Level 13

5G Optimization & Troubleshooting

Master 5G network optimization and troubleshooting end-to-end — coverage and capacity optimization (tilt strategy, pilot pollution, load balancing), parameter optimization (handover, power control, RACH, MIMO, scheduling, TDD patterns), throughput and latency optimization (NR throughput calculation, CA/DC, 256QAM), systematic troubleshooting (registration failure, PDU session failure, call drops, RLF, HO failure, VoNR issues), and SON/automated optimization (ANR, MRO, MLB, MDT, AI/ML-driven optimization).

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Coverage & Capacity Optimization

0/8

Learn the optimization lifecycle and master coverage optimization techniques — overshooting/undershooting correction, pilot pollution resolution, coverage hole remediation, capacity optimization with load balancing (MLB/MRO), carrier aggregation, and SSB beam optimization.

Optimization lifecycle: plan → deploy → optimize → monitor

The continuous optimization lifecycle — planning phase (predict coverage using propagation models), deployment phase (install sites with planned parameters), optimization phase (drive test, analyze KPIs, tune parameters), and monitoring phase (continuous KPI dashboards, alarms, trend analysis). Why optimization never ends: network changes, traffic growth, new features.

lesson3 min

Coverage optimization: overshooting, undershooting, tilting strategy

How to fix coverage issues using antenna tilt — overshooting detection (cell serves UEs far beyond intended boundary, high TA values, interference to distant cells), undershooting detection (coverage falls short, gap between this cell and neighbor), mechanical vs electrical tilt (mechanical tilts the entire pattern, electrical tilts via phase shifters, more precise). Tilt rules of thumb and impact on coverage radius.

lesson4 min

Pilot pollution: detection (>3 cells above threshold) and resolution

Pilot pollution deep dive — detection criteria (3+ cells with RSRP within 6 dB of serving cell at same location), impact on SINR and throughput, resolution strategies: reduce power on overshooting cells, increase downtilt, adjust azimuth to redirect coverage, change antenna type (narrower beamwidth). RSRP vs SINR scatter plot analysis for detection.

lesson4 min

Coverage hole remediation: new site, antenna swap, parameter change

Decision framework for fixing coverage holes — when to add a new site (large gap, no neighboring cell can extend), when to swap antenna (higher gain or wider beamwidth), when to adjust parameters (reduce tilt to extend coverage), when to add a repeater or small cell (indoor or shadowed areas). Cost-benefit analysis for each approach.

lesson4 min

Capacity optimization: load balancing, MLB, MRO, carrier aggregation

Capacity optimization techniques — Mobility Load Balancing (MLB) shifts users from congested cells to less loaded neighbors by adjusting handover parameters, Mobility Robustness Optimization (MRO) reduces handover failures, carrier aggregation adds bandwidth by combining carriers (intra-band contiguous, intra-band non-contiguous, inter-band). Cell splitting and sector splitting for dense areas.

lesson4 min

SSB beam optimization: beam sweep pattern, SSB periodicity tuning

SSB beam configuration and optimization — SSB beam count (4 for sub-6 GHz, up to 64 for mmWave), beam sweep pattern (how beams are arranged to cover the cell sector), SSB periodicity (5, 10, 20, 40, 80, 160 ms — tradeoff between beam tracking speed and overhead), beam-specific coverage optimization for Massive MIMO panels.

lesson3 min

Real-world: Optimize a high-traffic urban area (stadium, mall, CBD)

Case study lab — given a high-traffic urban area (stadium during an event) with KPIs showing degraded coverage and capacity: identify the issues (pilot pollution, congestion, coverage holes), apply optimization techniques (tilt changes, load balancing, CA activation), and compare before/after KPIs.

lab5 min

Quiz: Coverage & capacity optimization

Test your understanding of the optimization lifecycle, tilt strategies, pilot pollution resolution, coverage hole remediation, load balancing, and SSB beam optimization.

quiz3 min

Parameter Optimization

0/8

Master the key RAN parameters that control network behavior — handover parameters (A3 offset, TTT, hysteresis, CIO), power control (P0, alpha, TPC), RACH parameters, MIMO/beamforming configuration, scheduler algorithms, and TDD slot patterns.

