Overall QoS for 2G, 2.5G, and 3G systems comprises three important components, all of which need to be constantly monitored and optimized as networks change in response to increasing coverage and capacity demands:
• Accessibility – getting on the system
• Retainability – staying on the system
• Connection quality – having a good service experience while using the system
QUALITY OF SERVICE EVALUATION
The three mechanisms available to monitor, analyze, and evaluate QoS and take corrective actions are customer complaints, drive tests, and network statistics, all three of which are described below. Each mechanism has certain advantages and disadvantages, usually with conflicting priorities for limited optimization resources.
Customer ComplaintsAdvantages
• Real problems experienced by customers using the service
• Decision-forming/influential
Disadvantages
• Subjective
• Often vague with little supporting data
• Often received too late to react to the situation
• Require filtering by customer service before being handled by the engineering department
Drive Tests
Advantages
• Real calls
• Cause of failure can be identified
• Good for benchmarking
• Good for network pre-launch tuning (startups and new deployment projects)
Disadvantages
• Low volumes/statistically insignificant
• One terminal type
• Only ground level and in-car service
• Predetermined routes, calling patterns only
• Labor-intensive analysis
Network Statistics
Advantages
• All calls can be monitored
• Trends can be measured, by specific geographical areas of interest or for the entire network
• Trends are stable
Disadvantages
• Indicate problems but not their causes or solutions
• Do not differentiate customer value
Established GSM operators use clearly defined network QoS key performance indicators (KPIs) with target thresholds to be achieved. The KPI thresholds are usually revised once a year, and new goals are set as the business priorities change. Network performance management and optimization activities ensure that QoS targets are met.
For underperforming areas (sections of the network failing the KPI thresholds), optimization projects are initiated. Using all available methods, these projects fully analyze the performance of the area to understand the problems and take corrective actions. In such optimization projects, a combination of customer complaints, drive tests, and network statistics is used. Usually, statistical analysis and customer complaints are used to identify problems, while drive tests are used to verify them and/or the solution(s). However,
drive tests alone cannot be relied on to provide insight into the offered service. Drive tests can only provide an indicator of QoS for traffic that is highly mobile and at ground level. A large proportion of traffic offered via mature networks is static and often originates at higher-thanground levels. In several mature European
networks there is, on average, only one handover per call, which indicates the static nature of traffic. This makes statistics the most useful mechanism for identifying QoS shortfalls.
However, experience is required in recognizing problem trends, identifying the causes, and taking corrective actions. This, in turn, requires good knowledge of the system, analytical skills, and experience in network performance management and optimization. Nevertheless, using statistical analysis properly and to the fullest
extent possible can significantly improve QoS.
WHAT NEEDS TO BE MONITORED AND OPTIMIZED?
The trends of several KPIs must be closely monitored. A summary of the most important KPIs that can have an impact on the offered QoS follows.
Circuit Switched (CS) – Voice
• DCR: The dropped call rate (DCR) provides the customer-perceived dropout performance. It is calculated over an area of the entire network or a geographical area and not on a per-cell basis, because a call cannot be statistically related to just one cell, due to handovers.
• Minute-Erlang/Drop: This KPI indicates the average time between dropped calls. It is a division of traffic expressed in minute- Erlangs divided by the total drops and is inversely proportional to DCR. It is a good
way to evaluate the effectiveness of optimization activities because it takes into account the carried traffic and is more sensitive to changes than DCR.
• CFR: The congestion failure rate (CFR) indicates the failure rate of assignments due to congestion and can be used on a cell basis for engineering, planning, and troubleshooting purposes and on an area basis to provide a measure of the customer-perceived traffic congestion. GSM operators have developed sophisticated CFR formulas to account for the effects of features such as directed retry and cell load-sharing when measuring customer-experienced congestion.
• CCSR: The call completion success rate (CCSR) can be derived either from network statistics or from drive test statistics. It takes into account the fact that all failures are either drops or unsuccessful call set-ups. The total number of failures is divided by the total number of call attempts. It is a good method to use to evaluate the network accessibility and retainability as perceived by the customers. In the United Kingdom, the Office of Telecommunications (OFTEL), a governing body, uses CCSR from drive tests to declare the best network for QoS. Every 6 months, all network operators make approximately 22,000 calls while driving 305 pre-defined routes with clearly defined call patterns. At the end of the cycle, the operators submit a summary of the results and all drive-test files to OFTEL.
• DTCHR: The dropped traffic channel rate (DTCHR) indicates the drops at the cell level.
It is used for engineering purposes only (and not for reporting), to identify cells with high drops. Optimizing these cells improves DCR and CCSR.
• SDCCHSR: The standalone dedicated control channel success rate (SDCCHSR) indicates the rate of successful air interface signaling channel assignments and is used for engineering purposes only, to optimize cells with high failure rate. Optimizing such cells improves CCSR.
• HSR: Handover success rate (HSR) indicates the success of handovers. Minimizing handover failures improves DCR.
Packet Switched (PS) – Data (GPRS)
• Cell Throughput: Cell throughput is an end-to-end KPI used at the cell and network levels to indicate data throughput.
• RTT: Decreasing roundtrip time (RTT) delay increases throughput.
• TBF Multiplexing: Temporary block flow (TBF) multiplexing indicates the number of users per time slot usage of general packet radio service (GPRS) resources. A high number of users per time slot decreases the data throughput.
• Peak Hour: Peak hour statistics are of great significance, because they correspond to the time of heavy utilization of network resources. In a way, they provide the “worstcase” scenario.
• Day: Daily statistics are introduced to provide a way of averaging temporary fluctuations of hourly data. Problems can be identified and corrective actions triggered with more confidence. Trends with daily
values are also used for reporting and benchmarking.
• Online: Online statistics provide almost real-time monitoring of the network, if this is necessary. Statistics can be obtained directly from the switching node, where outputs are available every 15 minutes.
Classification by Resource Type or Event
Statistics can be classified by resource type or the events they refer to. Both user-defined formulas and “raw” counters are grouped into one of the following categories:
• Random access channel measurements• Standalone dedicated control channel (SDCCH) measurements
• TCH measurements
• Idle channel measurements
• Handover measurements
• Subscriber disconnection measurements
• Link access protocol on the D-channel (LAPD) signaling measurements
• BSC measurements