated that 67% of mobile apps designed for everyday use are location-based in some way, and the big IT players have each acquired geo-data companies qualified to conduct testing and Internet mapping services. This is significant because by combining their own services with the provision of apps with geolocation capabilities, these IT companies can leverage enormous amounts of low-level user resources to obtain information on users' locations, activities, services used, etc. These companies are therefore in possession of the resources necessary to carry out commercial data mining and analysis, and a few IT companies are already providing similar commercial marketing and inquiry services.

Therefore, as pipeline managers and innovators of transformative services, carriers need to seize this opportunity and use positioning services based on big data from test reports, networks, users, and OTT services to launch programs that guarantee service quality and user experience. This may include determining user location through positional analysis, and then using this information to provide relevant content. Partnering with IT companies to provide special service-quality guarantees to users, such as QoS control policies on network channels, guaranteed use of special services, and other innovative services, will be key to successfully telco transformation into service innovators.

Huawei currently has over 500 experts in the mobile broadband domain worldwide who are committed to better-meeting customer needs, allocating resources, and offering more effective network design plans. Huawei has over 50 patents in the geo-location field, and is providing network planning and design services for over 500 carriers worldwide, helping them plan and optimize their network, achieve smooth network evolution, improve ROI, and accelerate business success.


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