Reliable, low latency communication is vital for emerging vehicular applications, yet existing protocols, such as the new radio for vehicle-to-everything (NRV2X) Mode 2 encounter resource allocation conflicts in dense traffic. The growing data demands of future smart networks will force sidelink radios to resolve more sophisticated collisions within a few milliseconds while sustaining higher reliability. This study introduces smart predictive tracking and collision resolution (SPTCR), a novel protocol designed to enhance resource allocation in vehicular sidelink communications. SPTCR integrates a predictive resource allocation mechanism with an ID-based collision resolution strategy to improve communication reliability. Its performance is evaluated through analytical modeling and simulations conducted in both controlled environments and real-world scenarios modeled in simulation of urban mobility (SUMO). Results demonstrate that SPTCR outperforms NRV2X Mode 2 in high-traffic conditions, achieving up to a 32.1 % improvement in packet reception ratio (PRR) at a 500 m distance. Additionally, SPTCR significantly extends the communication range, ensuring robust performance across diverse traffic scenarios.

This paper proposes an integrated simulator combining WiLabV2Xsim, a MATLAB-based open-source simulator, and Virtual Test Drive (VTD), a traffic generation and vehicle dynamics simulator developed by HEXAGON, to evaluate Vehicle to Everything (V2X) communication performance in real road and driving environments. WiLabV2Xsim is a system-level simulator that implements Cellular-V2X and New Radio-V2X communication protocol stacks. Through VTD, it is possible to implement usecases standardized in 3GPP Technical Report (TR) 22.886 or evaluate V2X communication performance in real environments using virtual environments based on the Association for Standardization of Automation and Measuring Systems (ASAM) Open Scenario. Future research plans include evaluating various scenarios based on the 5G Automotive Association (5GAA) TR documents through the integrated simulator and conducting studies on wireless resource allocation and decentralized congestion control to enhance V2X communication performance.

Vehicle-to-everything (V2X) technology can facilitate platoon driving, which can improve traffic efficiency in cooperative-intelligent transportation systems (C-ITS). In platoon driving, vehicles share their driving information with each other, including their location and speed. However, in congested traffic situations, there is a higher likelihood of packet collision, as the vehicles in the same platoon are using the same resources. This paper analyzes the communication QoS degradation factors that occur when operating the cooperative adaptive cruise control (CACC)-based platoon driving service. In order to improve the reliability characteristics of the dynamic information exchange vehicle-to-vehicle (V2V) link for the CACC-based platoon driving service, this paper proposed the proactive V2X PC5 resource allocation algorithm using the extended 1-stage SCI. This paper finally showed the improved communication QoS performance of the system in which the CACC-based platoon driving service is operated through the proposed resource allocation algorithm.

This study analyzes the phenomenon of electromagnetic (EM) leakage that occurs through cables and explores the potential for information forensics using deep learning-based image-processing algorithms. We focus on the transition-minimized differential signaling (TMDS) interface to analyze information leakage caused by the inherent differential signal synchronization errors in video graphics controllers (VGC). Our analysis includes detailed mathematical modeling of the EM leakage phenomena from the video display unit (VDU) interface that uses the TMDS protocol. Furthermore, this study presents mathematical models for distortions and alterations caused by the VDU characteristics and its associated RF front-end system. Utilizing mathematical models of EM phenomena, this paper presents a method for creating training datasets for deep learning-based signal processing algorithms by generating and augmenting pseudo leakage signals (PLS) that closely resemble actual leakage signals. This study confirms the practical utility of signal enhancement models trained with generated and augmented PLS in real-world scenarios. Validation involves applying the trained model to measured actual VDU leakage signals and evaluating the results using image quality metrics: peak signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR), and the structural similarity index measure (SSIM). Ultimately, this study demonstrates the potential to develop deep learning models using theoretically generated PLS for VDU-targeted side-channel attacks, where collecting real training data poses a challenge. This suggests the potential for expanding into high-performance deep learning algorithms in future developments.

