In developing a site- and scenario-specific wireless channel emulator, a computationally efficient shadowing model for vehicles is essential for dynamic emulation with constrained computational resources. In this work, a single-dominant-ray knife-edge diffraction model is proposed to approximate the overall shadowing gain from a cuboid-shaped vehicle by a single diffraction ray. The proposed model is validated with full-wave simulations at 760 MHz. The efficacy of the model is demonstrated through a comparison of the coefficient of determination with that obtained from full-wave simulations and the 3GPP rectangular screen model.

Real-time access edge computing demands access networks to connect a lot of IoT devices to edge servers with ultra-low latency. A lot of connected devices will cause the data bursts and sudden increase of delay (i.e. micro-burst) in the upstream queues in gateways. This study proposes a novel method for detecting such bursts to ensure low-latency communication. The proposed method leverages the periodic messaging behavior of certain IoT devices. It detects bursts based on the variation in the arrival times of messages transmitted from already deployed multiple IoT devices. This approach enables monitoring of delays and detecting bursts without the need for additional probes or modifications to gateways. The study validates the detection accuracy and feasibility through numerical analysis and simulations.

We design geometrically shaped four-dimensional (4D) modulation formats for 5-7 bits/4D symbol with an autoencoder, which is one of the deep learning applications, using pre-training with 4D formats based on 2-ary amplitude 8-ary phase-shift keying. The numerical evaluation shows that the obtained 4D modulation formats have 0.5-0.7dB signal-to-noise sensitivity gains in terms of normalized generalized mutual information (NGMI) as well as bit error ratio (BER) performances. Furthermore, we show the NGMI and BER performances of these 4D modulation formats are almost equivalent to those of probabilistic amplitude shaping with enumerative sphere shaping with a block length of 20.

The unmanned aerial vehicle (UAV) network has been widely studied for for various metrics, e.g., flexible and reliable. Among these metrics, delay is a major performance metric for UAV network. This paper models a UAV network with hybrid wirless and power line communication (PLC) where data is first relayed through a wireless channel and then transmitted through a PLC system. We analysis the delay performance of the hybrid network via SNC approach. Numerical results shows how various parameters affect the delay performance under the service capability derived.

We analyze the outage probability for a massive multiple-input-multiple-output (MIMO) system employing maximum ratio transmission (MRT) under a multi-cell scenario. As cells become smaller, it will be even more necessary to analyze the outage probability considering interference from neighboring cells. Under a multi-cell environment, communication performance can be substantially compromised by channel estimation errors and inter-cell interference (ICI). We investigate the distribution of signal-to-interference and noise ratio (SINR) in a massive MIMO system and formulate a novel mathematical model for the outage probability. Simulation results show the validity of the derived mathematical model.

A Piggyback network, which is a store-carry-forward network organized by working mobilities of delivery trucks and serving robots, realizes a large-scale data distribution platform. However, when the working mobilities participate in the Piggyback network, the data carrying and forwarding tasks influence their original tasks, resulting in additional transfer costs necessitating appropriate data transfer management. This study proposes a data-transfer management scheme in the Piggyback network. We have developed an algorithm based on the Stackelberg game to balance the end-to-end throughput and the cost required by working mobilities for each data delivery, and we have formulated a rule for the users to select the best mobility based on the balanced throughput and costs. The simulation results show that the proposed method maximizes the utility and achieves a high average throughput of the entire network.

In recent years, various information has been delivered through web pages using HTTP, making the acceleration of web page display a crucial concern. While HTTP/3 achieves the acceleration of web pages through prioritizing resources, there exists a challenge in establishing an optimal prioritization method. In this study, we addressed this issue by developing a novel approach that dynamically selects scheduling methods based on the network environment, comparing the performance of HTTP/3 prioritization methods across various network conditions. As a result, we demonstrated a reduction in page load times compared to conventional methods, particularly in network environments with low RTTs and low packet loss rates or high RTTs and high packet loss rates.

The first quantum insertion code is the four qubits code given by Hagiwara in 2021. Since then, several quantum insertion codes have been proposed, but they are all unrelated to Hagiwara’s four qubits code. This article provides a new class of quantum single insertion codes that include the Hagiwara code. Furthermore, this construction gives a new decoder for insertion errors in the Hagiwara codes.

Traditional direct-current biased optical orthogonal frequency division multiplexing (DCO-OFDM) achieves unipolar signaling by adding a direct current (DC) bias and performing clipping. To suppress signal nonlinearity distortion caused by clipping, the DC bias needs to be set at a higher level, which results in low power efficiency of the DCO-OFDM. A scheme named Selectively Biased Optical OFDM (SBO-OFDM) was proposed in this letter. SBO-OFDM multiplies the OFDM signals with random phase sequences, selects the signal that requires the least amount of bias for transmission, and dynamically adds the bias based on signal variations to improve power efficiency. The experimental results demonstrate that the proposed SBO-OFDM exhibits a significant decrease in requirement of the normalized optical bit energy to noise power ratio [E_b(opt)/N_o] compared to DCO-OFDM, ACO-OFDM, and PAM-DMT at a BER of 10^-3. The results indicate that SBO-OFDM outperforms traditional optical OFDM (O-OFDM) in terms of power efficiency and have better BER performance than traditional DCO-OFDM.

In the realm of V2X (Vehicle to Everything) communication research, privacy is upheld through the use of pseudonym technology. However, employing pseudonyms necessitates the distribution of Certificate Revocation Lists (CRLs), posing challenges as the CRL size grows with the increase in invalidated pseudonyms, congesting communication bandwidth. To address this, our proposed method distributes CRLs exclusively to a lead vehicle, tasked with validating pseudonyms for nearby vehicles. Simulation results demonstrate the efficacy of our approach, reducing communication traffic and maintaining delays below 100ms. The proposed technique effectively mitigates the challenges associated with pseudonym-based CRL distribution in V2X communication.

Frequency-Shift Chirp Modulation (FSCM) also known as LoRa modulation, enables long-distance transmission with low power consumption for Internet of Things (IOT), but has a limited transmission rate. Frequency-shift chirp spread spectrum system with index modulation (FSCSS_IM) introduces index modulation to improve the transmission rate of FSCM at the cost of high demodulation complexity. This letter propose an improved FSCSS_IM scheme to further improve the transmission rate of FSCM by adding indexes with equal values to the codebook. And then we design a low complexity demodulation algorithm which employs index matching to replace the index search matching algorithm in FSCSS_IM. Finally, we derive the approximate BER expression of the proposed scheme. The analysis and simulation results show that the transmission rate of the proposed scheme is up to 91.7% higher than that of the FSCM and 8.3% higher than that of the existing FSCSS_IM scheme, and the demodulation algorithm has the almost the same computational complexity as the FSCM and much lower than that of FSCSS_IM.

In this letter, we consider socially-aware ICN (Information-Centric Networking) and empirically reveal the impact of user’s sociality, which is corresponding to human factors on social media, on the content caching of ICN. To this end, among user’s sociality, we focus on the information propagation behavior and the community structure, and describe a sociality-aware ICN model incorporating these two sociality. Also, we investigate the impact of these two sociality on the performance of ICN. Our key finding is, for instance, that the effectiveness of cache is significantly affected by the community structure rather than the information propagation behavior.