Handover parameter optimization: A3 offset, TTT, hysteresis, CIO

Handover parameter deep dive — A3 offset (target must be this much stronger than source to trigger, typical 2-3 dB), Time-to-Trigger (TTT, 40-640 ms, delays HO decision to avoid ping-pong), hysteresis (additional margin on A3 condition), Cell Individual Offset (CIO, per-neighbor adjustment). How each parameter affects HO: too early, too late, ping-pong.

lesson4 min

Power control optimization: PCMAX, P0, alpha, TPC commands

UL power control — PCMAX (maximum UE transmit power, typically 23 dBm), P0 (target received power at gNB), alpha (path loss compensation factor, 0-1), TPC commands (gNB adjusts UE power in real-time). Open-loop power control (initial power estimate) vs closed-loop (continuous adjustment). Impact on coverage, interference, and battery life.

lesson4 min

RACH optimization: preamble config, power ramping, target received power

RACH parameter optimization — number of preambles (64 total, contention-based vs contention-free split), preamble format (affects cell radius), initial preamble power, power ramping step (how much to increase per attempt, typically 2 dB), preambleTransMax (max attempts before failure), RACH target received power (how strong preamble should arrive at gNB). Optimizing for coverage vs capacity.

lesson4 min

MIMO & beamforming optimization: rank adaptation, CSI reporting, codebook

MIMO configuration optimization — rank adaptation (how quickly the system switches between MIMO layers based on channel conditions), CSI reporting periodicity (shorter = more accurate but more overhead), codebook configuration (Type I vs Type II, tradeoff between feedback overhead and beamforming precision), SU-MIMO vs MU-MIMO scheduling decisions.

lesson4 min

Scheduling optimization: proportional fair, round robin, max C/I

Scheduler algorithm comparison — Round Robin (equal time slots, fair but inefficient), Max C/I (serve the user with best channel, maximizes throughput but starves cell-edge users), Proportional Fair (balance fairness and efficiency, most commonly used), and QoS-aware scheduling (prioritize based on 5QI). Vendor-specific scheduler implementations.

lesson3 min

DL/UL TDD slot configuration: DDDSU, DDSUU, patterns and impact

TDD slot pattern optimization — DDDSU (4:1 DL:UL ratio, optimized for DL-heavy traffic), DDSUU (3:2 ratio, more UL for video calls/uploads), flexible symbols (can be DL or UL based on traffic). Impact on DL/UL throughput ratio, latency (UL wait time depends on next available UL slot), and cross-link interference between adjacent operators.

lesson3 min

Lab: Optimize parameters for a degraded 5G cluster — 10 cells, 5 issues

Hands-on lab — given a 10-cell 5G cluster with 5 performance issues (high HO failure rate, RACH failures, low throughput, pilot pollution, poor UL coverage), diagnose each issue from KPI data, identify the responsible parameter, and apply the correct parameter change to resolve it.

lab6 min

Quiz: Parameter optimization

Test your knowledge of handover parameters, power control, RACH configuration, MIMO optimization, scheduler algorithms, and TDD patterns.

quiz3 min

Throughput & Latency Optimization

0/7

Learn to calculate 5G NR theoretical throughput, optimize with carrier aggregation and dual connectivity, enable higher-order modulation (256QAM), analyze latency contributors, and systematically troubleshoot low throughput issues.

5G NR throughput calculation: RBs × layers × modulation × coding rate

How to calculate 5G NR peak and practical throughput — number of RBs (depends on bandwidth: 273 RBs for 100 MHz SCS 30 kHz), MIMO layers (up to 4 for typical UE, up to 8 theoretical), modulation (QPSK=2, 16QAM=4, 64QAM=6, 256QAM=8 bits/symbol), coding rate (0-1), overhead (DMRS, CORESET, SSB ~14-25%). Step-by-step calculation with examples.

lesson4 min

Carrier Aggregation (CA) and Dual Connectivity (EN-DC, NR-DC)

Combining carriers for higher throughput — Carrier Aggregation (CA, multiple NR carriers combined at MAC layer, up to 16 component carriers), EN-DC (LTE + NR dual connectivity for NSA, split bearer at PDCP layer), NR-DC (NR + NR for SA, MCG + SCG). Configuration combinations: n78 + n78 intra-band CA, n78 + n257 inter-band, LTE B3 + NR n78 EN-DC.

