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There has been considerable amount of research to improve performance for a dense wireless local area network (WLAN) environment. While some studies focus on aggressive channel access, others highlight frequent channel state information (CSI) corruption by excessive transmissions. We pay attention to midamble, adopted in the IEEE 802.11ax standard specification, to overcome CSI corruption. If the transmitter inserts midamble symbols, the receiver can acquire new CSI periodically during a physical layer convergence protocol (PLCP) protocol data unit (PPDU) frame. In this paper, we propose a precise receiver performance model to describe the impact of CSI, and design a standard-compliant algorithm called REMEDY that works with conventional channel access schemes by handling CSI corruption and time-varying channels in high-density WLAN networks. REMEDY determines whether to use midamble considering overhead, estimates on-frame signal-to-interference and noise ratio (SINR) to notice channel environments, and cancels the effects of scrambling and incorrect descrambling. We evaluate the performance of the conventional schemes with and without REMEDY in 11ax task group (TGax) indoor simulation scenarios using the ns-3 simulator, considering time-varying channels and CSI corruption. REMEDY helps the existing channel access schemes to achieve up to $2.20\times $ higher throughput while improving the throughput of the lowest performing group, compared to the existing schemes without REMEDY.

Millimeter-wave (mmWave) communication included in new radio (NR) provides high throughput to meet the stringent requirements of modern applications. However, its performance is highly dependent on whether obstacles are blocking line-of-sight (LOS) paths. Blockages on the LOS paths jeopardize reliable connections. E-UTRA-NR dual connectivity (EN-DC) is one option for managing unstable connectivity using robust long-term evolution (LTE) as well as mmWave NR. EN-DC aggregates and utilizes multiple links to provide a better quality of service (QoS) to users. However, the performance of EN-DC is strongly affected by flow control due to the possibility of out-of-order packet delivery at the packet data convergence protocol (PDCP) layer. In this paper, we propose a blockage-aware flow control scheme (BAFC) that appropriately responds to the dynamics of mmWave links in the presence of mobile blockages and improves users’ QoS. To this end, we also develop PDCP scheduling schemes that satisfy various users’ QoS requirements. Through extensive simulations, we verify that BAFC exploits over 99% of the sum capacity of links on average under rapidly changing channels due to mobile blockages. Moreover, BAFC combined with PDCP scheduling achieves higher throughput or reduces latency by up to 43.9% with minimal throughput degradation.

IEEE 802.15.4 Time-Slotted Channel Hopping (TSCH) has drawn significant attention as a low-power network solution for the Internet of Things (IoT). To make the TSCH scalable and robust, slot scheduling is an important issue that needs to be addressed. The research community has made significant strides with various autonomous or decentralized technologies in recent years. While these techniques try to provide non-overlapped slots for each link, they take collision for granted when multiple links utilize the same slot. In this paper, we challenge the perspective, investigate what happens within a TSCH slot, and find room for performance improvement even when multiple links unfortunately share a slot. To this end, we propose DualBlock that provides another chance for collision avoidance when multiple links try to utilize a slot at the same time by enabling clear channel assessment (CCA) and random backoff within the congested slot. In addition, given that the intra-slot backoff consumes more energy, a control mechanism is added that adjusts maximum backoff by monitoring network congestion level. DualBlock operates in a distributed manner for scalability. Extensive experiments demonstrate that TSCH networks achieve significant performance improvement in many aspects when DualBlock is combined with a scheduler (i.e., Orchestra), up to 3.6 times higher packet delivery ratio and 75% less radio duty cycle.

To support the emerging vehicle-to-everything (V2X) communication for autonomous vehicles and smart transportation services, 3rd Generation Partnership Project (3GPP) has recently introduced cellular V2X (C-V2X) standards. In C-V2X, radio resources can be managed not only centrally by the cellular network base station, but also in a completely distributed manner (Mode 4) without any cellular support. However, Mode 4 may suffer significant collisions and interference in a dense environment since each vehicle selects its own resources to transmit V2X messages autonomously without adapting appropriately to vehicle density. To address this challenge, we propose ATOMIC, an Adaptive Transmission pOwer and Message Interval Control scheme for C-V2X Mode 4, in which each vehicle utilizes real-time channel sensing and neighbor information to reduce channel contention for improved reliability and latency. Through analysis and extensive simulations, we show that ATOMIC outperforms the standard Mode 4 in both urban and highway scenarios especially in highly dense environments.

Location-based authentication for Internet of Things (IoT) devices can be used to permit activation and participation only to those devices that are in their predefined areas. It secures the devices from being used elsewhere (e.g. misplacement or theft), and also secures the system by preventing non-authorized devices from joining the network. However, absolute location is not required for such purposes; only whether the device is within the designated ‘secure’ region or not matters, which we define as the secure region detection problem. In this work, we propose SWORD, the first secure region detection scheme based on channel state information (CSI) of Wi-Fi and deep one-class classification (OCC) technique. OCC can be trained using data only from the inside of a secure region and no negative reference point is required, a critical advantage considering that outside of a secure region is practically unbounded. Our real-world experiment results show that SWORD can achieve 99.14% true-negative rate (TN, successfully rejecting devices not in secure region) and an acceptable true-positive (TP) of 76.90% for practical usage. Furthermore, there is an user-adjustable trade-off between TN and TP based on application requirement, and TP can be improved to 97.92% without a big loss of TN using simple automatic repeat mechanism.

