Reinforcement Learning Load Balancing in 6G Wireless Networks
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Solution Overview
Problem
Current wireless communication systems face challenges in efficiently managing handover processes in 6G networks, particularly in balancing load distribution across base stations to maintain high data rates and low latency, especially in the terahertz band where signal coverage and spectral efficiency are critical.
Innovation Solution
A reinforcement learning apparatus is introduced to determine priority information for handover procedures based on the number of user equipment (UEs) connected to each base station, utilizing transceivers, memory, and processors to receive and transmit data on UE distribution, handover information, and data throughput, enabling optimized load balancing across the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the number of connected devices increases in 6G networks, then network coverage and connectivity are improved, but load distribution across base stations becomes unbalanced
Solution Approach 1:
The patent implements a feedback mechanism where the reinforcement learning apparatus continuously receives information about the number of connected UEs and data throughput from multiple base stations, processes this information to determine priority information, and feeds it back to base stations for handover decisions. This closed-loop feedback system enables dynamic load balancing that adapts to changing network conditions, resolving the contradiction between increasing device connectivity and maintaining balanced load distribution.
Solution Approach 2:
The system employs reinforcement learning algorithms that enable the network to automatically self-optimize load distribution without manual intervention. The apparatus autonomously learns optimal handover policies by processing network state information and generating priority information based on the number of connected UEs and throughput metrics, allowing the network to self-adjust to varying device densities and traffic patterns.
2Speed
If handover procedures are optimized for speed, then data rate is improved, but load balancing between base stations deteriorates
Solution Approach 1:
The patent implements preliminary action by pre-calculating and transmitting priority information to base stations before handover decisions are made. The reinforcement learning apparatus processes network state information in advance, determines optimal handover priorities based on the number of connected UEs and data throughput, and prepares this information for rapid deployment when handover conditions arise, enabling both fast handover and load balancing.
Solution Approach 2:
The system dynamically adjusts handover priorities based on real-time network conditions. The reinforcement learning apparatus continuously monitors the number of connected UEs and data throughput, adapting priority information to current load conditions. This dynamic approach allows the system to optimize for speed when appropriate while simultaneously maintaining load balance, resolving the contradiction between these two objectives.
3Measurement precision
If reinforcement learning apparatus processes more handover information, then load balancing accuracy is improved, but system complexity increases
Solution Approach 1:
The patent extracts and processes only the most critical information elements needed for load balancing: the number of connected UEs and data throughput metrics. By focusing on these key parameters rather than processing all possible handover information, the reinforcement learning apparatus achieves accurate load balancing while maintaining manageable system complexity. This selective information extraction resolves the contradiction between precision and complexity.
Data Source
AI summary
A 5th generation (5G) or 6th generation (6G) communication system for supporting higher data rates, compared to that of a 4th generation (4G) communication system such as a long term evolution (LTE) communication system are provided. An apparatus and a method for load balancing in a wireless communication system are provided. The apparatus includes a transceiver, a memory storing one or more instructions, and at least one processor configured to execute the one or more instructions stored in the memory to receive first information about a relation between a base station (BS) and a user equipment (UE) from each of a plurality of BSs, determine, based on the first information, a number of UEs on which handover has to be performed from among UEs served by each of the plurality of BSs, and transmit, to each of the plurality of BSs, priority information determined based on the number of UEs.