Adaptive Uplink Transmission Scheduling for Co-Channel Interference
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Solution Overview
Problem
Wireless communication systems with high subscriber densities are interference-limited, leading to reduced network capacity due to co-channel interference, which affects the carrier-to-interference ratio (CIR) and connection quality.
Innovation Solution
Implementing a communication system where participants transmit data based on quality criteria, using different frequency ranges and time intervals, and adjusting code rates and hopping patterns to improve transmission success in poor reception conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If participants transmit data in the same frequency band simultaneously, then network capacity increases, but co-channel interference increases leading to reduced carrier-to-interference ratio
Solution Approach 1:
The frequency band is segmented into multiple sub-bands, and participants are divided into different groups that transmit in different frequency ranges. This segmentation reduces co-channel interference by ensuring that not all participants transmit simultaneously on the same frequency, while still maintaining high network capacity through parallel transmissions across different frequency segments.
Solution Approach 2:
The system employs periodic time intervals for data transmission, where participants transmit during specific time slots rather than continuously. This periodic action allows multiple participants to share the frequency band without constant interference, as transmissions are staggered over time while maintaining overall network capacity.
2Device complexity
If participants with poor reception conditions use the same transmission parameters, then system simplicity is maintained, but transmission success probability decreases
Solution Approach 1:
The system applies different transmission parameters to different groups of participants based on their local reception conditions. Participants with poor reception are assigned specific frequency ranges and time intervals that optimize their transmission success, while participants with good reception use different parameters. This local differentiation improves reliability without requiring complex centralized control.
Solution Approach 2:
Each participant autonomously determines its own transmission parameters based on its reception conditions and the assigned frequency/time resources. Participants self-select appropriate transmission parameters from predefined configurations, eliminating the need for complex centralized management while ensuring optimal transmission success for each user's specific conditions.
3Object-affected harmful factors
If frequency hopping patterns are used for all participants, then interference is reduced, but participants with poor reception still struggle to achieve sufficient carrier-to-interference ratio
Solution Approach 1:
Different frequency hopping patterns are assigned to different groups of participants based on their reception conditions. Participants with poor reception receive specific hopping patterns that prioritize frequencies with lower interference, while participants with good reception use different patterns. This localized approach to frequency hopping improves the carrier-to-interference ratio for vulnerable participants while maintaining overall interference reduction.
Data Source
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AI summary
Embodiments relate to a subscriber of a communication system, wherein the subscriber is configured to transmit data to a base station of the communication system. On the basis of a quality criterion of at least one previous transmission between the subscriber and the base station, the subscriber is configured to transmit the data in a first frequency range or in a second frequency range, said first frequency range and second frequency range differing, and/or to transmit the data in a first time interval or in a second time interval, said first time interval and second time interval differing.