MCE Cluster Management for V2X MBMS Downlink Capacity
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Solution Overview
Problem
Current MBMS/SC-PTM procedures in LTE-based V2X communication systems face challenges in meeting DL capacity requirements for V2V services, particularly in coordinating efficient resource allocation and scheduling for effective broadcast and multicast transmissions.
Innovation Solution
The method involves determining and updating a cluster of cells for V2X message transmission based on feedback information from eNodeBs, using a multi-cell/multicast coordination entity (MCE) to optimize resource allocation and scheduling, enabling dynamic and semi-static scheduling of MBMS/SC-PTM procedures across multiple transmission points (TPs) for enhanced capacity and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If MBMS/SC-PTM procedures are used for V2X communication, then service quality and coverage are improved, but downlink capacity requirements for V2V services are not met
Solution Approach 1:
The system segments the coverage area into multiple clusters, where each cluster is served by a specific eNodeB. This segmentation allows distributed resource allocation across multiple base stations, increasing overall downlink capacity while maintaining service quality through localized optimization of broadcast and multicast transmissions.
Solution Approach 2:
The patent introduces a new dimension of cluster-based resource allocation in the network architecture. By organizing eNodeBs into clusters and assigning specific V2X service areas to each cluster, the system adds a spatial dimension to resource management, enabling scalable capacity expansion without compromising service quality.
2Ease of operation
If resource allocation is centralized for MBMS/SC-PTM, then coordination efficiency is improved, but system complexity increases
Solution Approach 1:
The patent segments the centralized coordination function into distributed cluster-level decisions. Each eNodeB autonomously manages resources within its assigned cluster, eliminating the need for complex centralized coordination while maintaining efficiency through localized resource allocation and reduced signaling overhead.
Solution Approach 2:
The system enables self-service by allowing each eNodeB to autonomously allocate resources within its cluster without requiring complex centralized control. This self-organizing approach reduces system complexity while maintaining coordination efficiency through distributed intelligence and localized decision-making.
Data Source
AI summary
A multi-cell/multicast coordination entity (MCE) determines a cluster to which a vehicle-to-everything (V2X) message. The MCE receives a first session start message, which includes a temporary mobile group identity (TMGI), quality of services (QoS) parameters, and a list of cells, from a V2X application server and determines a cluster, which contains group of cells, to which V2X message is to be broadcast, based on the received TMGI, QoS parameters, and list of cells. Upon determining the cluster, the MCE transmits a second session start message, which includes an indication to notify eNodeB (eNB) to wait for scheduling information, to eNBs corresponding to the determined cluster, and transmits MBMS scheduling information to the eNBs. Further, update of the cluster may be triggered from the V2X application server or from the eNB with limited feedback.