As three-dimensional acquisition technologies like LiDAR cameras advance, the need for efficient transmission of 3D point clouds is becoming increasingly important. In this paper, we present a novel semantic communication (SemCom) approach for efficient 3D point cloud transmission. Different from existing methods that rely on downsampling and feature extraction for compression, our approach utilizes a parallel structure to separately extract both global and local information from point clouds. This system is composed of five key components: local semantic encoder, global semantic encoder, channel encoder, channel decoder, and semantic decoder. Our numerical results indicate that this approach surpasses both the traditional Octree compression methodology and alternative deep learning-based strategies in terms of reconstruction quality. Moreover, our system is capable of achieving high-quality point cloud reconstruction under adverse channel conditions, specifically maintaining a reconstruction quality of over 37dB even with severe channel noise.

Nowadays, wireless charging has become one of the most popular technologies in Internet of Things (IoT), which makes electric devices battery free and flexible. The electromagnetic coupling in antenna design is important to push the range limits beyond the near field. Previous studies did not consider the coupling among coils and they do not work for the far-field scenarios. In this article, we design an antenna for wireless charging that can expand the charging distance from 5 to 55 cm, a ten-fold improvement compared to the near-field commercial communication distance according to the simulation results. Specifically, it is practical to take into account the coupling of every two coils when we analyze the transmit power. Therefore, we first model the near-field signal propagation with higher-order factors, and establish the relationship between the geometry parameters and the transmit power. Then, since our problem is extremely nonlinear, we design the greedy search algorithm and narrow down the feasible region to obtain the optimal parameters of the coils that can maximize the charging distance. An Ansoft-High Frequency Structure Simulator is adopted to simulate the performance of the coil models, and the results show that square coils achieve the best performance. We also discuss the best arrangement of multiple coil antennas. The impact of the signal phase is also introduced and the best combination of signal phases from different transmit coils is analyzed.

The signal phase is one of the most important metrics in RFID-based sensing, which is a useful technique enabling many significant applications. However, existing approaches of RFID-based sensing are often restricted in terms of the sensing capability or accuracy, due to the phase entanglement problem: the phase of the RFID signal is jointly affected by multiple factors, and the change in the signal phase cannot be directly attributed to any one of them. In order to tackle this problem, we propose RF-Prism, a versatile sensing approach that can simultaneously infer multiple physical factors (i.e., location, orientation, and material of targets), purely based on the phase readings. RF-Prism includes a comprehensive model to describe how different physical factors affect the phase of the received signal, and a complete design to disentangle the phase in the multi-frequency and multi-antenna scenario. We implement RF-Prism and evaluate its performance with extensive experiments. The results show that RF-Prism simultaneously achieves a mean localization error of$\text{7.61}~cm$, a mean orientation error of 9.83 degrees, a mean tracking error of$\text{6.12}~cm$, and 87.9% material identification accuracy, which outperforms state-of-the-art approaches.

Hybrid long-range (LoRa) network is a promising approach to overcome the half-duplex issue in traditional LoRa networks, increasing the network efficiency and confidence for today's fast-developing smart city services. Gateways (GWs) in hybrid LoRa networks link the end devices (EDs) and the Netserver and have a great impact on the system performance. Previous results on GW planning cannot be directly applied to hybrid LoRa networks since the heterogeneous EDs require different redundancy of coverage. Furthermore, the spreading factors (SFs) which determine the system performance should be considered concurrently. In this article, in order to find the optimal planning scheme, i.e., deciding the number and locations of GWs in the hybrid LoRa network, we propose a heterogeneous redundant coverage solution to meet the requirements of the heterogeneous EDs using the same or different frequencies for uplink and downlink. Specifically, we formulate this problem as a point coverage problem that meets the requirements of EDs. The deleted greedy algorithm (DGA) and the nondeleted greedy algorithm (NDGA) are designed to solve this problem, in which the DGA shows better performance when compared to NDGA. Furthermore, we build models of system performance and analyze the system throughput and energy efficiency based on SFs. The simulation results show that our solution gains more system throughput and energy efficiency than a one-coverage solution.

