Signal to Insight

WCDMA / HSUPA  ·  packet performance By late 2011, voice KPIs alone were no longer telling the full story. Networks could meet call setup and drop targets while users complained that data sessions felt slow, stalled, or unstable. These problems were harder to diagnose because they rarely showed up as outright failures in any single counter. Data performance fails quietly. Unlike voice, it degrades before it collapses. A call drops, and you know something is wrong. A data session retries silently and times out. The user blames the network. The dashboard stays green. What voice metrics did not cover In several WCDMA clusters, voice performance looked acceptable while packet-switched KPIs quietly degraded. High RRC connection success rates masked frequent uplink instability, excessive retransmissions, and rising interference during busy hours. Metric Voice view Data view (same cells) RRC setup success 97.8% -- within target ...

WCDMA  ·  mobility analysis The most serious network issues no longer sit neatly inside individual cells. They appear in the transitions between them. Voice traffic keeps growing, smartphones are becoming common, and users are no longer staying still. Cells show solid coverage and acceptable KPIs, yet dropped calls continue. Almost always during movement. Walking short distances, driving along roads, or shifting slowly indoors triggers failures that static testing cannot reproduce. Mobility failures are path problems, not cell problems. That single realization changes how the whole analysis is approached. Handover failures at cell boundaries In several WCDMA clusters, radio link failures happened repeatedly at specific cell edges. The serving cell looked healthy. The target cell looked healthy. The handover transition itself was unstable. Serving cell: CPICH Ec/No = -8 dB, RSCP = -78 dBm -- acceptable Target cell: CPICH Ec/No = -9 dB, RSCP = -81 dBm -- ac...

 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...

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...