Base Station Beamforming Allocation Using ECN Congestion Signals
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Solution Overview
Problem
Existing wireless network communication systems face challenges with excessive traffic congestion leading to latency, buffer bloat, and packet loss, particularly impacting time-critical applications like VoIP, videoconferencing, and augmented/virtual reality, where conventional congestion detection methods are inadequate.
Innovation Solution
Implementing beamforming resource allocation in wireless networks based on Explicit Congestion Notification (ECN) data to dynamically switch between SRS and codebook beamforming techniques, optimizing resource distribution and anticipating congestion using AI models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional congestion detection methods (packet loss, latency monitoring) are used, then network congestion can be detected, but time-critical applications experience excessive latency and packet loss
Solution Approach 1:
The patent applies preliminary action by using ECN markers to signal congestion before buffer overflow occurs. Instead of waiting for packet loss to detect congestion, the network proactively marks packets with ECN bits when queue depth exceeds a threshold, allowing senders to reduce transmission rates before actual congestion and packet loss occur. This preventive approach maintains reliability while avoiding the latency associated with reactive congestion detection.
2Adaptability or versatility
If beamforming resources are allocated dynamically based on ECN data, then network adaptability to congestion improves, but system complexity increases
Solution Approach 1:
The patent implements feedback by continuously monitoring ECN marker rates in incoming traffic and using this information to dynamically adjust beamforming resource allocation. The base station measures the ECN marker rate, compares it against thresholds, and automatically switches between SRS and codebook beamforming modes accordingly. This closed-loop feedback mechanism enables the system to adapt to changing congestion conditions without requiring complex manual configuration or prediction algorithms.
3Reliability
If SRS beamforming is used for all UEs, then beamforming performance is optimized, but resource consumption increases during congestion
Solution Approach 1:
The patent applies dynamics by making beamforming resource allocation adaptive rather than static. The system dynamically switches between SRS beamforming (resource-intensive but high performance) and codebook beamforming (resource-efficient but lower performance) based on real-time ECN congestion indicators. During low congestion, SRS beamforming provides optimal performance; during high congestion, the system transitions to codebook beamforming to conserve resources, creating a dynamic allocation strategy that balances performance and efficiency.
Data Source
AI summary
Systems, methods, and software are disclosed herein for allocating beamforming resources of a base station of a wireless communication network based on congestion notification which includes detecting Explicit Congestion Notification (ECN) data of data traffic of user equipment (UEs) in communication with a base station; determining that the ECN data comprising a congestion notification exceeds a threshold value; and determining an allocation of beamforming resources of the base station among the UEs based on determining that the ECN data comprising a congestion notification exceeding the threshold value.