Research On Access In Low-power Internet Of Things

With the development of social science and technology,low-power Internet of Things(IoT)technology is applicated more and more.Compared with other IoT protocols such as Zigbee,BLE and SIGFOX,IEEE 802.11 ah has the advantage in long transmission distance and high communication speed.Based on the 802.11 ah protocol,this paper studies the power optimization problem in low-power Internet of Things(IoT),proposes a Signal Strength Assistant Grouping(SSAG)scheme and Real-Time Restricted Access Window(RAW)Setting(RTRS)algorithm to reduce the energy cost.Aiming at the problem of Hidden Node in IoT,this paper proposes a Signal Strength Assistant Grouping(SSAG)algorithm.In the proposed SSAG algorithm,several Reference Nodes(RN)with known locations are installed evenly in the IoT area.RNs sequentially transmit beacon signals,while the normal nodes monitor the signal strength from different RNs and join the group identified by the RN with the strongest average signal strength.The effect of SSAG algorithm on hidden node problems is analyzed through both the theory and simulation.Results show that SSAG algorithm can significantly reduce the probability of hidden node problems and reduce the system power consumption compared with free grouping algorithm.Taking into account service characteristics of low-power IoT applications,this paper proposes a Real-time RAW Setting(RTRS)algorithm.In RTRS,it is assumed that multiple nodes report data to an Access Point(AP),and the uplink channel resources are divided into Beacon periods in time.During a Beacon period,AP node firstly predicts the next data uploading time and the total amount of devices that will upload data in the next Beacon period.Then the AP node calculates the optimal RAW parameters for minimum energy cost and broadcasts the information to all nodes.Finally,all devices upload data according to the scheduling information from AP node.Simulation results show that the algorithm can dynamically adjust the parameters according to current network status and siginificantly improve the network energy efficiency.The algorithms proposed in this paper can effectively reduce the energy consumption of 802.11 ah.We believe the results can provide theoretical and practical reference for low-power IoT design.