Dynamic MCS Selection for Wireless Throughput Optimization
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Solution Overview
Problem
Current wireless packet transmission systems, such as those following the 802.11 standards, face challenges in maximizing throughput due to interference and channel conditions, leading to suboptimal modulation and coding rate selection, which can result in reduced data rates and increased collisions.
Innovation Solution
A modulation and coding selection (MCS) algorithm that characterizes channel and collision conditions to dynamically select the highest available MCS when interference or collisions are present, and adjusts based on signal-to-noise ratio (SNR) and packet error rate (PER) metrics to optimize throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a higher MCS is selected to maximize throughput, then data transmission rate is improved, but packet loss increases due to interference and channel errors
Solution Approach 1:
The patent implements dynamic MCS selection by continuously monitoring channel conditions, interference levels, and packet error rates, then adjusting the MCS accordingly. The system transitions from static MCS selection to adaptive dynamic selection that responds to real-time channel variations, allowing optimal balance between throughput and reliability under changing conditions
Solution Approach 2:
The system changes multiple parameters simultaneously including MCS level, packet size, and transmission power based on detected channel conditions. By adjusting these parameters in combination rather than singly, the system optimizes both throughput and packet loss performance across varying channel quality levels
2Reliability
If a lower MCS is selected to reduce packet loss, then reliability is improved, but data transmission rate decreases
Solution Approach 1:
The patent employs feedback mechanisms where the receiver sends acknowledgments and error reports to the transmitter, enabling the system to learn from transmission outcomes. This feedback loop allows the system to identify the optimal MCS that achieves sufficient reliability while maximizing throughput, rather than conservatively selecting lower MCS values
3Productivity
If packet size is increased to improve throughput, then data transmission efficiency is improved, but collision probability increases in high utilization networks
Solution Approach 1:
The system dynamically adjusts packet size based on detected network utilization levels and collision rates. When collisions are detected or network utilization is high, the system reduces packet size to minimize collision impact. When conditions are favorable, it increases packet size to maximize throughput efficiency
Data Source
AI summary
A method for selection of a particular modulation coding selection (MCS) from a plurality of available MCS selects a particular MCS after obtaining SNR_d, SNR_high, SNR_low, and if SNR_d>SNR_high, selecting the highest available MCS, and if SNR_d<SNR_low, selecting the lowest MCS, and if SNR_high>SNR_d>SNR_low, selecting MCS based on computing the function/table for each MCS according to the formula:f(MCS)=(1−PER(length_packet,MCS,SNR_d))/length_packet(packet_size,MCS),and thereafter selecting the MCS that maximizes the f(MCS) function. Further the neighboring MCS values are characterized for throughput in a throughput characterization step, and compared in throughput to the above determined throughput. In an embodiment of the invention, SNR_high, SNR_low are found by finding the SNR that satisfies:PER(length_packet,MCS_lowest,SNR_low)=PER_threshPER(length_packet,MCS_highest,SNR_high)=PER_threshWhere PER_thresh is a design parameter, and MCS_lowest is the lowest MCS and MCS_highest is the highest available MCS.