Network Planning TRIZ Cases

UEs exchange FFP configurations and shared resources to coordinate sidelink transmissions, reducing collisions in unlicensed spectrum.

A coverage overlap structure identifies neighboring base stations and supports power savings while preserving adequate network coverage.

A country determination service routes APs to the correct AFC system by location, avoiding hardcoded countries and separate controls.

A model improvement module alternates training and idle modes to keep state predictions reliable while limiting resource use.

This case uses configurable UE- and gNB-initiated COTs to reduce uplink delay and scheduling conflicts in unlicensed spectrum.

This case coordinates overlapping BS-FFP and UE-FFP periods so NR-U UEs can transmit uplink data without waiting for downlink detection.

Wireless stations detect energy on adjacent channels and switch transmission direction within allocated slots to improve bandwidth use.

This case configures selective subband transmission when some LBT checks fail, improving data efficiency in shared spectrum.

This case uses tunable band-stop and sharp bandpass filters to manage TVWS gaps and limit out-of-band emissions.

This case uses selective UE mobility reports to tailor RF, beam, and resource settings against propagation loss and Doppler shifts.

A TDD controller aligns adjacent-band networks to reduce cross-link interference.

This case coordinates module observation timing to distribute traffic, limit interference, and meet total transmission-time limits.

This case aligns terminal and base station transmission-burst rules with LBT detection periods for 52.6–71 GHz unlicensed bands.

This case adjusts PRACH retries for LBT failures and timing conflicts, balancing handover reliability, delay, and device power use.

This case uses unlicensed-band identifier signaling and temporary IDs to expand network capacity while limiting delay and power use.

Flexible IAB slot formats align DL-UL resources for spatial multiplexing.

A cluster controller uses periodic imaging and AI/ML to update RF maps, allocate bandwidth, and sustain connectivity as environments change.

A core network node analyzes UE location and movement data to forecast behavior, optimize resources, and target paging.

Neighbor channel status and RSSI guide NBA-UWB target-channel selection, improving ranging accuracy in dense Wi-Fi environments.

This case models subscriber growth and cell data to forecast sector, vDU, and vCU breaches before congestion degrades service.

Network usage sequences help machine learning detect incorrect wireless cell locations and update datasets for infrastructure planning.

Preconfigured SpCells use lower-layer MAC signaling and cell indexes to reduce RRC exchanges and mobility interruptions.

Separate parameters for half- and full-duplex slots help UEs use resources efficiently, reducing latency and power consumption.