Accurately forecasting heavy rainfall disasters requires collecting wide-area maritime weather data obtained by ocean buoys without communication interruption. A low-cost approach to collect these data is a maritime sensor network using altitude-controllable light balloons with only a limited number of altitude controls. This paper analyzes the impact of the altitude controls on the spatial coverage of buoys that establish communication links with balloons within an allowable interruption duration in this maritime sensor network. To this end, this paper formulates a buoy coverage maximization problem with wind-dependent trajectories of altitude-controllable light balloons based on altitude controls and solves this problem. Our simulation results highlighted that the optimally altitudecontrolled balloons communicated with 67% of the buoys without an interruption duration exceeding one hour. Our results also showed that optimally altitude-controlled balloons achieved a 264% larger number of buoys within the allowable interruption than free-floating balloons.

In global navigation satellite system (GNSS) positioning, Doppler shift-based methods suffer from low accuracy due to the low dynamics and high altitude of medium Earth orbit (MEO) satellites. In contrast, low Earth orbit (LEO) satellites, such as Starlink, exhibit high dynamics and low altitude, leading to a significant Doppler shift effect that can enhance user terminal (UT) positioning accuracy. However, the accuracy of Doppler-based positioning is influenced mainly by the Doppler dilution of precision (DDOP) of the satellites, which quantifies the influence of satellite velocity direction and geometric diversity. Unlike conventional geometric dilution of precision (GDOP), which only quantifies the satellite's geometric diversity, DDOP accounts for velocity vectors, making it a critical factor in Doppler-based positioning. This paper presents an intuitive analysis of DDOP and drives the Doppler geometry matrix. To evaluate the DDOP performance of Starlink satellites and GNSS, we calculate the DDOP values for evenly-spaced random places on Earth. A simulator GUI is designed to calculate the DDOP value on any place on Earth. Moreover, we establish the correlation between DDOP and Doppler-based positioning accuracy, demonstrating that lower DDOP values yield higher positioning accuracy. Our numerical analysis also confirms that Starlink LEO satellites offer significantly better DDOP than GNSS, underscoring its potential as an alternative positioning solution, particularly in the GNSS-denied environment.

This paper proposes a novel proactive deployment framework for multiple aerial base stations (ABSs) to enhance the resilience of cellular networks against post-disaster disruptions. Unlike conventional approaches that optimize the ABS deployment separately for pre and post-disaster conditions, our proposed framework jointly optimizes the ABS deployment providing high-quality services continuously from predisaster to post-disaster environments. By formulating the joint optimization problem, our strategy maximizes the minimum user satisfaction before disasters and the user coverage after disasters. Our simulation results demonstrated that our strategy significantly outperformed the existing strategies by achieving the pre and post-disaster network performance while requiring only a marginal increase in the number of ABSs.

This paper analyzes the packet reception ratio (PRR) in unmanned aerial vehicle (UAV)-to-UAV communications (U2U) in a realistic urban environment considering 3D blockage effects by buildings and interference from other UAVs. Buildings are generated based on real-world data, leading to mixed and non-homogeneous building profiles beyond the assumptions of existing mathematical models. To this end, we use stochastic simulations to analyze the PRR dynamics and the trade-off in the line-of-sight (LoS) conditions for the communication and interference links under realistic blockage effects. Our findings have important implications for U2U deployment in future smart cities. In particular, the simulation results reveal the importance of incorporating real-world building data and performing a joint analysis on the number of UAVs and their operating height range for different sub-regions with varying building profiles.

