By Usman S. Goni
The need for CDMA networks constantly to expand and evolve
is putting pressure on wireless engineers to guarantee system performance.
What tools and methods are available to help them monitor and maintain
network quality? Usman S. Goni, LCC International Inc.
The explosive growth in wireless networks due to increased
subscriber demand has put pressure on cellular and PCS operators to differentiate
their service offerings in order to remain competitive. With the increased
number of service providers, the wireless marketplace of today is no longer
dictated to by the operator but by the subscriber who has several options
in choosing for a wireless service. The wireless engineer is therefore
faced with issues of network test and performance measurements in order
to address customer complaints and as part of network performance monitoring
to maintain quality of service (QoS).
Test procedures for RF engineering of CDMA wireless networks have evolved
since the initial deployment of IS-95 based systems. In this initial phase,
few test and measurement tools were available and signal strength logged
via drive-tests through pre-selected routes around the service area was
used to determine the system coverage performance. The system quality
of service was often assessed using measured frame error rate (FER) on
forward and reverse links as well as call set-up success and call drop
The key requirement of an optimum test and measurement tool is a comprehensive
data collection and analysis system that supports the needs of management,
engineering, operations and marketing services for providers. Above and
beyond this, however, an optimum test and measurement tool should provide
a means of evaluating quality of service from the subscriber's perspective
as well as track it over time. To remain competitive, it is essential
for an operator to compare the QoS among all systems in the market to
determine areas of competitive strength and to find out where improvements
are required. To ensure its effectiveness, benchmarking needs to be part
of a scheduled operational process since CDMA network capacity and coverage
performance tends to vary as the network subscriber size changes, in addition
to the dynamics of the local environment.
A known standard measurement of forward link system coverage has been
to monitor the signal strength of the pilot channel as a function of the
total interference density in the CDMA carrier band, popularly known as
Ec/Io. Since the Ec/Io metric provides a relative measure of interference
within the system, and also because the mobile uses the Ec/Io metric to
lock or remain on the CDMA system, it is used to determine the extent
of the system footprint on the forward path. The measurement process involves
a data logging system with or without diagnostic monitor capability, and
data collection is performed using the CDMA phone.
Although several system performance metrics such as Ec/Io, call drops
and initiation failures could be analyzed from the collected data, the
phone-based measurement process has some limitations. Firstly, the data
collected is largely controlled by the phone's dependence on the network,
including the limited range of PNs that the phone can scan. Thus, a scan
receiver-based Ec/Io measurement that is network-independent allows the
determination of key metrics for performance optimization. Using both
the scan receiver and the phone will provide the key to isolating pilot
pollution, as well as the capability to determine neighbor list alerts
and to build an optimum neighbor list and search window sizes. Figure
1 shows a typical measurement set-up for CDMA wireless network performance
evaluation and optimization.
It is not yet as straightforward to measure reverse link frame error rate
(FER) without resorting to setting up a call trace at the switch for the
test mobile. FER, which, by definition, refers to the number of frames
received in error as compared to the total number of transmitted frames,
has been the quantitative measure of voice quality on a CDMA network.
The usual FER level used on a CDMA network that corresponds to an acceptable
speech quality was in the range two to three percent or better. However,
measurement duration that will be used to quantify the FER network performance
is not an established standard, and therefore measurement results for
FER are often subject to interpretation.
Clearly, the significance of this measure in the statistical sense depends
on the number of frames transmitted. Thus, for measurement purposes, the
interval within which information is transmitted and used to measure the
quality of the network affects the accuracy and reliability of the result.
However, a voice quality-based measurement technique can now be used to
objectively determine the quality of not only CDMA but also any wireless
network. Using an equivalent aural quality score (AQS), accurate measurement
of voice quality can be obtained in real time. Thus evaluation of voice
quality in this way greatly supplements FER scores to provide a true evaluation
of subscribers' perception of the network call quality.
In addition, power control transmit gain adjust provides another dimension
to proper evaluation of reverse link system performance. The gain adjust
parameter is derived via post-processing of logged phone-based measurement
data, using a comprehensive analysis and parsing tool such as OptimEyes,
shown in Figure 2. The more positive the gain adjust is, the greater the
possibility of reverse link noise rise and hence the more power required
for the mobile to ensure the attainment of target Eb/No at the best serving
Quality benchmarking is another important part of the test and measurement
process. In a competitive environment where several wireless services
are offered, a network operator may need to evaluate his/her network to
determine the need for increased service performance, in order to establish
a stronger subscriber base. This is the process typically described as
The test and measurement tools employed for benchmarking are designed
to track changes in the network performance as perceived by the subscriber,
and hence to provide a more objective approach to quantifying system quality
performance. All the wireless networks in the market are evaluated by
collecting measurement data via drive testing using test phones registered
on all the networks.