In the Industrial Internet of Things (IIoT), energy efficiency is a paramount concern as it directly affects operational longevity. Traditional approaches, like flooding for time synchronization, often result in redundant message transmissions, thereby wasting energy. This article introduces an intelligent neighbor-knowledge synchronization (INKS) method to mitigate this problem. The INKS algorithm leverages each node's understanding of its neighboring nodes to optimize the synchronization process, thereby reducing the total number of synchronization messages and conserving energy. The INKS is implemented and evaluated using real wireless sensor networks with varying configurations. The experimental results demonstrate their superior performance to existing techniques, such as rapid flooding multiple one-way broadcast time synchronization (RMTS). Additionally, the performance of INKS is evaluated through simulations conducted on large-scale networks. For the network topology of the four-way grid, the findings reveal that INKS reduces the number of transmitted messages by approximately 72% compared to RMTS. Moreover, INKS matches the efficiency of scheduling-based low-energy synchronization for IIoT.

Distributed congestion control (DCC) is a representative algorithm for improving the performance of Cellular-V2X (C-V2X) in dense vehicle scenarios. Since the existing DCC algorithms are not designed to respond to the target value of the Quality of Service (QoS) parameter adaptively, they can improve communication performance to some extent but do not guarantee the achievement of the target value. To solve this problem, we propose a deep Q network (DQN)-based QoS adaptive DCC algorithm in C-V2X Vehicle to Vehicle (V2V) communication. In particular, considering the limitations of the V2V network, where the exchange of state and reward information between vehicles is limited, we adopt a central controller (single agent) to train the congestion control policy and then distribute the completed policy to each vehicle for distributed execution. Simulation results show that the proposed algorithm satisfies the target QoS more effectively than the standardized ETSI DCC algorithm.

This brief presents a low-complexity I/Q (in-phase and quadrature components) imbalance calibration method for the transmitter using quadrature modulation. Impairments in analog quadrature modulator have a deleterious effect on the signal fidelity. Among the critical impairments, I/Q imbalance (gain and phase mismatches) deteriorates the residual sideband performance of the analog quadrature modulator degrading the error vector magnitude. Based on the theoretical mismatch analysis of the quadrature modulator, we propose a low-complexity I/Q imbalance extraction algorithm. After the parameter extraction, the transmitter is calibrated by imposing the counter imbalanced mismatch of the transmitter through the digital baseband. In comparison with existing I/Q imbalance calibration methods, the novelty of the proposed method lies in that: 1) only three spectrum measurements of the device-under-test are needed for extraction and calibration of gain and phase mismatches; 2) due to the blind nature of the calibration algorithm, the proposed approach can be readily applicable to an existing I/Q transmitter; 3) no extra hardware that degrades the calibration accuracy is required; and 4) due to the noniterative nature, the proposed method is faster and computationally more efficient than previously published methods.

Joint transmission across the cluster of radio remote heads (RRHs) by exploiting the centralized processing of the cloud-radio access network (C-RAN) is a promising technique to overcome the severe interference problems in ultra-dense small cell networks. In practical considerations, local clustering of networks is preferred over global clustering as the number of RRHs that can be jointly transmitted on the network is finite. In this study, we attempt to revisit the principles of the well-known affinity propagation (AP) clustering algorithms, especially for the naive method of determining the exemplar with a fixed threshold. To further explain the decision method, we propose a method to easily determine the threshold using the network map of converged value of messages generated by AP algorithm, by combining Otsu's threshold and density peak searching method with the existing AP clustering algorithm. The proposed algorithm provides higher spectral efficiency than the conventional AP algorithms as well as statically coordinated multi-point (CoMP) techniques, although it has similar execution time as the traditional AP algorithms.

