To efficiently support and manage massive number of Internet of Things (IoT) short and bursty sessions, current long-term evolution (LTE) system needs to reduce signal load generated by IoT session setup/synchronization, while balancing the system performance, such as UE power consumption and delays to time-sensitive traffic. In LTE, radio resource control (RRC) and discontinuous reception (DRX) affect power consumption, signal load, and delay. We provide a session management methodology suitable for IoT traffic over LTE. Our analysis starts with a Markov chain analysis of the impact of DRX parameters. This is followed by an optimal uplink scheduler design and an IoT-aware adaptive DRX algorithm at the client, both of which modulate the tradeoff among signal load, delay, and power consumption. Scalability is also considered by providing a high-priority clustering-based adaptive DRX algorithm at eNB. Simulation results show that for packets with 0.1 s delay, our scheduler outperforms 'Tx now' (and 'Wait Till Deadline') by 50% (and 30%) in power saving and by 60% (and 15%) in signal saving. With knowledge of the traffic pattern, IoT-aware adaptive DRX can further reduce signal load by 25%, especially for delay-sensitive traffic.
All Science Journal Classification (ASJC) codes
- Signal Processing
- Information Systems
- Hardware and Architecture
- Computer Science Applications
- Computer Networks and Communications