Before embarking on the tests, system-wide drive routes that were used
for system-wide optimization of the network, or other new routes, are
selected. The period of the measurements should span through the system
busy hour to allow the collection of data that represents the network
Other measurement tools that are employed for these tests include audio
quality assessment modules, scan receivers, specialized data collection
software and computer-based data logging systems. A relative assessment
of the wireless network performance for all the operators in the same
market can then be compared on the basis of subscribers' perceived quality.
In this way, a more comprehensive method is provided for operators to
measure their performance and determine areas of improvement.
In addition to the transparency of the benchmarking technique to the air
interface technology of the various operators' networks, the benchmarking
process is for the first time, the optimal approach in determining the
balance between the forward and reverse links of a CDMA wireless network
. It is well known that the air interface specifications for IS-95
forward and reverse links are entirely different. Thus, network performance
engineers often analyze CDMA forward and reverse link balance by comparing
outages in specific geographic bins. For a given bin, link imbalance is
said to occur when either the forward or reverse links is in outage. However,
the accuracy of this measurement process depends on the size of the bin
and the data reduction process used. Hence, a more accurate performance
link in a CDMA network could be determined through simultaneous evaluation
of reverse and forward link AQS.
Next, we turn to system performance engineering. Traffic measurements
and reporting are an essential part of CDMA network performance engineering.
The capacity performance of the network is usually determined from a detailed
analysis of traffic usage on each sector over a period of time, usually
during the peak traffic hour.
Since coverage of the system is impacted by increased usage beyond a given
nominal design load, traffic carried by sectors (or cells) is usually
monitored to determine optimum loading levels beyond which enhancements
to the capacity are incorporated to maintain quality.
The measurement tools required are usually part of the vendors' offering,
which comes as a suite of features associated with the MSC or as a direct
interface to the OMC. However, there are network performance management
tools not tied to one particular vendor-type infrastructure, that could
provide service measurements, performance analysis and reporting. These
network traffic measurement tools are used to automatically collect and
monitor valuable network performance statistics, analyze key network performance
indicators, identify current and potential performance problems, investigate
problem causes, and forecast network growth to aid in optimal planning.
A key metric for CDMA network planners is determining channel elements
overhead due to soft handoff. Although a key feature of CDMA, soft handoff
overhead becomes a major constraint to forward link capacity, especially
for sites in dense urban core areas, owing to excessive cell overlaps
caused by the need to provide greater in-building signal penetration.
A network performance measurement tool can be configured to determine
sectors with excessive channel element overhead and hence determine corrective
actions to preclude capacity problems.
In the early days, CDMA network performance engineering relied on deriving
raw traffic data and performing detailed spreadsheet-based traffic analysis,
trending and growth planning. It is inefficient to manually monitor such
network problems as congestion, drops on the air interface, and fixed
network utilization, on a daily basis. Automated performance measurement
will allow network operation engineers and planners to forecast medium-to-long
term site and network growth, as well as evaluate usage patterns and enhance
overall network-wide performance.
As CDMA networks worldwide continue to mature, supporting an estimated
subscriber base of about 23 million, tools for system performance tests
and measurements will continue to evolve to meet the challenges of maintaining
network quality. The demand for faster system rollout coupled with the
need for advanced service features in a rapidly expanding wireless market
has put greater pressure on CDMA wireless network operators to seek quick
and automated response solutions to network problems. To fulfil these
needs, test and measurement tools with intelligent network diagnostics
capabilities are required. Test and measurement equipment manufacturers
are therefore faced with the tasks of improving on the earlier version
of their CDMA software and hardware products, as well as continuing to
innovate and develop new products offerings to meet these demands.
It is anticipated that future CDMA based wireless networks supporting
high-speed data and multi-media services would require more intelligent
network test and measurement tools. One major challenge would be to monitor
and track traffic pattern and variations for the different 3G services
to be offered. Test and measurement products for such services are currently
Usman S. Goni, Ph.D., is a Senior Principal Engineer
with Engineering Services Group LCC International Inc., a leader in wireless
communications services, test and measurement products.
 Nandu Gopalakrishnan, CDMA Voice Quality-Based Optimization, Wireless
Business Technology, January 1998