This paper studies the spectral/energy efficiency (SE/EE) of a heterogeneous network with the backhaul enabled by low-resolution analog-to-digital converters (ADCs) quantized full-duplex massive multiple-input multiple-output (MIMO) over Rician channels. Backhaul communication is completed over two phases. During the first phase, the macro-cell (MC) base station (BS) deploys massive receive antennas and a few transmit antennas; the small-cell (SC) BSs employ large-scale receive antennas and a single transmit antenna. For the second phase, the roles of the transmit and receive antennas are switched. Due to the low-resolution ADCs, we account for quantization noise (QN). We characterize the joint impact of the number of antennas, self-interference, SC-to-SC interference, QN, and Rician K-factor. For the first phase, the SE is enhanced with the massive receive antennas and the loss due to QN is limited. For the second phase, the desired signal and QN have the same order. Therefore, the SE saturates with the massive transmit antennas. As the Rician K-factor increases, the SE converges. Power scaling laws are derived to demonstrate that the transmit power can be scaled down proportionally to the massive antennas. We investigate the EE/SE trade-offs. The envelope of the EE/SE region grows with increase in the Rician K-factor.

In this paper, we consider a decode-and-forward (DF) two-way relay (TWR) system in power line communication (PLC). The DF TWR employs physical- layer network coding (PNC). We derive analytic expressions for the average capacity and the outage probability of the system over a log-normal fading channel. Analytic results are verified through Monte Carlo simulations. From the results, the TWR is able to mitigate the half-duplex (HD) spectral efficiency loss incurred by one-way relaying. The impact of the impulsive noise on the system performance is also highlighted in the simulation results. It is shown that higher impulsive probability degrades system performance.

In this paper, we propose a channel estimation method based on a complex valued regression of the neural network for the IEEE 802.11p standard. It consists of the complex weighted summation optimized by feedforward neural network with backpropagation algorithm using initial estimated channel of the pilot and the long preamble. It also exploits the shift matrix in order to mitigate the effect from a systemic problems in IEEE 802.11p standards. The major problems of IEEE 802.11p standard are wide bandwidth of 10 MHz consisting of 64 subcarriers and relatively insufficient four pilot subcarriers at single ODFM symbol, which are unsuitable for a channel of vehicular environment. Despite these problems, the proposed method performs better than the conventional channel estimation methods. The performance of proposed scheme is provided with the comparison between constructed data pilots (CDP), Spectral Temporal Averaging (STA), and proposed scheme. The proposed channel estimation scheme has low mean square error (MSE) and bit error rate (BER) throughout the whole SNR region. It is the result from properly trained weight. At the low SNR region, especially, the performance of proposed scheme is much better than CDP and STA scheme. It is because of the noise suppression effect caused by a weighted summation algorithm.

The optimal number of clusters (K) differs depending on the radio remote head (RRH) density. This paper verifies that the K values cannot be met by the conventional affinity propagation (AP) clustering algorithm. In an ultra-dense network (UDN) environment, the density of RRH is a very important factor for the bender because it is directly related to the cost of configuring the wireless communication network. Likewise, in order to provide the optimal communication environment to the user in the UDN environment, it is necessary to enable flexible clustering according to changing channel environment by utilizing semi-dynamic clustering technology. As a result, we propose an AP algorithm that finds a better K value than the conventional method. To this end, the proposed algorithm additionally utilizes a non-coordinated multi-point (CoMP) interference power that varies depending on the RRH density, user position, and the variations in propagation channel. The simulation results show that the proposed algorithm shows a better average capacity than the conventional algorithm.

