Base Station Clustering for Wireless Network Scheduling
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Solution Overview
Problem
In heterogeneous wireless networks, the existing technologies face challenges in efficiently managing packet scheduling between different networks, leading to contention on uplink channels and delays, which affects the quality of service (QoS) in wireless local area networks (WLANs).
Innovation Solution
A base station with a transceiver and processor that estimates the mean arrival rate of data from user equipment (UEs) and divides them into clusters, reducing contention by notifying each UE of its cluster size and identification, allowing coordinated data transmission through the LTE and WiFi networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If user equipments transmit data through the first wireless network without clustering, then the transmission process is simple, but contention on the uplink channel increases leading to longer transmission delays
Solution Approach 1:
The patent segments the user equipments into multiple clusters based on their data transmission characteristics and mean arrival rates. Each cluster is assigned specific time-frequency resources for uplink transmission, which reduces contention and collision on the shared channel. This segmentation approach directly addresses the transmission delay issue by organizing UEs into manageable groups that can be scheduled more efficiently.
Solution Approach 2:
The base station performs preliminary clustering of user equipments before the actual data transmission occurs. By pre-calculating cluster assignments based on mean arrival rates and transmission patterns, the system prepares the scheduling structure in advance, avoiding the need for complex real-time scheduling decisions and reducing overall transmission delay.
2Productivity
If the base station clusters user equipments to reduce contention, then transmission delay decreases, but the base station's processing complexity increases
Solution Approach 1:
The patent changes the parameter of cluster size dynamically based on the mean arrival rate of data from user equipments. When the arrival rate is high, larger clusters are formed to maximize resource utilization; when the arrival rate is low, smaller clusters are formed to reduce processing overhead. This parameter adaptation allows the system to optimize data throughput while controlling base station processing complexity.
Solution Approach 2:
The base station applies clustering selectively to user equipments that benefit most from it, rather than clustering all UEs uniformly. By identifying and clustering only those UEs with significant contention issues or high data arrival rates, the system achieves improved throughput for critical users while minimizing the overall processing complexity burden on the base station.
3Quantity of substance
If heterogeneous networks are integrated for bandwidth aggregation, then network capacity increases, but packet scheduling between networks becomes complex
Solution Approach 1:
The patent introduces cluster-based scheduling as an intermediary layer between the heterogeneous networks (LTE and WiFi). Instead of directly managing packet scheduling across multiple networks, the system first groups UEs into clusters and assigns each cluster to specific networks or time slots. This intermediary clustering mechanism simplifies the overall scheduling complexity while maintaining the bandwidth aggregation benefits of heterogeneous network integration.
Data Source
AI summary
A scheduling method for wireless network is provided. The scheduling method is executed by a base station and includes the steps of estimating a mean arrival rate of data to be transmitted through a first wireless network by a plurality of user equipments (UEs) through a second wireless network when the UEs are connected to the base station and in need of transmitting data through the first wireless network, determining a cluster size and dividing the UEs into a plurality of clusters according to the mean arrival rate, and notifying each UE the number of the clusters and the identification (ID) of the cluster accommodating the UE through the second wireless network. The number of the UEs in each cluster is not greater than the cluster size.