We propose an analytical model to evaluate the performance of slotted ALOHA with NOMA for mMTC under the assumption that base stations and devices are distributed according to mutually independent stationary point processes. For NOMA, we consider a simple scenario in which perfect interference cancellation can be conducted at each base station. As performance metrics, we focus on the probability of a device successfully transmitting data to the nearest base station (transmission success probability) and the expected number of devices from which a base station can correctly decode the signals (throughput of base station). We establish analytical expressions for the two performance metrics for three schemes: simple slotted ALOHA, slotted ALOHA with interference cancellation, and slotted ALOHA with power control. Through several numerical experiments, we show that the application of interference cancellation improves the throughput by up to 20%; however, the application of interference cancellation does not solve the near-far problem. We also show that the application of power control solves the near-far problem but significantly degrades the performance of slotted ALOHA.

This paper analyzes the impacts of realistic blockage effects by buildings for the packet reception ratio (PRR) in unmanned aerial vehicle (UAV)-to-UAV communications (U2U). The key idea is to generate buildings based on real-world data on an urban landscape, i.e., more mixed and inhomogeneous building profiles than the existing mathematical models, to simulate the PRR stochastically. This key idea enables us to capture the impact of such inhomogeneous blockage profiles on line-of-sight conditions in a communication link between target UAVs and interference links from other UAVs, providing a key trade-off in the PRR. Our simulation results highlight this trade-off as the number of UAVs and UAV heights change. The results also illustrate how the inhomogeneous building profiles affect the PRR in each sub-region of the urban landscape under study. Our findings have important implications for U2U in real-world urban areas by using realistic building models and performing a joint analysis on the number of UAVs and their operating height across different sub-regions within the urban area of interest.

This paper maximizes the throughput in the grant-free power-domain non-orthogonal multiple access (GF-NOMA) for users distributed in a 3D space by optimizing the power level selection strategy. To maximize the throughput, we propose a stochastic geometry-based analytical model for an offered load per level (called per-level offered load), deciding the throughput, for 3D distributed users. The key idea is to reflect line-of-sight conditions depending on the altitudes of such users to power level constraints. This key idea enables our model to stochastically limit selectable power levels along with LoS conditions and derive a selection strategy suitable for offloading an inhomogeneous per-level offered load caused by LoS conditions to maximize the throughput. Our optimization results showed that the derived power level selection strategy achieved 16% higher throughput than the baseline strategy, where each user randomly selects a power level under the power level constraints.

This paper proposes a scalable framework to analyze the throughput of the grant-free power-domain nonorthogonal multiple access (GF-NOMA) and presents the achievable performance in the optimized offered load at each power level (called per-level offered load) by using our framework. Our analytical model reflects packet errors caused by power collisions, characterized by GF-NOMA, based on the power level design guaranteeing the required signal-to-interference-and-noise ratio (SINR). This key idea enables analyzing the throughput of a large-scale GF-NOMA system more accurately than the existing analytical models. Also, this key idea enables optimizing the per-level offered load rather than a uniform one in typical optimization problems related to the throughput: the throughput maximization or energy minimization problem with a throughput condition. Our analytical results highlight some key insights into designing future access control methods in GF-NOMA. First, our analytical model achieves an approximation error of only 0.4% for the exact throughput obtained by the exhaustive search at five power levels; the existing analytical model provides an approximation error of 25%. Next, our proposed framework highlights that the optimal per-level offered load restrictively improves the throughput above the optimally uniform per-level offered load. Finally, our proposed framework discovers a 27 more energy-efficient per-level offered load than the existing framework at five power levels while providing higher throughput than the optimally uniform per-level offered load.

This article proposes a stochastic geometry-based analytical framework for the throughput of the grant-free power-domain nonorthogonal multiple access (GF-NOMA) with user-specific constraints of selectable power levels and analyzes the achievable throughput. Our analytical framework uses stochastic geometry to reflect selectable power levels constrained by the maximum transmission power and channel of each user to an inhomogeneous offered load per level. This key idea enables our framework to analyze the throughput bounded by the geographical user distribution and derive a suitable selection strategy of power levels under the constraint more accurately than the existing models. Our analytical results showed that our framework analyzed the throughput with only an analysis error of 0.1% compared with the Monte Carlo simulations, although the existing model overestimated 58% higher throughput. By using the proposed analytical model, our results presented decreasing the achievable throughput with increasing the coverage range. This article also proposes a heuristic method based on our proposed analytical model to derive a suitable selection strategy of power levels. Our results highlight that the derived selection strategy on our analytical framework achieved 20% higher throughput than the baseline strategy, where each user randomly selects a power level under the power-level constraint.