This brief presents a low-complexity I/Q (in-phase and quadrature components) imbalance calibration method for the transmitter using quadrature modulation. Impairments in analog quadrature modulator have a deleterious effect on the signal fidelity. Among the critical impairments, I/Q imbalance (gain and phase mismatches) deteriorates the residual sideband performance of the analog quadrature modulator degrading the error vector magnitude. Based on the theoretical mismatch analysis of the quadrature modulator, we propose a low-complexity I/Q imbalance extraction algorithm. After the parameter extraction, the transmitter is calibrated by imposing the counter imbalanced mismatch of the transmitter through the digital baseband. In comparison with existing I/Q imbalance calibration methods, the novelty of the proposed method lies in that: 1) only three spectrum measurements of the device-under-test are needed for extraction and calibration of gain and phase mismatches; 2) due to the blind nature of the calibration algorithm, the proposed approach can be readily applicable to an existing I/Q transmitter; 3) no extra hardware that degrades the calibration accuracy is required; and 4) due to the noniterative nature, the proposed method is faster and computationally more efficient than previously published methods.

Polarization division multiple access (PDMA) is a method to simultaneously transmit two independent signals by using vertical and horizontal polarization in the same frequency band. In PDMA systems, the received signal can experience significant interference from cross-polarized signals if the transmit and receive antennas are misaligned in terms of polarization state. In this paper, a precoding technique to solve this problem is discussed and a channel model to disentangle vertical and horizontal components from the received signal and include the rotation of receive antenna is proposed. The precoding technique is designed and analyzed using a channel model assuming a line-of-sight environment. To measure the performance of the precoding technique, a testbed is implemented using a software-defined radio platform. Simulation and measurement show that enhanced channel gain is achieved even when the polarization state between the transmit and receive antennas is mismatched. Comparison between simulation and measurements proves a basic and crucial principle concerning the capability of controlling the polarization state of a transmitted signal.

Spectrum sharing is an elegant solution to the problem of spectrum scarcity. A novel advanced approach is developed in this study to enable power-controlled cellular networks coexist with primary rotating radars. A canonical scenario is considered where a single cellular BS interferes with single rotating radar. A new mathematical model is also developed using log-normal approximations to capture the aggregate interference from multiple power-controlled cellular systems. The cellular system transmits at high power for over 83.3% of time due to the slow radar antenna rotation and narrow main beam width. Our numerical results show that the power control drastically reduces the required separation distances between the two systems. The log-normal approximation gives results which virtually match the results of our simulation.

In this paper, we study spectral coexistence between rotating radar and power-controlled cellular networks in radar bands. For two systems to spectrally coexist, they must be able to operate effectively without causing harmful electromagnetic interference to each other. Very short radar-cellular system separation distances are required during 83.3% of time due to the narrow main beam width of the rotational radar antenna. We propose a spatio-temporal analytical approach with adaptive base station (BS) power control for adjacent spectrum sharing between the two systems. We develop a new model for the aggregate interference from power-controlled cellular BSs using log-normal approximation. The cellular system is allowed to transmit at high power when the radar antenna's main beam is pointing elsewhere from it. On the other hand, the cellular system reduces its transmit power only for a short period when the radar directional antenna main beam is pointing toward it. We use the degradation of the radar signal-to-interference plus noise ratio and cellular outage probability as our performance metrics. Numerical results show that power control of cellular BS highly reduces separation distance between the BS and radar, while yielding marginal degradation of outage performance. In addition, the mathematical results given by the log-normal approximation closely follow our simulated results. Detail system level assessments and investigations are presented to comprehensively understand secondary access to this band opportunistically.

This paper analyzes the effects of polarization-mismatch and space-correlation to a multiple-input and single-output (MISO) channel which is observable in the near future cellular communications environments such as large-scale antenna arrays and small cells. The analysis is based on a polarization-mismatched and space-correlated MISO channel which is modeled from the conventional dual-polarized channel. In the MISO channel, polarization-mismatch is described by the polarization-mismatch angle which is uniformly distributed from 0 to the maximum polarization-mismatch angle and space-correlation is described by the exponential correlation model. Assuming high SNR, approximate expressions of the ergodic capacity are derived as a function of the transmit power, number of transmit antennas, maximum polarization-mismatch angle, and space-correlation coefficient in four representative environments: narrowly or widely spread polarization-mismatch angles and slightly or highly correlated channels. Further, the capacity loss introduced by polarization-mismatch and space-correlation is derived with respect to the maximum polarization-mismatch angle and space-correlation coefficient. It is shown that the capacity loss introduced by polarization-mismatch is upper bounded by 2 bit/s/Hz. Whereas, the capacity loss introduced by space-correlation increase with the number of transmit antennas and is upper bounded by 0.832 bit/s/Hz. Required resources to compensate for the capacity loss is derived as well.

