This video presents a summarized (5-minute long) description of the Handover optimization scheme for 5G Wireless Networks. This video was submitted for the Malaysia Technology Expo 2024 (MTE2024) International Innovation Awards (IIA) held
Summary of Innovation.
5G wireless networks offer higher data rates and lower latency compared to 4G, primarily due to the use of higher frequency bands. However, higher frequencies result in the shortening of cell coverage, leading to small cell networks. Small cells introduce frequent handovers from one 5G base station (BS) to another when users travel in the service area, resulting in high occurrences of ping-pong handovers and handover failures. Consequently, leading to frequent interruptions in network sessions, degradation of quality of service (QoS), wastage of network resources, and increased device power consumption.
Highlights of Innovation's Important Features (500 words)
The invention pertains to wireless communications between User Equipment (UE) and Base Stations (BSs). The novelty of the invention lies in the automatic optimization of handover control parameters (HCPs) that are used to determine whether the UE should perform a handover to another cell. The objective is to minimize unnecessary handovers, ping-pong effects, and handover failures for users in 5G networks. To achieve this, we propose a novel handover algorithm comprising the following steps:
Step 1: The UE receives parameters related to channel quality (RSRP/SINR), user mobility (speed, direction, and location), and BS configuration (SMTC, MGRP, Qrxlevmin, handover events, etc.). The UE receives the BS configurations through system information transmitted periodically by the BSs. The UE operates in different RRC modes, namely RRC idle, RRC inactive, or RRC connected. In RRC-connected and inactive mode, the UE receives the BS configurations through RRC configuration messages.
Step 2: The UE classifies the received parameters of channel quality and BS configuration based on serving BS and target BS(s). The BSs in a wireless system may differ in terms of transmitting power, bandwidth, SMTC/MGRP periodicity, etc. This classification enables the optimization of HCPs for each BS to be optimized individually, making the present invention independent of the type and technology of the BS.
Step 3: The UE identifies the handover event(s) that will be used to perform handover measurement. The UE receives the handover event(s) via RRC configuration messages (step 1). The UE classifies the handover event(s) as either serving BS-based events, target BS-based events, or both serving and target BS-based events depending on the parameters used in the event. The handover event uses channel quality parameters and HCPs of either the target BS, serving BS, or both, to perform handover measurements. Examples of handover events are defined in the 3GPP RRC protocol for 5G, including Events A1 to A6. Based on parameters used to define these events, they can be classified as either serving BS-based events, target BS-based events, or both serving and target BS-based events.
Step 4: The UE determines the optimal values of the HCPs, namely Threshold, Hysteresis, Time-To-Trigger, and Traverse-Time, using novel tractable analytical models that we have formulated for each HCP (the models have been published in the IEEE Access journal accessible via https://doi.org/10.1109/ACCESS.2023.3346039 ).
Step 5: The UE applies the optimum value of at least one HCP to perform handover measurement using the handover event(s) identified in Step 1.
Step 6: Finally, the UE reports the handover event to the serving BS in a Measurement Report (MR) for the network to perform the handover to the best target BS.
Usefulness and potential of this invention: Seamless handover and data transmission in a fast-moving scenario are crucial, especially with the latest wireless technologies. The proposed innovation has significantly minimized unnecessary handovers and handover failures compared to existing approaches, providing a seamless handover experience that allows users to stay connected when traveling from one location to another. This innovation can be used in telemedicine/smart ambulances, IoT drones, and autonomous cars.
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