This paper proposes an optimal dynamic transmission power allocation mechanism for multiple users to maximize mobile ad hoc networks (MANETs) energy efficiency. With the widespread adoption of the internet of things (IoT), energy efficiency is a crucial metric in MANETs constrained by the battery capacity of portable devices. Specifically, a practical scheme needs to be explored that ensures the quality of service (QoS) while minimizing battery costs. Previous studies mainly focus on designing power-manageable components and achieving predictive mechanisms at the circuit or system layer. In contrast to the traditional approaches, we jointly consider power management and multiuser cooperative mobility for energy efficiency maximization. On the one hand, we formulate the dynamic power allocation schemes with multiuser cooperative mobility strategies into the infinite-horizon time average problems. On the other hand, an algorithm based on Lyapunov optimization is developed to obtain the optimum, i.e., dynamic power allocation based on the multiuser cooperative mobility (DPA-MCM) algorithm. Numerical simulations show that the proposed algorithm improves the energy efficiency by up to 27.84 % compared to the previous method, demonstrating the effectiveness.

This paper proposes a retransmission or 2-shot method using the cross-slot SIC for the grant-free power-domain non-orthogonal multiple access (GF-NOMA) in the massive machine-type communications (mMTC). The proposed method allows only the users experiencing power collisions to retransmit their packets in a quasi-coordinated fashion by order of IDs of pilot sequences. Our second-shot mechanism enhances the impacts of cross-slot SIC to recover packet errors in the first transmission due to power collisions. Our simulation results highlight that the proposed method provides 32% higher throughput than the baseline method retransmitting all the error packets.

This paper analyzes the packet reception ratio (PRR) of direct communications between unmanned aerial vehicles (UAVs), i.e., UAV-to-UAV (U2U), by using stochastic geometry tools, focusing on UAV heights. In U2U, a receiving UAV (called a UAV-Rx) experiences better line-of-sight (LoS) conditions of its communication and interference links with other UAVs distributed in a three-dimensional space at its higher height. The balance of LoS conditions of these links decides the PRR of U2U. To analyze the characteristics, we derived a closed-form expression of the PRR of U2U. Our analysis highlighted that the PRR of U2U decreased and then increased as the height of a UAV-Rx increased at the distance of the communication link of 100 m in the dense urban model, and the UAV-Rx experienced the bottom PRR at its height of 32.5 m, depending on the building heights.

We propose an analytical model to evaluate the performance of NOMA-based slotted ALOHA for mMTC under the assumption that base stations and devices are distributed according to mutually independent stationary point processes. For the NOMA, we consider a simple scenario in which perfect interference cancellation can be conducted at each base station. As performance metrics, we focus on the probability for a device successfully transmitting data to the nearest base station (transmission success probability) and the expected number of devices from which a base station can correctly decode the signals (throughput of a base station). We establish a universal relationship between these two performance metrics that holds for general stationary point processes, including Poisson point processes. Using this universal relationship, we derive analytical expressions for the two metrics for the case in which the base stations and devices are distributed according to mutually independent Poisson point processes. Numerical experiments using simulations show that throughput can be improved by up to 15% compared to the case where interference cancellation is not applied.

This paper presents the optimal position of an aerial base station (ABS) by unmanned aerial vehicle (UAV) in a heterogeneous cellular network (HetNet) at heterogeneous user traffic demands to maximize the throughput. The key idea is to consider the upper limit of the achievable throughput based on the traffic demand of each user to optimize the ABS position, optimally selecting its direct communication path to the terrestrial base station or its forwarding path via the ABS. We derive the throughput maximization problem with traffic demands and then solve this problem for the ABS position with the optimal communication paths. Our simulation results highlighted that the proposed method achieved 23% higher throughput than an existing method at heterogeneous user traffic demands.