In this paper we develop a tractable framework for SINR analysis in downlink heterogeneous cellular networks (HCNs) with flexible cell association policies. The HCN is modeled as a multi-tier cellular network where each tier's base stations (BSs) are randomly located and have a particular transmit power, path loss exponent, spatial density, and bias towards admitting mobile users. For example, as compared to macrocells, picocells would usually have lower transmit power, higher path loss exponent (lower antennas), higher spatial density (many picocells per macrocell), and a positive bias so that macrocell users are actively encouraged to use the more lightly loaded picocells. In the present paper we implicitly assume all base stations have full queues; future work should relax this. For this model, we derive the outage probability of a typical user in the whole network or a certain tier, which is equivalently the downlink SINR cumulative distribution function. The results are accurate for all SINRs, and their expressions admit quite simple closed-forms in some plausible special cases. We also derive the average ergodic rate of the typical user, and the minimum average user throughput - the smallest value among the average user throughputs supported by one cell in each tier. We observe that neither the number of BSs or tiers changes the outage probability or average ergodic rate in an interference-limited full-loaded HCN with unbiased cell association (no biasing), and observe how biasing alters the various metrics.

In this paper we develop a tractable framework for SINR analysis in downlink heterogeneous cellular networks (HCNs) with flexible cell association. The HCN is modeled as a multi-tier cellular network where each tier's base stations (BSs) are randomly located and have a unique transmit power, path loss exponent, spatial density, and bias towards admitting users. We implicitly assume every BS has full queues. From this model, we derive the outage probability of a typical user in the network, which can be viewed as a spatial average of SINR over all users in the network. We observe that deploying more or less BSs does not change the outage probability in interference-limited HCN with unbiased cell association, and observe how biasing affects the metric.

A fundamental choice in femtocell deployments is the set of users which are allowed to access each femtocell. Closed access restricts the set to specifically registered users, while open access allows any mobile subscriber to use any femtocell. The main results of the paper are lemmas which provide expressions for the SINR distribution for various zones within a cell as a function of this MBS-femto distance. The average sum throughput (or any other SINR-based metric) of home and cellular users under open and closed access can be readily determined from these expressions. We show that unlike in the uplink, the interests of home and cellular users are in conflict, with home users preferring closed access and cellular users preferring open access. The conflict is most pronounced for femtocells near the cell edge, when there are many cellular users and fewer femtocells.

This paper proposes a self-optimized coverage coordination scheme for two-tier femtocell networks, in which a femtocell base station adjusts the transmit power based on the statistics of the signal and the interference power that is measured at a femtocell downlink. Furthermore, an analytic expression is derived for the coverage leakage probability that a femtocell coverage area leaks into an outdoor macrocell. The coverage analysis is verified by simulation, which shows that the proposed scheme provides sufficient indoor femtocell coverage and that the femtocell coverage does not leak into an outdoor macrocell.

This paper proposes two interference mitigation strategies that adjust the maximum transmit power of femtocell users to suppress the cross-tier interference at a macrocell base station (BS). The open-loop and the closed-loop control suppress the cross-tier interference less than a fixed threshold and an adaptive threshold based on the noise and interference (NI) level at the macrocell BS, respectively. Simulation results show that both schemes effectively compensate the uplink throughput degradation of the macrocell BS due to the cross-tier interference and that the closed-loop control provides better femtocell throughput than the open-loop control at a minimal cost of macrocell throughput.