Fuzzy Logic Multi-RAT Selection for 5G Handover Optimization
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Solution Overview
Problem
Existing LTE cellular networks face inefficiencies in cell-selection/reselection and handover procedures, leading to frequent handovers and adverse effects on downlink throughput and latency, especially in multi-RAT scenarios, which are exacerbated in the development of 5G networks with ultra-dense deployments.
Innovation Solution
The implementation of a fuzzy logic-based multi-RAT selection and handover method that utilizes load information, Received Signal Strength, Reference Signal Received Quality, and Service Sensitivity to Latency, along with the decoupling of control and user planes, to optimize radio access technology selection among macrocells, femtocells, and WiFi access points, reducing handover frequency and improving network performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing LTE cell-selection/reselection and handover procedures are used, then basic network connectivity is maintained, but handover frequency increases and network performance deteriorates in multi-RAT scenarios
Solution Approach 1:
The patent changes the decision parameters for RAT selection from simple signal strength thresholds to a comprehensive evaluation system considering multiple factors including QoS requirements, network load, user mobility state, and service sensitivity to latency. This multi-parameter approach enables more accurate RAT selection that maintains connectivity while optimizing throughput and reducing unnecessary handovers.
Solution Approach 2:
The patent implements a feedback mechanism where the network continuously monitors handover performance, throughput metrics, and latency measurements, then uses this information to dynamically adjust RAT selection policies. The system learns from past handover outcomes and optimizes future decisions, reducing frequent handovers while maintaining network reliability and performance.
2Reliability
If existing handover procedures are used, then network coverage is maintained, but latency increases and communication efficiency decreases under load
Solution Approach 1:
The patent performs preliminary evaluation of candidate RATs and networks before handover is actually needed. By pre-assessing QoS capabilities, network load conditions, and compatibility with service requirements, the system prepares optimal handover targets in advance, reducing actual handover latency and maintaining coverage continuity without time-consuming evaluation during critical handover moments.
3Productivity
If multi-RAT selection is implemented with multiple evaluation criteria, then network performance improves, but system complexity increases
Solution Approach 1:
The patent segments the RAT selection process into distinct modular evaluation stages: QoS requirement analysis, candidate network identification, multi-criteria scoring, and final selection. Each stage handles specific evaluation aspects independently, making the complex multi-criteria system more manageable and implementable while maintaining high network efficiency through systematic evaluation.
4Adaptability or versatility
If frequent handover occurs in multi-RAT scenarios, then network flexibility is maintained, but average throughput decreases and communication stability is affected
Solution Approach 1:
The patent introduces an intermediary evaluation layer that acts as a mediator between multiple RAT options and the final selection decision. This intermediary systematically evaluates QoS matching, network load, and service requirements to determine whether a handover is truly necessary, preventing unnecessary handovers that would reduce communication stability while maintaining network flexibility for genuinely beneficial transitions.
Data Source
AI summary
A method of selection and/or handover for multi radio access technologies in a 5G cellular network. The method includes: 1) collecting, by a user terminal, load information of a candidate Access Point (AP) or an Evolved Node (H)eNB via a local entity of Access Network Discovery and Selection Function (L-ANDSF); 2) checking, by the user terminal, a Received Signal Strength (RSS) value of the candidate AP or (H)eNB, a Reference Signal Received Quality (RSRQ) and a Service Sensitivity to Latency; 3) based on the above information, evaluating suitability of an available radio access technology; 4) triggering, by a specific triggering event, a fuzzy logic controller, to select a most appropriate radio access technology for each session; and 5) establishing a new session to perform admission control or handover.