Wireless Relay Network Communications Schedule Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing wireless relay networks face challenges in efficiently determining communications schedules that optimize data routing between relay nodes, particularly in ensuring reliable communication over large distances and varying conditions, due to varying capacity requirements and interference issues.
Innovation Solution
A method and system for determining a communications schedule that generates candidate connectivity patterns and resource allocations, evaluates performance characteristics, and selects optimal combinations to interconnect relay nodes using a weighted resource block allocation, allowing for adaptive reconfiguration in response to changes in load and conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If a multi-hop nearest neighbour relaying approach is used to transmit data over larger distances, then the communication distance is improved, but the capacity required by the communications links varies significantly making it difficult to provide reliable communication
Solution Approach 1:
The patent implements dynamic connectivity patterns that allow relay nodes to adapt their communication paths and resource allocations based on varying traffic demands and channel conditions. The system generates multiple candidate connectivity patterns and selects optimal configurations in real-time, enabling the network to maintain reliable communication across varying distances by dynamically adjusting the number of hops and resource distribution.
Solution Approach 2:
The system changes key parameters including connectivity patterns, resource block allocations, and power levels to optimize communication reliability. By evaluating multiple candidate configurations and selecting those that meet desired performance characteristics, the system adapts parameter settings to maintain reliable communication regardless of distance variations in the multi-hop relay network.
2Productivity
If the first wireless communications link between a transmitting node and the nearest relay node is provided with high capacity to carry all communications traffic, then the data throughput is improved, but it becomes very difficult to provide the required capacity over such a communications link
Solution Approach 1:
The patent segments the communication traffic by distributing it across multiple parallel relay paths instead of concentrating all traffic through a single nearest relay node. By generating multiple candidate connectivity patterns and utilizing multiple relay nodes simultaneously, the system divides the total traffic load into smaller segments that can be handled by individual links with moderate capacity requirements, reducing the complexity of providing high capacity on any single link.
Solution Approach 2:
The system implements multi-functionality by enabling relay nodes to serve multiple purposes: they can act as intermediate relays for distant communications, direct recipients for local communications, and flexible participants in different connectivity patterns. This universal role assignment allows traffic to be distributed across multiple nodes that can dynamically switch between different functional roles, reducing the burden on any single communication link.
3Productivity
If candidate connectivity patterns and resource allocations are evaluated and selected to optimize performance, then the communication efficiency is improved, but the computational complexity increases
Solution Approach 1:
The patent applies partial action by evaluating a limited set of pre-generated candidate connectivity patterns and resource allocations rather than exhaustively searching all possible configurations. The system generates a manageable number of candidate patterns that are most likely to be optimal, then selects from these candidates based on performance characteristics. This approach achieves good optimization without the computational burden of exhaustive search.
Solution Approach 2:
The system performs preliminary action by pre-generating candidate connectivity patterns and resource allocations before actual data transmission begins. These candidate configurations are prepared in advance and stored, allowing the network to quickly select from pre-evaluated options rather than performing complex optimization calculations in real-time during data transmission, thus reducing computational complexity while maintaining efficiency.
Data Source
AI summary
A communications schedule routes data between relay nodes forming a wireless relay network and interconnects relay nodes by an ordered sequence of communications links established over a wireless resource comprising resource blocks. Candidate connectivity patterns for the ordered sequence of communications links and candidate resource allocations are provided. For each candidate connectivity pattern, a level of a performance characteristic is calculated for a selected combination of the candidate resource allocations. Based on a desired level of the performance characteristic, a candidate connectivity pattern and associated selected combination of candidate resource allocations whose calculated level of the performance characteristic meets the desired level, is selected as the communications schedule. In response to a trigger condition, the performance level evaluation process and the selection process are repeated to re-select one of the candidate connectivity patterns and its associated selected combination of candidate resource allocations to be used as the communications schedule.