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WiPLUS: Towards LTE-U Interference Detection, Assessment and Mitigation in 802.11 Networks

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We propose WiPLUS – a system that enables WiFi to deal with the stealthy invasion of LTE-U into the frequency bands used by WiFi. Using solely MAC layer information extracted passively, during runtime, out of the hardware registers of the WiFi NIC at the WiFi access point, WiPLUS is able to: i) detect interfering LTE-U signals, ii) compute their duty-cycles, and iii) derive the effective medium airtime available for each WiFi link in a WiFi Basic Service Set (BSS). Moreover WiPLUS provides accurate timing information about the detected LTE-U ON and OFF phases enabling advanced interference mitigation strategies such as interference-aware scheduling of packet transmissions, rate adaptation and adaptive channel bonding. WiPLUS does not require any modifications to the WiFi client stations and works with commodity WiFi APs where it has a simple software installation process. We present the design, the implementation details and the evaluation of the WiPLUS approach. Evaluation results reveal that it is able to accurately estimate the effective available medium airtime for each link in a WiFi BSS under a wide range of LTE-U signal strengths with a root-mean-square error of less than 3 % for the downlink and less 10 % for the uplink.
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... Before establishing the CTC channel, a network becomes aware of the other one through a Cross-Technology Interference (CTI) detection mechanism, for instance, one of those in [16][17][18][19]. Then, the channel establishment takes place through CTC-CEM in three phases: (i) network discovery (Section IV), (ii) cross-network neighbor discovery (Section V-A), and (iii) energy optimization (Section V-C). ...
... Afterwards, before increasing the weight of n, all nodes that has equal weight as n are removed from the related lists in Z and n is added to their lists in N (lines 10-11). The weight of n is increased by one (line 12); if another node (k 2 ) has the same weight as n, that node is removed from N (n) and k 2 and n are added to the related lists in Z (lines [13][14][15][16]. Finally, the algorithm returns the improved schedule S (line 17). ...
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Cross-Technology Communication (CTC) allows direct message exchange between devices with different (i.e., incompatible) wireless communication standards. CTC is particularly suitable to allow for coordination between heterogeneous devices sharing the same spectrum, as in the Internet of Things. Existing research on CTC has focused on enabling communications for diverse technologies with the goal of achieving a high throughput. However, it did not address how to establish a link suitable for CTC, which is necessary for successful data exchange. This article specifically addresses such a problem by introducing CTC-CEM (CTC Channel Establishment with Multiple nodes), a scheme to establish a CTC channel involving the use of multiple nodes in a network. CTC-CEM employs duty-cycling and leverages network density to reduce energy consumption, while keeping a low discovery latency. In particular, CTC-CEM defines different discovery protocols to reliably detect co-located networks. Moreover, it addresses the selection of multiple CTC nodes as a set cover problem, and includes an optimization technique based on dynamic programming to balance the energy consumption in the whole network. Extensive simulations show that CTC-CEM effectively distributes the energy consumption in the network, increasing fairness by 97% after optimization. Furthermore, the latency in establishing a channel with CTC-CEM is two orders of magnitude lower than that for device discovery in duty-cycled networks.
... Finally, WiPlus [253] uses ML (i.e., k-means clustering) on the Wi-Fi side to detect LTE-U interference by using the spectral scan capabilities of COTS Wi-Fi hardware. This approach allows Wi-Fi to quantify the effective available channel airtime of each Wi-Fi link (downlink/uplink) at runtime. ...
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... Finally, WiPlus [248] uses ML (i.e., k-means clustering) on the Wi-Fi side to detect LTE-U interference by using the spectral scan capabilities of COTS Wi-Fi hardware. This approach allows Wi-Fi to quantify the effective available channel airtime of each Wi-Fi link (downlink/uplink) at runtime. ...
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Wireless local area networks (WLANs) empowered by IEEE 802.11 (Wi-Fi) hold a dominant position in providing Internet access thanks to their freedom of deployment and configuration as well as the existence of affordable and highly interoperable devices. The Wi-Fi community is currently deploying Wi-Fi~6 and developing Wi-Fi~7, which will bring higher data rates, better multi-user and multi-AP support, and, most importantly, improved configuration flexibility. These technical innovations, including the plethora of configuration parameters, are making next-generation WLANs exceedingly complex as the dependencies between parameters and their joint optimization usually have a non-linear impact on network performance. The complexity is further increased in the case of dense deployments and coexistence in shared bands. While classical optimization approaches fail in such conditions, machine learning (ML) is well known for being able to handle complexity. Much research has been published on using ML to improve Wi-Fi performance and solutions are slowly being adopted in existing deployments. In this survey, we adopt a structured approach to describing the various areas where Wi-Fi can be enhanced using ML. To this end, we analyze over 200 papers in the field, providing readers with an overview of the main trends. Based on this review, we identify both open challenges in each Wi-Fi performance area as well as general future research directions.
... WiFi discovery frames have been leveraged previously for data transfer in various applications ranging from low-level network management, such as interference reduction, to highlevel applications, such as broadcasting user-specific advertisements [8][9][10][11]. However, we argue that the mere decision of leveraging discovery related network traffic, which is generally broadcast on all channels, to transmit data is not enough. ...
... However, these protocols are vendor specific and do not guarantee ubiquitous implementation. WiPLUS [17] uses ED registers and modifies the client scheduling at Wi-Fi AP to detect LTE-U. However, ED registers cannot identify the channel of LTE operations and modifying client scheduling increases delay and unfairness. ...
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