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WiPLUS: Towards LTE-U Interference Detection, Assessment and Mitigation in 802.11 Networks
Abstract and Figures
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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Supplementary resource (1)
... 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). ...
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. ...
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
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 describe the various Wi-Fi areas where ML is applied. To this end, we analyze over 250 papers in the field, providing readers with an overview of the main trends. Based on this review, we identify specific open challenges and provide general future research directions.
... 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. ...
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. ...
LTE in unlicensed 5 GHz bands is being deployed by mobile operators for increased capacity. In this paper, we conduct an extensive measurement study with commodity LTE and Wi-Fi hardware to identify key coexistence challenges. Our study -- the first to include a commercial LAA base station -- confirms that LTE interference causes WiFi performance to degrade, harming 802.11ac high-throughput features. We then present DeMiLTE -- a system for commodity enterprise WiFi APs that detects, quantifies, and reacts to LTE interference. To our best knowledge, our solution is the first that achieves fair coexistence without modifying the LTE PHY/MAC, while still being fully-compliant to the 802.11ac standard. DeMiLTE's architecture is based on lightweight per-link interference detection and enables WiFi APs to mitigate LTE-induced performance degradation with minimal overhead. Our evaluation results show that DeMiLTE can provide up to 110% throughput gains and alleviate client disruption caused by LTE interference.
... Hence, we envision the following ML/DL approach. First, a node joining the radio spectrum performs scanning for different technologies in vicinity using methods like [23], [24]. After discovering the OTFG dimensions used by the technologies in vicinity, the node loads the corresponding pretrained DeepCTC model from which it automatically derives the transmitter and receiver functionality. ...
Recently, it was shown that a communication system could be represented as a deep learning (DL) autoencoder. Inspired by this idea, we target the problem of OFDM-based wireless cross-technology communication (CTC) where both in-technology and CTC transmissions take place simultaneously. We propose DeepCTC, a DL-based autoencoder approach allowing us to exploit DL for joint optimization of transmitter and receivers for both in-technology as well as CTC communication in an end-to-end manner. Different from classical CTC designs, we can easily weight in-technology against CTC communication. Moreover, CTC broadcasts can be efficiently realized even in the presence of heterogeneous CTC receivers with diverse OFDM technologies. Our numerical analysis confirms the feasibility of DeepCTC as both in-technology and CTC messages can be decoded with sufficient low block error rate.
In this study, an energy-efficient self-organized framework for sub-channel allocation and power allocation is presented for ultra-dense small cell networks, which can operate in both licensed and unlicensed bands. In order to protect legacy WiFi devices(operating in unlicensed bands), we consider the LTE operation in unlicensed bands based on CSAT, in which ‘ON’ and ‘OFF’ dutycycle approach is utilized. On the other hand, there are severe interference management problems among small cells (operating in licensed and unlicensed bands) and between macro cells and small cells (operating in licensed bands) due to co-channel and ultra-dense deployment of small cells. This article proposes a self-organized optimization framework for the allocation of sub-channels and power levels by exploiting a non-cooperative game with the objective to maximize the energy efficiency of dual-access small cells without creating harmful impact on coexisting network entities including macro cell users, small cell users, and legacy WiFi devices. Simulation results show that the proposed scheme outperforms (6% and 11%) and (8% and 18%) the round-robin and the spectrum-efficient schemes, respectively for two different small cell scenarios. In addition, it is shown that for less CSI estimation errors
$\varsigma = 0.02$
, the maximum performance degradation of the proposed scheme is reasonably small (5.5%) as compared to the perfect CSI.
We present our current work-in-progress on the design and implementation of a hybrid TDMA/CSMA medium access architecture, hereafter referred to as hMAC, which can be used on top of commercial IEEE 802.11 off-the-shelf hardware. The software only solution is based on the popular Linux ATH9K softMAC driver and hence can be used with standard Linux systems using Atheros based wireless network devices. The proposed hMAC exploits the standard 802.11 power saving functionality present in the ATH9K device driver to enable control of the software packet queues. This allows the assignment of TDMA time slots on wireless link and traffic class basis. While the solution is placed only in the device driver, the CSMA/CA functionality on hardware level is still active. This enables inter-working with standard unmodified 802.11 devices. We tested our prototypical hMAC implementation in a small test-bed. Therefore, we implemented a centralized interference management scheme in which pairs of links suffering from a hidden node problem are assigned to TDMA time slots on a per-link basis. To show the benefits of the proposed hMAC approach we compared the results with standard 802.11 DCF and classical, i.e. per-node, TDMA. Finally, to enable collaboration with the research community, the hMAC source code is provided as open-source.
The increased usage of IEEE 802.11 Wireless LAN (WLAN) in residential environments by unexperienced users leads to dense, unplanned and chaotic residential WLAN deployments. Often WLAN Access Points (APs) are deployed unprofitable in terms of radio coverage and interference conditions. In many cases the usage of the neighbor's AP would be beneficial as it would provide better radio coverage in some parts of the residential user's apartment. Moreover, the network performance can be dramatically improved by balancing the network load over spatially co-located APs. We address this problem by presenting Neighborhood extensible WLAN (NxWLAN) which enables the secure extension of user's home WLANs through usage of neighboring APs in residential environments with zero configuration efforts and without revealing WPA2 encryption keys to untrusted neighbor APs. NxWLAN makes use of virtualization techniques utilizing neighboring AP by deploying on-demand a Wireless Termination Point (WTP) on the neighboring AP and by tunneling encrypted 802.11 traffic to the Virtual Access Point (VAP) residing on the home AP. This allows the client devices to always authenticate against the home AP using the WPA2-PSK passphrase already stored in the device without any additional registration process. We implemented NxWLAN prototypically using off-the-shelf hardware and open source software. As the OpenFlow is not suited for forwarding native 802.11 frames, we built software switch using P4 language. The performance evaluation in a small 802.11 indoor testbed showed the feasibility of our approach. NxWLAN is provided to the community as open source.
