Scheduling UWB Ranging and Backbone Communications in a Pure Wireless Indoor Positioning System

被引:0
|
作者
Charlier, Maximilien [1 ]
Koutsiamanis, Remous-Aris [2 ]
Quoitin, Bruno [1 ]
机构
[1] Univ Mons UMONS, Dept Comp Sci, B-7000 Mons, Belgium
[2] Inria, IMT Atlantique, STACK Res Grp, LS2N, F-44307 Nantes, France
来源
IOT | 2022年 / 3卷 / 01期
关键词
ultra-wideband; TSCH; MAC; TDMA; IPS; scheduling; localization; SENSOR NETWORKS;
D O I
10.3390/iot3010013
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
In this paper, we present and evaluate an ultra-wideband (UWB) indoor processing architecture that allows the performing of simultaneous localizations of mobile tags. This architecture relies on a network of low-power fixed anchors that provide forward-ranging measurements to a localization engine responsible for performing trilateration. The communications within this network are orchestrated by UWB-TSCH, an adaptation to the ultra-wideband (UWB) wireless technology of the time-slotted channel-hopping (TSCH) mode of IEEE 802.15.4. As a result of global synchronization, the architecture allows deterministic channel access and low power consumption. Moreover, it makes it possible to communicate concurrently over multiple frequency channels or using orthogonal preamble codes. To schedule communications in such a network, we designed a dedicated centralized scheduler inspired from the traffic aware scheduling algorithm (TASA). By organizing the anchors in multiple cells, the scheduler is able to perform simultaneous localizations and transmissions as long as the corresponding anchors are sufficiently far away to not interfere with each other. In our indoor positioning system (IPS), this is combined with dynamic registration of mobile tags to anchors, easing mobility, as no rescheduling is required. This approach makes our ultra-wideband (UWB) indoor positioning system (IPS) more scalable and reduces deployment costs since it does not require separate networks to perform ranging measurements and to forward them to the localization engine. We further improved our scheduling algorithm with support for multiple sinks and in-network data aggregation. We show, through simulations over large networks containing hundreds of cells, that high positioning rates can be achieved. Notably, we were able to fully schedule a 400-cell/400-tag network in less than 11 s in the worst case, and to create compact schedules which were up to 11 times shorter than otherwise with the use of aggregation, while also bounding queue sizes on anchors to support realistic use situations.
引用
收藏
页码:219 / 258
页数:40
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