Imagine when you line up in a store, the person in front of you can make you pay her bill by using a passive wearable device that forces a scan of your credit card or mobile phones without your awareness. An important assumption of today's near-field communication (NFC)-enabled cards is the limited communication range between the commercial reader and the NFC cards. Previous approaches effectively used mobile phones and active relays to break the range limit of NFC propagation for the NFC attack. However, these approaches require a power supply and protocol modification when mobile phones or active relays transmit NFC signals. We propose ReCoil, a system that uses passive relays to attack NFC-enabled mobile phones or cards by expanding the communication range of NFC to 49.6 cm, an obvious improvement over its intended commercial distance. ReCoil is a magnetically coupled resonant wireless power transfer system, which optimizes the energy transfer by searching the optimal geometry parameters. Specifically, we first narrow down the feasible area reasonably and design the ReCoil-greedy algorithm such that the relays absorb the maximum energy from the reader. In order to reroute the signal to pass over the surface of the human body, we then design a half waistband by carefully analyzing the impact of the distance and orientation between two coils on the mutual inductance. Then, three more coils are added to the system to keep enlarging the communication range. Finally, extensive experiment results validate our analysis, showing that our passive relays consisting of common copper wires and tunable capacitors can expand the range of NFC to 49.6 centimeters.

Due to the advantages including low cost, low power, massive connections, and wide coverage, and with the assistance of fog computing to achieve low latency, location awareness, etc., narrow-band Internet of Things (NB-IoT) can be widely applied in industry. Many NB-IoT industrial applications need a positioning feature for tracking, fault localization and fast repair, etc. When dedicated positioning systems, e.g., Global Position System, are unavailable for a low-power, low-cost NB-IoT device, it is necessary to rely on terrestrial cellular network for localization. Existing performance studies in NB-IoT cellular-network-based positioning have been mostly carried out by targeting deterministic scenarios. However, it is hard to provide general insights with changing system design parameters and propagation effects, due to the random variations in device location, network coverage, channel condition, etc. This paper develops a general analytical model to study the NB-IoT positioning performance. The location randomness of the device to be localized is considered through the distance distributions between the device and its surrounding evolved node Bs (eNBs). This makes it possible for using the powerful probabilistic distance-based tools from geometric probability to derive the probability that at least a fixed number of participating eNBs can be heard by the device. The model considers both the interference and the NB-IoT system-related parameter settings. It also includes modeling the eNB transmission coordination and traffic load. The obtained results reveal how participating eNBs impact the NB-IoT positioning performance, with the effects of a set of parameter settings investigated.

Narrowband Internet of Things (NB-IoT) is one of the most promising technologies for low-power, wide-area, and low-traffic applications. In NB-IoT, random access is implemented in media access control layer to resolve the channel contention conflict among multiple user equipments (TIEs), and is crucial to the throughput performance of NB-IoT. Previous results in long-term evolution cannot be directly applied due to specification differences. In this paper, we take the first attempt to systematically analyze the performance of random access in NB-IoT. First, after extensively studying the backoff mechanism, we characterize the probability that a TIE initiates random access, the probability that a packet is transmitted successfully and the probability that a channel is busy. Then, we define each TIE's buffer as a first-in-first-out queue. We employ Markov chain to model retransmission number caused by collisions and the length of the queue simultaneously. By exploiting the characteristic of the steady-state distribution of the Markov chain, the above three probabilities in steady state can be obtained explicitly. Based on these probabilities, we calculate the system throughput in terms of TIE number, packet generation rate, retransmission number, and the length of the queue. Finally, we investigate the system throughput and conduct extensive simulations under various parameters, which validate our analysis.

Recently, narrowband Internet of Things (NB-IoT), one of the most promising low power wide area (LPWA) technologies, has attracted much attention from both academia and industry. It has great potential to meet the huge demand for machine-type communications in the era of IoT. To facilitate research on and application of NB-IoT, in this paper, we design a system that includes NB devices, an IoT cloud platform, an application server, and a user app. The core component of the system is to build a development board that integrates an NB-IoT communication module and a subscriber identification module, a micro-controller unit and power management modules. We also provide a firmware design for NB device wake-up, data sensing, computing and communication, and the IoT cloud configuration for data storage and analysis. We further introduce a framework on how to apply the proposed system to specific applications. The proposed system provides an easy approach to academic research as well as commercial applications.