Ambient backscatter communication has emerged as a promising paradigm for ultra-low-power wireless systems. To support diverse IoT applications, backscatter communication should support high uplink throughput, maintain ultra-low power consumption, and reuse existing Wi-Fi signals without special infrastructure. Achieving high-throughput backscatter over existing Wi-Fi signals, however, remains challenging because rapid fluctuation of ambient signals distort the backscattered signal, severely degrading decoding reliability and limiting throughput. Existing approaches, such as codeword translation and per-sample encoding, fail to meet all these requirements, particularly due to their limited throughput caused by single-carrier modulation and the need for additional hardware, such as dual receivers or full-duplex receivers. To address this issue, in this paper, we propose MCScatter, whereby an ultra-low-power device (ULPD) modulates its data using multi-carrier modulation and transmits data by reflecting ambient Wi-Fi signals. To mitigate distortion from ambient signal fluctuations, MCScatter estimates the effective channel, capturing both wireless propagation effect and fluctuations, and equalizes the received signal accordingly. To boost throughput, MCScatter incorporates two mechanisms: Frequency-aware Adaptive Modulation (FAM), which chooses different modulation schemes across subcarriers, and Maximum Likelihood Estimation (MLE), which enables reliable decoding of ULPD data embedded on the cyclic prefix (CP) of a Wi-Fi signal. To the best of our knowledge, MCScatter is the first design to jointly realize OFDM-based ULPD modulation with practical reuse of ambient Wi-Fi signals. To analytically characterize system behavior, we develop an analytical bit error rate (BER) model for MCScatter. Evaluation results demonstrate that MCScatter significantly outperforms benchmarks in both BER and throughput.

Concurrent transmission with collision resolution has been considered as the multiple access solution in backscatter networks. However, designing practical collision resolution mechanisms in backscatter networks is challenging for the following reasons. First, interference from multiple tags accumulates, resulting in strong and complicated inter-tag interference. Second, transmitted signals are distorted by various factors (e.g., imperfect digital filter), which have not been considered in previous collision resolution schemes. Due to these distortions, tag-side mechanism like orthogonal codes, which assume undistorted conditions, are not effective for resolving collision at the receiver. Third, variation in received signal levels across tags often degrades performance in concurrent transmissions (i.e., near-far problem). Although transmit power control was proposed as a solution, it increases tag complexity and energy consumption. To address the challenges, we propose CodeScatter, a distortion-aware design for collision resolution that is robust to near-far problem in backscatter networks. The innovative features of CodeScatter are 1) distortion-aware design and 2) robustness to near-far problem without transmit power control. CodeScatter achieves these features by employing two mechanisms: 1) Distortion-aware Successive Decoding (DSD), which iteratively isolates individual tag signals while accounting for distortions and 2) Distortion-aware Orthogonal Codes (DOC), which ensures orthogonality even in the presence of distortions. To our knowledge, CodeScatter is the first distortion-aware design for collision resolution in backscatter networks. We implement a prototype using COTs RF switch and USRPN210. Experimental results demonstrate that CodeScatter outperforms previous proposals in terms of BER and throughput.

Predicting trajectories of neighboring vehicles accurately is essential for safe driving in Advanced Driving Assistance Systems (ADAS). Conventional approaches for predicting trajectory rely upon an expensive image sensor (i.e., lidar). However, high cost but limited sensing range of lidar makes installing a trajectory prediction system on existing vehicles impractical. Using two functionalities provided by a smartphone, i.e., periodic beaconing and GPS positioning could address issues of conventional approaches. However, modules for wireless communications and GPS are limited in achieving accurate prediction in their current form: transmission error and inaccurate GPS data. In this paper, we propose a novel scheme for predicting neighbors’ trajectories using periodic beaconing and GPS, and show that our scheme is feasible to trajectory prediction. To address the limitations of the wireless and GPS modules, our scheme integrates Long Short-Term Memory (LSTM) with two strategies: 1) Tailoring Multi-band Transmission to Prediction (TMTP) and 2) Environment-Aware Positioning (EAP). To improve prediction accuracy even with the imperfect input, our scheme employs interactive LSTM model. To our knowledge, this is the first to enable predicting the neighbors’ trajectories using periodic beaconing with inaccurate GPS data. Experimental results using real traces demonstrate that our scheme is accurate in predicting neighbors’ trajectories.

