LTE網路中機械通訊下的動態資源分配

Abstract

隨著物聯網的蓬勃發展，未來機械通訊的裝置數量將會大增。在無線網路系統LTE 中，原先的設計是以服務手機用戶為考量，因而把大量的資源規劃給資料資源，僅有少量的資源提供給控制資源；然而在機械通訊中，僅需要少量的資料資源，若大量的機械裝置有連線需求會造成目前LTE 系統控制資源不足，而導致後續的連線無法順利完成。在這篇論文中，為了解決控制資源不足的問題並提高LTE的連線效能，我們提出了兩個不同的情境做分析，第一個為通道間的動態資源分配系統，先運算出裝置連線所需的資源量，再透過連線裝置數量的估計方法，來適當的分配控制資源與資料資源，能達到穩定的成功率下並使資源能夠有效分配，另一個為考慮機械通訊與人對人通訊共存情形下的賽局理論分析，透過拍賣競標資源的方式，也能達到同樣的效益。在這兩個方法中我們都透過模擬方式驗證理論，並和標準文件中的解決方案做比較，驗證它的可行性。

According to the estimation, Machine-to-Machine(M2M) devices in the Internet of Things(IoT) would be boosted in the near future. LTE system is originally designed for human to human(H2H) communications. The most of radio resource is allocated to data channels but rarely less to control channels. Comparing M2M traffic with H2H traffic, M2M devices only have lightweight uplink packet to report their data. When numerous devices access the network, there are huge amount of the controlling signals would be sent. The overhead of control packets would be too high for the system to maintain the service when massive M2M device access the network. To resolve the problem and improve the performance of LTE system, two scenarios are analyzed. One is a inter-channel dynamic resource allocation scheme designed for massive devices. First, we calculate the resource requirement for each device and estimate the traffic of random access attempts, then allocate data resource and control resource properly in pursuit of high success transmission probability. The other is a game theoretic analysis to a hybrid scenario. We evaluate the performance and find that our proposed scheme in both scenario has better performance in terms of success probability and resource efficiency.