In this paper, we investigate a downlink non-orthogonal multiple access (NOMA) system consisting of a base station (BS) and two users, where each user decodes its own signal through successive interference cancellation (SIC). When the signal of one user, called the weak user (WU) who has a bad channel, is being decoded, the signal of the other user, called the strong user (SU) who has a good channel, acts as interference. In an interference channel, we can increase the achievable rate by applying improper Gaussian signaling (IGS). Therefore, we apply IGS to SU, aiming to mitigate the interference. We also consider imperfect SIC at SU, which is a more general assumption for a NOMA system. For the considered NOMA system model, we derive the outage probability of each user in a closed form, provide its asymptotic expression, and obtain its diversity order. We also derive the ergodic rate of each of the two users in a closed form. We propose two algorithms to maximize the fairness of the NOMA system based on the primal decomposition method. Through simulation, we verify that our analysis is correct, and confirm that applying IGS improves the fairness of the NOMA system.

3GPP cellular communications in unlicensed spectrum allow transmission only after completing listen-before-talk (LBT) operation. For downlink, the LBT operation helps cellular traffic to coexist well with Wi-Fi traffic. However, cellular uplink transmission is attempted only at the time specifically determined by the base station after having a successful LBT and the user equipment (UE) may suffer transmission failure and delayed transmission due to Wi-Fi interference. As a result, cellular uplink traffic does not coexist well with Wi-Fi traffic. This article mathematically analyzes the problem of unfairness between cellular and Wi-Fi for uplink channel access. To address the coexistence problem in unlicensed spectrum, we propose a standard-compliant approach, termed UpChance, which allows the UE to use a minimum length of uplink reservation signal and the base station to determine the optimal timing for the UE's uplink transmission. Through ns-3 simulation, we verify that UpChance improves the performance of fairness and random access completion time by up to 88% and 99%, respectively.

Aerial acoustic communication (AAC) has been developed for a variety of Internet-of-things (IoT) applications, thanks to the merit of embedding small amounts of data directly into audio contents and transmitting them through commercial off-the-shelf (COTS) devices without additional infrastructure. However, AAC has clear limitations due to ambient noise, severely frequency-selective acoustic channels, and high power consumption of COTS devices. We adopt chirp spread spectrum (CSS) modulation and design new quaternary symbols to overcome frequency selectivity of audio interfaces of COTS devices. We also develop a computation-efficient method to demodulate the proposed symbols, aiming to reduce the power consumption of COTS devices. We employ a frame combining technique without increasing computational complexity, to mitigate the effects of multipath fading and ambient noise in acoustic channels. To evaluate the proposed methods, we conduct extensive experiments with several smartphones in various environments. The experimental results and evaluation demonstrate that the proposed symbols and frame combining method contribute to improving the frame reception ratio by up to 59.8%p (267.9%) and 14%p (84.3%), respectively. The frame combining increases the possibility of receiving a frame within two attempts at extremely low SNR, by up to 107.9%, resulting in reduced excessive delay. The method to demodulate the proposed symbols lowers power consumption by tens to hundreds of milliwatts, depending on the device. Our proposal significantly helps to achieve high reliability and low power consumption of COTS devices in AAC.

One of the most important and recurrent tasks in managing a store is to provide accurate information of products to customers by maintaining up-to-date price tags of every item. Till today, however, updating price tags is done manually in most markets, which is labor-intensive, time-consuming, and error-prone. Adopting wirelessly reconfigurable electronic price tags could be of significant benefit to this problem. A key requirement of such a system, then, is to establish a robust, reliable, and scalable wireless communication network while spending minimal energy on thousands of densely-deployed and battery-powered price tags. In this work, we present a comprehensive study of electronic shelf labeling (ESL) system including its design and real-world deployment experiences. While the overall design turns out to be relatively straightforward, our preliminary study using 1000 real commercial e-tags reveals technical challenges in reliable and low-power wireless communication with ultra-high node density in scatter-rich indoor environments. To address the problem, we adopt multi-radio and multi-channel diversity techniques which need to modify only the gateways but significantly improve overall system performance. Our evaluation from a real-world deployment of 550 tags at an actual convenience store shows that our proposal achieves 98.51% network connectivity, 590 ms average latency for price updates, and over 5 years of e-tag lifetime. ESL system is part of the upcoming smart market era, and we see this work as a practical industrial application case study of Internet of Things technologies.

Low-power wireless network for the emerging Internet of Things (IoT) should be reliable enough to satisfy the application requirements, and also energy-efficient for embedded devices to remain battery powered. Synchronized communication methods such as Time Slotted Channel Hopping (TSCH) have shown promising results for these purposes, achieving end-to-end reliability over 99% with low duty-cycles. However, they lack one thing: flexibility to support a wide variety of applications and services with unpredictable traffic load and routing topology due to “fixed” slotframe sizes. To this end, we propose TESLA, a traffic-aware elastic slotframe adjustment scheme for TSCH networks which enables each node to dynamically self-adjust its slotframe size at run time. TESLA aims to minimize its energy consumption without sacrificing reliable packet delivery by utilizing incoming traffic load to estimate channel contention level experienced by each neighbor. We extensively evaluate the effectiveness of TESLA on large-scale 110-node and 79-node testbeds, demonstrating that it achieves up to 70.2% energy saving compared to Orchestra (the de facto TSCH scheduling mechanism) while maintaining 99% reliability.