This paper investigates the co-existence of Wi-Fi and LTE in emerging unlicensed frequency bands which are intended to accommodate multiple radio access technologies. Wi-Fi and LTE are the two most prominent access technologies being deployed today, motivating further study of the inter-system interference arising in such shared spectrum scenarios as well as possible techniques for enabling improved co-existence. An analytical model for evaluating the baseline performance of co-existing Wi-Fi and LTE is developed and used to obtain baseline performance measures. The results show that both Wi-Fi and LTE networks cause significant interference to each other and that the degradation is dependent on a number of factors such as power levels and physical topology. The model-based results are partially validated via experimental evaluations using USRP based SDR platforms on the ORBIT testbed. Further, inter-network coordination with logically centralized radio resource management across Wi-Fi and LTE systems is proposed as a possible solution for improved co-existence. Numerical results are presented showing significant gains in both Wi-Fi and LTE performance with the proposed inter-network coordination approach.
Using LTE in unlicensed bands will allow operators to access additional spectrum to meet the increasing demand for mobile services. In this article, we provide an overview of the different approaches currently being considered for LTE operation in unlicensed bands and their interaction with WiFi networks. In summary, LTE-Unlicensed with carrier sense adaptive transmission is likely to be available in the short term, but cannot be used in all regions due to regulatory restrictions. License assisted access is intended for use more widely, so it will include listen-before- talk and other features required to conform with, for example, European and Japanese regulations. However, this will require changes to the LTE standards, so license assisted access is likely to take longer to deploy. In addition to describing the trade-offs between these approaches, we also discuss the issue of fair coexistence with existing unlicensed band users, especially WiFi devices.
Wireless LANs (WLANs) carry a diversemix of traffic, ranging from delay-sensitive real-time applications to bulk transfers. Using existing QoS mechanisms in high speed WLANs (e.g., 802.11n/ac) presents a tradeoff between maximizing the performance of real-time applications and achieving high throughput. We propose SlickFi, a service differentiation scheme for high-speed WLANs that addresses this tradeoff by leveraging existing dual radio WiFi access points (APs). SlickFi opportunistically adapts channel width on a per-frame basis based on application demands and communicates traffic information across radios to control aggregate frame sizes for improving channel efficiency. SlickFi can be readily deployed on commodity devices using only driver-level changes at the AP-side. We implemented SlickFi in the ath9k driver and using real testbed experiments, show that it can improve aggregate throughput by up to 1.8x and 2.2x over 802.11n and 802.11e, respectively and the PSNR of 1080p videos by up to 3.4x and 1.7x over 802.11n and 802.11e, respectively.
Omnipresent Wi-Fi access points (APs) periodically broadcast beacon frames to inform potential stations (STAs) about their existence. Beacon frames can be extended by adding additional information (so-called beacon stuffing) making it possible to deliver this information to mobile devices (smart-phones, tablets, etc. equipped with 802.11 interfaces) without the need for association with the local infrastructure. This feature can be used to support location-based information services (LBS) related for e.g. advertising local opportunities, temporary obstacles and traffic disturbances or emergency notifications. In this paper we discuss technical solutions that support LBS using 802.11 beacon stuffing. For a selected approach we present the design, implementation details and performance evaluation for Location-based Wi-Fi Services (LoWS) - a complete open source solution. LoWS supports an original, highly efficient way to encode information. The LoWS system can be integrated in an existent 802.11 infrastructure while the receiver application can be installed on commercial off-the-shelf Android devices. The LoWS system is modular with well-defined interfaces making it an attractive tool for modifications, changes and improvements.
Recently, there has been an increasing interest in operating long-term evolution (LTE) in unlicensed bands (i.e., LTE-U). However, since LTE and wireless local area networks (WLANs) are designed to operate in different bands, they have no coexistence mechanism, which leads to significant performance degradation. In particular, since LTE does not sense channel vacancy prior to transmissions, the LTE interference severely affects the WLAN operation. To address this problem, we propose a fair listen-before-talk (F-LBT) algorithm for coexistence of LTE-U and WLAN in unlicensed bands. F-LBT jointly considers the total system throughput and the fairness between LTE-U and WLAN and then allocates an appropriate idle period for WLAN. Evaluation results demonstrate that F-LBT can improve the total system throughput while providing the fairness between LTE-U and WLAN.
The phenomenal growth of mobile data demand has brought about increasing scarcity in available radio spectrum. Meanwhile, mobile customers pay more attention to their own experience, especially in communication reliability and service continuity on the move. To address these issues, LTE-Unlicensed, or LTEU, is considered one of the latest groundbreaking innovations to provide high performance and seamless user experience under a unified radio technology by extending LTE to the readily available unlicensed spectrum. In this article, we offer a comprehensive overview of the LTEU technology from both operator and user perspectives, and examine its impact on the incumbent unlicensed systems. Specifically, we first introduce the implementation regulations, principles, and typical deployment scenarios of LTE-U. Potential benefits for both operators and users are then discussed. We further identify three key challenges in bringing LTE-U into reality together with related research directions. In particular, the most critical issue of LTE-U is coexistence with other unlicensed systems, such as widely deployed WiFi. The LTE/WiFi coexistence mechanisms are elaborated in time, frequency, and power aspects, respectively. Simulation results demonstrate that LTE-U can provide better user experience to LTE users while well protecting the incumbent WiFi users??? performance compared to two existing advanced technologies: cellular/WiFi interworking and licensed-only heterogeneous networks (Het-Nets).