lesson4 min

256QAM DL / 64QAM UL enablement and conditions

Higher-order modulation optimization — 256QAM DL (33% more bits per symbol vs 64QAM, requires SINR > 20 dB and low EVM, UE capability required), 64QAM UL (50% more than 16QAM, requires good UL SINR and UE support). Enabling conditions: feature license, UE capability check, SINR thresholds, EVM requirements. Network-wide enablement vs per-cell.

lesson3 min

Latency analysis: air interface, backhaul, core contributions

End-to-end latency breakdown — air interface latency (processing time + HARQ RTT + scheduling delay, typically 1-4 ms for sub-6 GHz), backhaul latency (fiber: 0.1-1 ms, microwave: 1-5 ms, satellite: 20-600 ms), core network latency (UPF processing: 0.5-2 ms, inter-DC routing: 1-5 ms). Total typical RTT: 10-30 ms for 5G, how to reduce each component.

lesson4 min

Real-world: Low throughput troubleshooting — systematic approach

Systematic approach to diagnosing low throughput — 8 common causes: (1) poor RF/low SINR, (2) high interference, (3) cell congestion/scheduling, (4) backhaul bottleneck, (5) wrong MCS/CQI mapping, (6) MIMO rank reduction, (7) missing CA/DC configuration, (8) transport/server limitation. Decision tree for root cause analysis with KPIs to check at each step.

lesson5 min

Lab: Analyze and improve throughput for an underperforming cell

Hands-on lab — given an underperforming cell with DL throughput 60% below expected, analyze KPI data (SINR distribution, CQI histogram, MCS distribution, PRB utilization, MIMO rank, CA status), identify the root cause(s), apply corrective parameter changes, and predict the expected throughput improvement.

lab5 min

Quiz: Throughput & latency

Test your understanding of NR throughput calculation, carrier aggregation, dual connectivity, 256QAM enablement, latency analysis, and throughput troubleshooting.

quiz3 min

Troubleshooting Masterclass

0/8

Master systematic 5G troubleshooting — registration failures (NAS 5GMM cause codes), PDU session failures (5GSM causes, PFCP), call drops and RLF (T310/T311, RLF reports), handover failures (too early/late/wrong cell), VoNR quality issues, and a timed end-to-end troubleshooting challenge.

5G troubleshooting methodology: systematic 7-step approach

The structured 7-step troubleshooting approach — (1) Define the problem precisely (what, where, when, who affected), (2) Gather data (KPIs, alarms, drive test, traces), (3) Analyze data (compare against baselines, identify anomalies), (4) Formulate hypothesis (root cause theory based on data), (5) Test hypothesis (targeted test, parameter change, trace analysis), (6) Implement fix (apply parameter change, hardware fix, config update), (7) Verify and document (confirm KPIs improved, document root cause and solution).

lesson4 min

No service / registration failure: NAS reject causes (5GMM cause codes)

Troubleshooting registration failures — common 5GMM cause codes: #3 (Illegal UE), #5 (PEI not accepted), #6 (Illegal ME), #7 (5GS services not allowed), #9 (UE identity cannot be derived), #11 (PLMN not allowed), #15 (No suitable cells in tracking area), #22 (Congestion). For each cause: what it means, where to check (AMF/UDM/AUSF logs), and how to resolve.

lesson4 min

No data / PDU session failure: 5GSM cause codes, N4 PFCP failures

Troubleshooting PDU session establishment failures — 5GSM cause codes: #26 (Insufficient resources), #27 (Missing or unknown DNN), #28 (Unknown PDU session type), #29 (User authentication failed), #31 (Request rejected, unspecified), #33 (Requested service option not subscribed). N4 PFCP Session Establishment failures between SMF and UPF. GTP tunnel creation issues on N3/N9.

lesson4 min

Call drops / RLF: RRC re-establishment, T310/T311 timers, radio problems

Troubleshooting call drops and Radio Link Failures — RLF detection (N310 out-of-sync → T310 → RLF), RRC Re-establishment procedure (T311 timer, cell selection, re-establishment to same or different cell), RLF report analysis (RSRP/SINR at failure point, last serving cell, time since HO). Common causes: coverage hole, sudden interference, fast fading, mobility failure, hardware fault.

