Resource Scheduling for Sparse Non-Orthogonal Wireless Transmissions
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Solution Overview
Problem
Existing wireless communication systems face challenges in efficiently scheduling resources for sparse non-orthogonal transmissions, particularly in managing receiver signal to noise ratio (SNR) for optimal resource allocation.
Innovation Solution
The described techniques involve considering receiver SNR, pathloss, and uplink transmission power to schedule resources for sparse non-orthogonal multiple access (NOMA) in wireless communications. This includes transmitting scheduling information to user equipment (UE) that indicates resource assignment vectors and codes for uplink communications, and similarly for multilayer transmissions between devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If resources are allocated without considering receiver SNR, then the scheduling process is simpler, but spectral efficiency deteriorates
Solution Approach 1:
The patent changes the scheduling parameters from uniform resource allocation to SNR-based differentiated allocation. The network entity calculates receiver SNR for each UE based on pathloss and transmission power, then uses these SNR values to determine optimal resource assignment vectors and repetition codes, transforming the scheduling process into an SNR-optimized system that achieves higher spectral efficiency.
Solution Approach 2:
The patent implements a feedback mechanism where UEs transmit pathloss values and uplink power information to the network entity. The network entity uses this feedback to calculate receiver SNR for each UE and generates scheduling information (resource assignment vectors and repetition codes) based on these SNR calculations, enabling adaptive resource allocation that improves spectral efficiency while managing complexity through structured feedback loops.
2Reliability
If pathloss and transmission power are considered for scheduling, then resource allocation optimality improves, but measurement and computation requirements increase
Solution Approach 1:
The patent applies self-service by having UEs autonomously measure and report their own pathloss values and uplink transmission power to the network entity. This eliminates the need for complex centralized measurement systems, as each UE uses its own transmission parameters and channel conditions to provide scheduling information, thereby improving resource allocation optimality while keeping measurement complexity manageable through distributed self-measurement.
3Reliability
If more orthogonal resources are assigned per UE, then transmission reliability improves, but system capacity deteriorates
Solution Approach 1:
The patent applies local quality by assigning different numbers of orthogonal resources to different UEs based on their individual receiver SNR values. UEs with higher receiver SNR (better channel conditions) are allocated fewer resources, while UEs with lower receiver SNR are allocated more resources. This differentiated local allocation optimizes the trade-off between transmission reliability for each user and overall system capacity, preventing uniform resource allocation from bottlenecking system performance.
Data Source
AI summary
Methods, systems, and devices for wireless communications are described. Receiver signal to noise ratio (SNR) (e.g., pathloss and transmission power) may be considered for scheduling of resources for sparse non-orthogonal transmissions. For example, for uplink multi-user scheduling, the network may consider the pathloss and uplink transmission power of each user equipment (UE) (e.g., the receiver SNR) when assigning resources for sparse non-orthogonal multiple access (NOMA) to each UE. As another example, for multilayer transmissions between two devices (e.g., either uplink or downlink), the transmitting device may identify and consider the receiver SNR for each transmission layer when assigning resources for a multi-layer transmission between the two devices.