Coordinated Power-Zone Assignment in Wireless Backhaul
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Solution Overview
Problem
Existing wireless backhaul networks face inefficiencies in resource scheduling due to uncoordinated power-zone assignments, which fail to maximize network utility and do not guarantee optimal solutions, especially in interference-limited environments.
Innovation Solution
The implementation of coordinated power-zone assignment methods, such as Auction-Based Power-Zone Assignment (AB-PZA) and Clustering-and-Exhaustive-Search Power-Zone-Assignment (CES-PZA), which optimize network utility by assigning Remote Backhaul Modules (RBMs) to power-zones on a one-to-one basis, leveraging Soft Frequency Reuse techniques and auction approaches for distributed and asynchronous implementation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If uncoordinated power-zone assignment is used per hub basis, then device complexity is reduced, but network utility maximization and interference mitigation are compromised
Solution Approach 1:
The network is segmented into multiple hubs, each independently performing power-zone assignment based on local channel state information. This segmentation allows distributed decision-making that reduces coordination complexity while maintaining network utility through localized optimization.
Solution Approach 2:
The system changes parameters dynamically by adjusting power allocation across different zones based on real-time channel conditions. Each hub independently modifies its power-zone assignment parameters to maximize network utility without requiring complex inter-hub coordination.
2Ease of manufacture
If conventional proportional fair scheduling is used, then implementation simplicity is improved, but optimal solution guarantee and one-to-one mapping constraint are not satisfied
Solution Approach 1:
The system performs preliminary power-zone assignment based on channel state information before actual data transmission. This preliminary optimization ensures that the assignment satisfies one-to-one mapping constraints and achieves optimal solution guarantees while maintaining implementation simplicity.
Solution Approach 2:
The system uses channel state information feedback to continuously optimize power-zone assignments. Each hub receives feedback about channel conditions and adjusts its power-zone assignment accordingly, ensuring optimal solutions are achieved while keeping the implementation straightforward.
3Productivity
If coordinated power-zone assignment is implemented across the network, then network utility and interference mitigation are improved, but computational complexity increases
Solution Approach 1:
Each hub independently performs power-zone assignment by serving itself based on local channel state information. This self-service approach achieves coordinated optimization across the network without requiring complex inter-hub coordination mechanisms, thus improving network utility while limiting computational complexity increases.
4Speed
If per-hub independent scheduling is used, then implementation speed is improved, but interference management and network-wide optimization are compromised
Solution Approach 1:
Each hub independently changes power allocation parameters based on real-time channel state information, enabling fast scheduling decisions. This parameter-based approach allows rapid adaptation to changing conditions while managing interference through localized power control without requiring slow centralized coordination.
Data Source
AI summary
Methods are disclosed for scheduling resources in a wireless backhaul network comprising a plurality of N Hubs, each Hub serving a plurality of K Remote Backhaul Modules (RBMs), using a coordinated power zone assignment across the backhaul network. For each Hub, a one-to-one power zone assignment, of each of the K RBM to one of the K power zones, is computed by maximizing a selected network utility across the backhaul network. Coordinated power zone assignment according to preferred embodiments based on the auction approach offers a close-to-global-optimal solution. Coordinated scheduling based on first assigning RBMs to hubs heuristically, and then optimally scheduling RBMs within each hub also offers significant performance improvement as compared to non-coordinated systems. Preferred embodiments offer a significant performance improvement as compared to conventional systems. They are low in complexity, and compatible with the physical constraints of SFR-based wireless backhaul network, which make them amenable to practical implementation.