As the capabilities for vehicular communications have become widespread, periodic beaconing is becoming fundamental to tracking neighbors. Specifically, a vehicle periodically broadcasts its kinematic data and receivers estimate the sender’s evolving position. To ensure safety, tracking neighbors via beaconing requires position errors and transmission delay to be small. To satisfy stringent requirements, previous proposals have employed multiple RF devices based on the unrealistic assumption that vehicles have the same type of RF devices. In reality, vehicles possess different RF devices (heterogeneous vehicle conditions). Satisfying the requirements under heterogeneous conditions is challenging because network connectivity is low and multi-hop transmissions to improve the connectivity aggravate network congestion. To address this challenge, we propose a novel scheme using a model-based trajectory prediction and multi-hop transmissions adaptively. To maintain accuracy of the model, each vehicle creates a model for predicting its own trajectory and distributes the model. For reliable multihop transmissions, our scheme employs periodic scan for translator and disconnected neighbors (PSTN) and probabilistic relay (PR). To our knowledge, this is the first to consider heterogeneous vehicle conditions for tracking neighbors via beaconing. Evaluation confirms that our scheme tracks neighbors more accurately than previous work.

Reliable safety message dissemination is a fundamental primitive for constructing intersection safety systems. Normally, the dissemination is based on vehicular communications, of which the de-facto standard is Dedicated Short Range Communications (DSRC). However, due to high frequency operations, a DSRC signal is seriously attenuated when being propagated in Non Line-Of-Sight (NLOS) conditions. Previous schemes leveraged the use of centralized infrastructures or relay vehicles enabling a safety message to bypass large obstacles. However, implementing the infrastructures in all intersections would be very costly; one may not find proper relay vehicles in low density, and frequent rebroadcasts cause serious network congestion in high density. To address this challenge, we propose a novel scheme that exploits excellent propagation characteristics of a TV White Space (TVWS) band (in addition to a DSRC band) for reliable dissemination in NLOS intersections. To ensure reliable dissemination throughout a broad range of densities without infrastructures, our scheme employs two innovative mechanisms: a collaborative procedure and a Dynamic optimal Configuration (DoC). To our knowledge, this is the first that simultaneously satisfies two vital demands for intersection safety system: 1) lacking infrastructures and 2) working well in all densities. Simulation studies show that the proposed scheme outperforms previous infrastructure-based schemes.

Real-time video dissemination over Vehicular Ad hoc Networks (VANETs) is fundamental for many services, e.g., emergency video delivery, road-side video surveillance, and advertisement broadcasting. These applications deal with several challenges due to strict video quality level requirements and highly dynamic topologies. To handle these challenges, geographic receiver-based beacon-less approaches have been proposed as a suitable solution for forwarding video flows in VANETs. In general, the routing decisions are performed only based on network, link, and/or node characteristics, such as link quality and vehicle's location. However, in real situations, due to different requirements and hierarchical structures of multimedia applications, these existent routing decisions are not satisfactory to select the best relay nodes and build up reliable backbones to delivery video content with reduced delay and high Quality of Experience (QoE). This paper introduces the QOe-Driven and LInk-qualiTy rEceiver-based (QOALITE) protocol to allow live video dissemination with QoE assurance in Vehicle-to-Vehicle (V2V) scenarios. QOALITE considers video and QoE-awareness, coupled with location and link quality attributes for relay selection. Simulation results show the benefits of QOALITE when compared to existing work, while achieving multimedia transmission with QoE support and robustness in highway scenarios.

