1. GSM voice quality Final report Tunis, 15 th of July 2004 Customer: Tunisiana

2. Telecommunications and IT Know-How in:  Training  Commissioning and Maintenance (OAM)  Network Planing  Radio coverage tests  Traffic measurements and analysis Company profile (MCI) MCI: Management Conseil et Ingénierie

3. Traditional approach for GSM radio link test: Protocol analysers (RXQUAL) Data useful in network maintenance but not for the estimation of the Quality of Service (QoS) as viewed by the mobile phone user (perception!!). RXQUAL does not represent “real life” conditions. The following slides discuss inherent problems of RXQUAL and demonstrate that the measurement cannot be related to perceived speech quality in an accurate and reliable way. Why voice QoS

4. In today’s competitive environment, it is important for GSM operators to be able to accurately assess performance and voice quality of their networks in order to maintain or extend market position. From a subscriber’s point of view, the relevant performance measure are: Call success rate Speech quality QoS is critical to success

5. RXQUAL does not consider the varying efficiency of interleaving and bit error correction under different environmental conditions (fading or frequency hopping) RXQUAL does not consider quality degradation caused by stolen speech frames (Handover: TCH becomes FACCH for 0,2s) RXQUAL does not detect any PSTN quality impairing effects (echo, crosstalk or noise in the analogue part of the network) Speech quality is the only parameter to detect defects within voice processing circuits Arguments for Speech Quality

6. RXQUAL does not recognise whether bad speech frame indication (BFI) failed Downlink RXQUAL may Fail in Detecting QoS degradation in Uplink Direction RXQUAL does not consider acoustical power level variations Arguments for Speech Quality

7. Objectives of the study  Evaluation of the quality of service for the telecom operator: Orascom Telecom Tunisia  Location: Tunis

8. Training of the agents Identification of the typical noise (echo, metallic or robot voice, lost syllables, etc…) ; Evaluation of the voice quality (recorded audio samples) MCI used a software tool for recording and editing of voice messages

9. Training of the agents The agents were trained on : Use of MCI Hotline Numbers to be called Itineraries to follow Manipulation of topographical maps Use of the test forms

10. Equipment used

11. Test types Outdoor : Outside buildings (pedestrian) Indoor : Inside buildings, underground excluded: Close to doors or windows Far from doors and windows Incar : Inside a car also called drive test

12. Measured parameters Call success rate / Call failure: Due to network saturation Due to missed coverage Call drop rate / Call completion rate Voice quality noted 1 to 4: Excellent quality Some noise but still good quality Some words are not understood but the conversation is still OK Bad quality. The conversation is not understood Speech quality relates to: Intelligibility: Quality of perception of the meaning or information content of what the talker said; Naturalness: Degree of fidelity to the talker’s voice; Loudness: Absolute loudness level at the listener’s side.

13. Sample of the study Totally 2706 calls: - Outdoor: 1236 - Indoor: 1226 - Incar: 244 Tunis was divided into: - 6 regions - 79 sectors with different sizes Incar calls: all main roads tested, also bidirectionally

14. R E S U L T S O F T H E S T U D Y

15. Major Indoor points Liste of the indoor points (365 points) :

16. Constitution of the sample Distribution of the calls by regions

17. Speech quality by regions (1)

18. Speech quality by regions (2) Distribution of the the notes 3 and 4 by regions

19. DATA ON GIS ArcView

20. Sample on ArcView (1) Habib Bourguiba Avenue

21. Sample on ArcView (2) Ariana City Center

22. Data for a sample on ArcView Data stored on GIS for each measurement

23. End