GSM / WCDMA · OSS analysis Networks could look perfectly healthy on OSS dashboards while subscribers kept complaining about dropped calls and poor voice quality. Call setup success rate, overall drop rate, and congestion KPIs stayed comfortably within target. Real users were still experiencing frequent interruptions. The disconnect almost always came down to one thing: aggregation hiding real problems. How averages conceal cell-level failure Performance KPIs were typically calculated and reported as averages at BSC or cluster level. In dense urban environments, a handful of problematic cells could fail repeatedly without moving the needle on the aggregated numbers. Their impact was diluted by volume. From the customer's perspective, those few cells were the only thing that mattered. Example: cluster of 40 cells, BSC-level KPI reporting Call drop rate (cluster average): 1.8% -- within target Call drop rate (worst 3 cells): 12%, 9%, 11% -- far outs...
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A strong signal is not the same as good performance. GSM / early WCDMA · field observations That took time to accept. Many of the worst-performing clusters had excellent RSSI, clear dominance, and coverage plots that looked textbook clean. Yet they produced persistent call drops, handover failures, and poor voice quality day after day. The issues were rarely coverage gaps. They came from how the radio system behaved under real traffic load. That distinction is not obvious until you spend enough time correlating drive data against busy-hour OSS counters and watch the two tell completely different stories. Static neighbor planning Neighbor lists were typically planned once during rollout and rarely touched afterward. Over months, traffic patterns shifted. New sites were added. Antenna adjustments changed dominance areas. The original neighbors became outdated, but the configuration stayed the same. Symptom in OSS (busy hour): HO failure rate elevated in cl...