Resource Allocation for Machine-Type Communication of Energy-Harvesting Devices in Wi-Fi HaLow Networks

Abstract

The recent Wi-Fi HaLow technology focuses on adopting Wi-Fi for the needs of the Internet of Things. A key feature of Wi-Fi HaLow is the Restricted Access Window (RAW) mechanism that allows an access point to divide the sensors into groups and to assign each group to an exclusively reserved time interval where only the stations of a particular group can transmit. In this work, we study how to optimally configure RAW in a scenario with a high number of energy harvesting sensor devices. For such a scenario, we consider a problem of device grouping and develop a model of data transmission, which takes into account the peculiarities of channel access and the fact that the devices can run out of energy within the allocated intervals. We show how to use the developed model in order to determine the optimal duration of RAW intervals and the optimal number of groups that provide the required probability of data delivery and minimize the amount of consumed channel resources. The numerical results show that the optimal RAW configuration can reduce the amount of consumed channel resources by almost 50%.

Resource Allocation Strategy of the Educational Resource Base for MEC Multiserver Heuristic Joint Task

“…UE associated with the same SBS allocates orthogonal spectrum, so there is no intra cell interference between UE which is associated with the same SBS. [ 19 – 21 ]. The uplink transmission rate is shown in the following formula: where B nk represents the channel bandwidth allocated by SBS k to UE n , P n represents the transmission power of UE n , h nk is the channel gain between SBS k and UE n , and N 0 is the power spectral density.…”

Balanced Allocation Method of Physical Education Distance Education Resources Based on Linear Prediction

“…e smaller the resource matching distance, the more balanced the server resource utilization. At the same time, in order to make full use of various types of resources and minimize the fragments of unavailable resources, if the remaining amount of some resources of the server is not enough to create any type of new virtual machine, the remaining rate of other types of resources of the server shall be less than a preset minimum [16]. In order to ensure the timeliness of resource provision, the balanced allocation method of sports distance education resources should actively predict and configure a certain number of virtual machines in advance to deal with the sudden growth of resource demand in the future.…”

An Analytical Model for the Aggregate Throughput of IEEE 802.11ah Networks under the Restricted Access Window Mechanism

“…They validated their model based on a simulator designed by themselves, i.e., not widely adopted by the networking community. In [ 36 ], Bankov et al extended the model from [ 35 ] for the scenario where the IEEE 802.11ah network has energy-harvesting sensor stations. They studied how to optimize the RAW parameters, such as the duration and number of groups, that provide the required probability of data delivery and minimize the amount of consumed channel resources in a network with a high number of energy-harvesting sensor devices.…”

“…Although there are different approaches in the literature for modifications in MAC-layer protocols to reduce energy consumption, there is still a gap to understand possible MAC improvements to enable RF energy harvesting in IoT systems and ensure the energy self-sustainability of the network [ 47 ]. Moreover, to date, most works have tackled the introduction of RF energy harvesting only in traditional Wi-Fi networks [ 48 , 49 , 50 , 51 ], and only recently has there been some effort to introduce energy harvesting into IEEE 802.11ah networks [ 36 ]. Therefore, there is still a need to address RF energy harvesting in IEEE 802.11ah networks and, because of that, our future work aims to integrate RF energy harvesting in the operation of IEEE 802.11ah networks.…”