Wi-Fi Spatial Frequency Reuse with Reinforcement Learning
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Solution Overview
Problem
The IEEE 802.11ax standard creates a tradeoff between channel contention time and frame transmission duration due to adjustments in OBSS PD level and MCS index, necessitating a balanced approach to improve spatial frequency reuse in wireless communication.
Innovation Solution
A system and method utilizing reinforcement learning (RL) to jointly adjust OBSS PD level and MCS index, optimizing parameters like learning rate, discount rate, and ∈-greedy parameter to minimize total transmission time for successful frame delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the OBSS PD level is increased to reduce channel contention time, then channel access speed improves, but frame transmission duration increases due to lower MCS index
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the OBSS PD level and MCS index based on channel conditions and network environment. Instead of using fixed values, the system modifies these parameters adaptively to optimize the tradeoff between channel contention time and frame transmission duration, resolving the technical contradiction through flexible parameter tuning.
2Productivity
If the OBSS PD level is increased to allow simultaneous channel access, then spatial frequency reuse improves, but transmit power must be decreased
Solution Approach 1:
The patent implements dynamics by making the OBSS PD level and transmit power level adjustable and adaptive rather than fixed. The system dynamically modifies these parameters based on real-time channel conditions, network density, and traffic requirements, enabling the network to optimize spatial frequency reuse while managing transmit power constraints through continuous adaptation.
Data Source
AI summary
The disclosed wireless communication systems and methods for i) determining that a protocol data unit (PDU) is ready for a transmission by a Wi-Fi apparatus; ii) determining a current environment state associated with the Wi-Fi apparatus; iii) based on the current environment state, selecting an action from a set of actions in accordance with a reinforcement learning (RL) technique configured to select the action suitable according to the current environment state; and iv) based on the selected action, transmitting the PDU.