Course/Day 6/Small Cells, Trials & Capstone

Day Six

Small Cells, Feature Trials & Capstone

Optimize small cells, master the golden-parameter / trial workflow, map across vendors, and apply everything in an interactive end-to-end capstone on a degraded cell.

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Day objective — small-cell RF tuning, a disciplined feature-trial method, cross-vendor mapping, and a full diagnose → tune → verify capstone. Pick a sub-topic on the left — › opens a deep-dive.

6.1

Small Cell Optimization

The small-cell portfolio and its RF optimization — coverage and interference against the macro layer, PCI and power, plus LAA channel selection and Wi-Fi coexistence. Full detail in the dedicated deep-dive.

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Deep-dive: CB1000 · LTM (mmWave n257/8/61) · FRMM · FSR 5.4.0 femto, HetNet layering, LAA/Wi-Fi LBT, CSG access, real small-cell-pci-config, eICIC/ABS/CRE, SON.Open Small Cells ›

Coverage & interference

Right-size each small cell; manage macro↔small-cell & co-channel interference (CRE + ABS/eICIC).

PCI & power

Plan PCI (mod-3/mod-30) so dense small cells don't collide/confuse; set power to define the cell edge cleanly.

CB1000 · LTM · FRMMFSR 5.4.0 femtoLAA channel selectWi-Fi coexistencesmall-cell-pci-config (Home-eNB 28-bit)

6.2

Golden Parameters & Feature Trials

The workflow that ties the whole week together — the golden-parameter concept, the disciplined trial method, the Trial Tracker, and the FGR↔KPI mapping you use to select which trial to run.

Baseline

Snapshot the KPI & counters for the target cell; save the running config. Nothing changes yet.

Single-variable change

Change exactly one golden parameter (or one feature), chosen from the FGR↔KPI mapping for the failing family.

one golden param · from a recommended-configuration template

48-hour soak

Let it run a full busy-hour cycle so the KPI reflects real load, not a transient.

KPI verify

Compare before/after on the targeted KPI and guard KPIs (did fixing accessibility hurt retainability?).

Roll back

If the KPI didn't improve — or a guard KPI regressed — revert the single change. Log it in the Trial Tracker.

FGR ↔ KPI mapping — the basis for trial selection

Which features / golden params move which KPI family

KPI family	Key FGR features	Golden parameters
Accessibility	`CC3102 · RS0121/0122 · CC0301-03`	t300–t319 · RACH · admission/CAC
Retainability	`LC0302 · LC0401 · CC0401`	RLF+RRC timers · admission-preemption
Mobility	`MC1015 · MC1006`	A3-offset/TTT · A5 · reselection priority · q-hyst
Integrity	`RS0501 · CC6201 · RS0301`	DRX-inactivity · HARQ · UL power · TDD-power
Throughput	`RC0100 · RC0203 · RC1000 · RS0620/0622`	256QAM (mcs-table) · CA-SCell · MU-MIMO · DSS

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Trial selection — the failing KPI family points you at its FGR features and golden parameters; you pick one, trial it, and prove it. The Trial Tracker documents problem → change → before/after so every result is reproducible.

6.3

Cross-Vendor Mapping

Translate the Samsung model to and from Nokia for migration and benchmarking — and read the mappings honestly, by confidence level.

Mapping framework — verified vs rule-based, with confidence

Mapping type	How it's derived	Confidence
Verified	Confirmed 1:1 against both vendors' documentation / lab	High — use directly
Rule-based	Inferred from the shared 3GPP IE (same standard, different name)	Medium — validate on site
Heuristic	Best-guess by function where no direct equivalent exists	Low — treat as a starting point

Illustrative Samsung ↔ Nokia mapping (3GPP-anchored)

Concept (3GPP IE)	Samsung	Nokia (illustrative)	Type
A3 offset	`a3-offset-rsrp`	a3-offset / a3Offset	Rule-based
Time-to-trigger	`time-to-trigger`	timeToTrigger	Rule-based
RRC setup timer	`t300`	t300	Rule-based (same IE)
Cell reselection priority	`cell-reselection-priority`	cellReselectionPriority	Rule-based
PRB share (MOCN)	`plmn-N-ue-distribution-ratio`	vendor-specific RAN-sharing ratio	Heuristic

3GPP IEs (A3, TTT, t300, reselection priority) map cleanly by standard; vendor-proprietary features (PRB-portion, FGR features, counter families) rarely have a 1:1 and are heuristic — always validate on a live cell before a migration cutover. Nokia names above are illustrative placeholders, not from a Samsung↔Nokia mapping doc.

6.4

Capstone

Prove the whole method on one case — a degraded cell diagnosed from counters, fixed with golden-parameter changes across the five KPI families, and verified.

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Interactive capstone: pick a degraded cell, read its counters, diagnose the root-cause KPI family, apply the right golden parameter, and prove the KPI recovered — with the optimization report generated for you.Open the Capstone Simulator ›

The optimization report structure

// optimization report — one page per fix Problem : which cell, which KPI family, how far from target Counters : the PM evidence (Family IDs) that isolate the cause Change : the single golden parameter / feature changed Result : before → after on the target KPI (and guard KPIs) Method : baseline → single change → 48h soak → verify → keep / roll back

LAB

Hands-on Lab 6 — Capstone: Degraded-Cell Optimization

The final proof: take a degraded cell, diagnose it purely from counters, apply the right golden-parameter changes, and demonstrate a measured KPI improvement — run it now in the simulator.

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Run the interactive capstone — 5 degraded-cell scenarios (one per KPI family), diagnose → fix → verify → report.Open the Capstone Simulator ›

Hands-on Lab 6 · Capstone

Diagnose from counters → golden-parameter changes → prove KPI improvement

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1Take a degraded cell and diagnose the fault family from its counters
2Select the trial via FGR ↔ KPI mapping; apply golden-parameter changes
3Soak and verify; roll back cleanly if the KPI doesn't move
4Produce the optimization report: problem → counters → change → verified result

CountersGolden paramsTrial TrackerKPI verify

Deliverable — a customer-ready optimization report proving a measured KPI improvement on a real degraded cell.