2021/07/05 by Indika Dhanapala, Dhanapala, Indika S. A., Ramona Marfievici +3
Computer Science · Engineering · #68M12 #Advanced MIMO Systems Optimization #C.2.2 #FOS: Computer and information sciences #Millimeter-Wave Propagation and Modeling #Networking and Internet Architecture (cs.NI) #Wireless Networks and Protocols
paper · pdf · doi:10.48550/arxiv.2107.02271
openalex publication_date 2021/07/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In the last decade, the advancement of the Internet of Things (IoT) has\ncaused unlicensed radio spectrum, especially the 2.4 GHz ISM band, to be\nimmensely crowded with smart wireless devices that are used in a wide range of\napplication domains. Due to their diversity in radio resource use and channel\naccess techniques, when collocated, these wireless devices create interference\nwith each other, known as Cross-Technology Interference (CTI), which can lead\nto increased packet losses and energy consumption. CTI is a significant problem\nfor low-power wireless networks, such as IEEE 802.15.4, as it decreases the\noverall dependability of the wireless network.\n To improve the performance of low-power wireless networks under CTI\nconditions, we propose a data-driven proactive receiver-aware MAC protocol,\nLUCID, based on interference estimation and white space prediction. We leverage\nstatistical analysis of real-world traces from two indoor environments\ncharacterised by varying channel conditions to develop CTI prediction methods.\nThe CTI models that generate accurate predictions of interference behaviour are\nan intrinsic part of our solution. LUCID is thoroughly evaluated in realistic\nsimulations and we show that depending on the application data rate and the\nnetwork size, our solution achieves higher dependability, 1.2% increase in\npacket delivery ratio and 0.02% decrease in duty-cycle under bursty indoor\ninterference than state of the art alternative methods.\n