lesson4 min

Handover failure: too early, too late, wrong cell — HO failure classification

Handover failure classification from 3GPP — Too Early HO (UE successfully hands over but immediately experiences RLF on target, re-establishes on source → source cell A3 offset too low), Too Late HO (UE experiences RLF on source before HO triggers → A3 offset too high or TTT too long), HO to Wrong Cell (UE hands over to cell B but immediately has RLF, re-establishes on cell C → neighbor list wrong or CIO needed).

lesson4 min

VoNR quality issues: MOS < 3.0, jitter, delay, codec problems

Troubleshooting VoNR quality — MOS (Mean Opinion Score) measurement and thresholds (4.0+ excellent, 3.5-4.0 good, 3.0-3.5 fair, <3.0 poor), jitter analysis (>30 ms causes audible artifacts), one-way delay (>150 ms causes conversation difficulty), codec issues (EVS vs AMR-WB, codec mismatch between endpoints), QoS bearer problems (5QI 1 not properly configured), and ROHC header compression failures.

lesson4 min

Lab: End-to-end troubleshooting challenge (timed, 5 scenarios)

Timed troubleshooting challenge — 5 independent scenarios, each presenting symptoms (KPIs, alarms, user complaints), network topology, and relevant log/trace data. For each scenario: identify the root cause, explain the evidence, and recommend the specific fix. Scenarios cover registration failure, throughput degradation, RLF cluster, handover failure, and VoNR quality issue.

lab8 min

Quiz: Troubleshooting

Comprehensive level gate quiz covering 5G troubleshooting methodology, NAS cause codes (5GMM/5GSM), RLF analysis, handover failure classification, and VoNR quality diagnostics.

quiz5 min

SON & Automated Optimization

0/6

Explore Self-Organizing Networks (SON) — centralized, distributed, and hybrid architectures, key SON functions (ANR, MRO, MLB, PCI optimization), vendor implementations, Minimization of Drive Tests (MDT), and AI/ML-driven network optimization.

SON architecture: centralized, distributed, hybrid

Self-Organizing Network architectures — Centralized SON (algorithms run in OSS/SON server, global view but slower response, typical for inter-cell optimization), Distributed SON (algorithms run in each gNB, fast local decisions but no global view, typical for intra-cell functions), Hybrid SON (combination, most common in practice). Comparison of response times, coordination ability, and vendor implementation approaches.

lesson3 min

SON functions: ANR, MRO, MLB, PCI optimization, RACH optimization

Key SON functions — Automatic Neighbor Relations (ANR, automatically discovers and adds neighbor cells from UE measurement reports), Mobility Robustness Optimization (MRO, detects too-early/too-late/wrong-cell HO failures and adjusts parameters), Mobility Load Balancing (MLB, shifts traffic from congested to less loaded cells), PCI Optimization (assigns collision-free and confusion-free PCI values), RACH Optimization (auto-tunes preamble config based on RACH statistics).

lesson4 min

Vendor SON implementations: Ericsson SON, Nokia SON, Samsung SON

How major vendors implement SON — Ericsson (SON functions integrated in ENM/gNB, strong ANR and MRO, centralized optimization via Network Design tool), Nokia (NetAct-based centralized SON, gNB-level distributed functions, AirScale RAN features), Samsung (Samsung SON Manager, integrated with their vRAN, AI-based optimization features). Feature comparison across vendors.

lesson3 min

Minimization of Drive Tests (MDT): logged/immediate measurements

MDT as a 3GPP standardized alternative to drive testing — Logged MDT (UE records measurements in background while in RRC_IDLE or RRC_INACTIVE, uploads at next connection, provides coverage data from real users), Immediate MDT (UE reports measurements in RRC_CONNECTED on request, provides real-time performance data), MDT data usage (coverage verification, interference detection, parameter optimization without drive tests).

lesson3 min

AI/ML-driven optimization: anomaly detection, predictive optimization

Machine learning for network optimization — anomaly detection (ML models learn normal KPI patterns, flag cells that deviate), predictive optimization (predict traffic patterns, pre-configure parameters before congestion), reinforcement learning for parameter tuning (agent learns optimal tilt/power/HO parameters through trial), digital twin (simulate network changes before applying), and RAN Intelligent Controller (RIC) from O-RAN as the platform for AI/ML optimization apps (xApps/rApps).

lesson4 min

Quiz: SON & automation

Test your knowledge of SON architectures, SON functions (ANR, MRO, MLB), vendor implementations, MDT, and AI/ML-driven optimization.

quiz3 min