In wireless networks, broadcasting is a fundamental communication primitive for network management and information sharing. However, in multi-channel networks, the broadcast efficiency is very poor as devices are distributed across various channels. Thus, a sender tries all channels for broadcasting a single message, which causes large overhead. In this paper, we propose a novel scheme for efficient broadcast in multichannel networks. Our scheme leverages the overlapped band, which is the frequency range that partially overlapped channels (i.e., adjacent channels) share within their channel boundaries. Specifically, a sender advertises the rendezvous channel through the overlapped band of adjacent channels; the message sharing via broadcast is done on the rendezvous channel. Our scheme employs Signaling via Overlapped Band (SOB), which defines a new signal processing mechanism for communication via the overlapped band. SOB is integrated with MAC layer mechanisms: 1) Reserve Idle Spectrum Fragment (RISF) to reduce waiting time, 2) Reinforce Switch Notification (RSN) to reduce the residing time at a wrong channel, and 3) Multi-sender Agreement on Rendezvous CHannel (MARCH) to support multisender broadcasts. We implemented our scheme on the SORA platform. Experiment results validated communication through the overlapped band. Intensive simulation studies showed that our scheme drastically outperformed previous approach.

In vehicular safety systems, two types of safety messages are required: Emergency Safety Message (ESM) and Periodic Beacon Message (PBM). The ESM has to be disseminated within a specified area with stringent delay and delivery ratio requirements, while the PBM does not need to meet these requirements. For exchanging the safety messages in Vehicular Ad-hoc NETwork (VANET), Inter-Vehicle Communication (IVC) is necessary whose de facto standard is Dedicated Short-Range Communications (DSRC). However, the effective transmission range in the DSRC-based IVC is short since a signal can be attenuated due to blocking by obstacles. In order to cover a large dissemination area in the DSRC-based IVC, multi-hop dissemination is required, which however causes channel collision and network congestion. Moreover, the coexistence with PBMs aggravates the collision and the congestion, which make it hard to satisfy the requirements of the ESM dissemination. To overcome the limitation of the DSRC, we utilize an extra TV White Space (TVWS) band that has a large communication range for ESM disseminations, and exploit a DSRC band for 1) the exchange of control data and 2) the compensation of ESM reception errors. In this paper, we propose and analyze a distributed channel usage framework that exploits advantages of DSRC and TVWS bands for ESM dissemination under the existence of PBMs. Our scheme employs TVWS Channel Rendezvous Algorithm (TCRA), ensuring that vehicles within a dissemination area select the same channel with the ESM sender. To compensate ESM reception failures in a TVWS band, our scheme adopts Two-Way Recovery Algorithm (TWRA) that uses DSRC and TVWS bands for ESM retransmission. Further, we establish an analytical delivery ratio model that considers a delay bound of an ESM for optimal parameter selections. To the best of our knowledge, this is the first attempt to propose a distributed channel usage scheme that leverages the strengths of TVWS and DSRC bands for safety message dissemination. Through an in-depth simulation study, we show that the proposed scheme satisfies ESM requirements for latency and packet delivery ratio, and outperforms previous approaches in various vehicular scenarios.

Recently, academic researchers and car manufactures have directed major efforts to develop active safety systems for reducing car accidents. In particular, for work zones they proposed to use smart cones that send a warning radio message to vehicles when the smart cones detect the possibility of an accident. The dominant protocol for vehicular communication is Dedicated Short Range Communications (DSRC), where Enhanced Distributed Channel Access (EDCA) and Hybrid Coordination Function (HCF) Controlled Channel Access (HCCA) are the MAC protocol options. Even though two MAC protocols are specified in the standard, there has been no attempt to use two protocols cooperatively nor to study the performance of such hybrid system in an actual vehicular network. In this paper, we examine for the first time the performance of a system that exploits EDCA and HCCA concurrently in vehicular networks. In particular, we concentrate on interaction between two MAC protocols and how much the interaction affects system performance. In addition, we investigate whether the system is feasible for work zone safety applications, and suggest guidelines for improvements based on our simulation findings.

In this paper, we present an accurate throughput model of the IEEE 802.11e enhanced distributed coordination function (EDCF). Compared to the previous models, we newly consider a delay bound by predicting an effective retry limit and applying the retry limit to our model. To support this, the accurate description of the performance in a non-saturation condition is necessary, which is achieved by newly considering a queue length and a queue limit in the Markov chain. Simulation results show that our model is accurate in predicting the system throughput.