Distributed Resource Allocation for Heterogeneous Wireless Networks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current load balancing techniques in Massive MIMO wireless networks face challenges in efficiently distributing user rates due to their dependence on large-scale signal-to-interference plus noise ratio and channel realization, and require significant computational resources from centralized controllers, which limits their scalability and flexibility.
Innovation Solution
A method and apparatus for resource allocation and scheduling that allocates resources across clusters of base stations, allowing user terminals to be served by their preferred clusters, using distributed MIMO transmission, which does not require channel state information exchange between base stations, enabling efficient load balancing and scheduling across multi-tier wireless networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized controller is used to perform load balancing and scheduling, then load balancing performance is improved, but computational burden increases
Solution Approach 1:
The centralized controller functionality is segmented into distributed base station units, where each base station independently performs load balancing and scheduling decisions. This segmentation reduces the computational burden on any single controller while maintaining overall system performance through distributed intelligence.
Solution Approach 2:
A standardized interface mechanism is introduced as an intermediary between base stations and the central network controller. This interface enables efficient information exchange and coordination without requiring the central controller to perform all computational tasks, thus reducing its burden while maintaining system-wide optimization.
2Ease of manufacture
If traditional PHY layer approaches are used where one BS serves at most one user, then implementation simplicity is maintained, but throughput gains are limited
Solution Approach 1:
Multiple base stations are merged to serve a single user terminal simultaneously through coordinated multipoint (CoMP) transmission. This merging enables spatial diversity and multiplexing gains, significantly increasing throughput while the standardized interface maintains implementation simplicity by abstracting the complexity of multi-BS coordination.
Solution Approach 2:
The base station interface and resource allocation mechanism are designed to be universal, supporting both traditional single-BS serving mode and multi-BS CoMP mode. This multi-functionality allows the system to achieve high throughput gains when conditions permit while maintaining simplicity in standard operating scenarios.
3Productivity
If user rates depend on scheduling set and channel realization, then transmission efficiency is improved, but load balancing becomes more complex
Solution Approach 1:
A feedback mechanism is implemented where user terminal measurements of channel quality and transmission performance are reported to base stations. This feedback enables dynamic adjustment of scheduling decisions and load balancing configurations, allowing the system to optimize transmission efficiency while the standardized interface simplifies the complexity of real-time adaptations.
Data Source
AI summary
A method and apparatus is disclosed herein for resource allocation in a wireless communication system are disclosed. In one embodiment, the method comprises allocating portions of the resources available to a subset of base stations of the plurality of base stations to serve a subset of UTs from clusters of base stations with cluster sizes including at least one with two or more base stations, where each of the portions of resources are allocated to serve one UT via a user-dependent cluster of base stations; and scheduling UT transmissions over the subset of base stations and scheduling slots, wherein within each of the scheduling slots one or more user terminals are scheduled for transmission, each by its user-dependent cluster of base stations.