This paper analyzes the spatial performance of the autonomous sidelink cellular-vehicle-to-everything (called ASC-V2X) with the sensing-based semi-persistent scheduling (SB-SPS) with the power-domain non-orthogonal multiple access (NOMA), called SPS-NOMA. In SPS-NOMA, multiple users (e.g., cars or pedestrians) simultaneously broadcast their packets, i.e., a packet collision, and each receiver (i.e., each of their surrounding users) aims to decode the packets by using the successive interference cancellation (SIC). However, some re-ceivers may undergo collision errors at collisions even in SPS-NOMA due to spatial location relationships between the receivers and simultaneously transmitting users, called collision users. To reveal such spatial performance characteristics, this paper derives closed-form expressions of the packet reception ratio (PRR) at the receiver deployed on each coordinate point in a spatial area. Our analysis showed the spatial distributions of the PRR in an area, and SPS-NOMA achieved the required PRR in a 50% more wide area than the existing ASC-V2X without SIC. Additionally, our analysis provided the limitations of SPS-NOMA, and specifically, receivers experienced 65 % lower PRRs than the peak around the bisector created by collision users.

This paper proposes an analytical model for the throughput of the grant-free power-domain non-orthogonal multiple access (called GF-NOMA) in the massive machine-type communications, reflecting the characteristics of packet errors. GF-NOMA designs power resources (called power levels) for each terminal to autonomously satisfy the decoding condition in NOMA. This design causes packet errors at higher-power levels than the level used by multiple terminals due to the non-orthogonality. Our proposed analytical model reflects the packet errors due to this power level design to analyze the throughput more accurately than related works. Our analytical results highlighted that our proposed model underestimated the throughput by only 0.3% over the Monte Carlo simulation at fifteen power levels. In contrast, an existing model overestimated the throughput by 68% over the simulation. Our analysis also showed the throughput characteristics and revealed that using the lowest-power level provided 89% lower throughput than using the highest-power level at ten power levels.

This paper proposes a retransmission strategy using the non-orthogonal multiple access (NOMA) in the PC5-based cellular-V2X mode 4 (called mode 4) to mitigate the channel congestion. The proposed strategy has two key ideas. The first idea is to allow each node (e.g., a car or a pedestrian) to retransmit its packet at lower transmission power than its original packet in the first transmission. The second idea is that each node aims to synchronize its low-powered retransmission with the first transmission of its neighbor node. The two key ideas boost the PRR through diversity effects by mitigating interference and providing power differences with widely deployed receivers. Our simulations highlighted that the proposed strategy outperformed the existing NOMA with retransmissions in mode 4 by 29%.

This paper presents the link-level performance of sparse code multiple access (SCMA) for PC5-based cellular-vehicle-to-everything (C-V2X with different channel estimation errors (CEEs) for every user, called a heterogeneous CEE, due to user mobility. Such a CEE may cause decoding error propagation for users experiencing no CEEs through the message passing algorithm used in SCMA due to the non-orthogonality. First, we analyze the error propagation in a basic heterogeneous CEE model, in which a specific user provides a Gaussian CEE. Our analysis shows that the error propagation depends on the edge connectivity with the specific user on the Factor graph; its directly connected users’ signals show worse decoding performance than its indirectly connected users’ signals. Next, we evaluate the link-level performance of each user in the heterogeneous CEE model to confirm the impacts of the error propagation. Our evaluation results demonstrated that the error propagation degraded 8.1 times worse bit error rate performance of the indirectly connected user at a CEE variance of 0.1 than no CEE for all users. Through our simulation results, this paper highlights that error propagation is a potential challenge for SCMA in PC5-based V2X.

We investigate the analytical expressions of typical performance metrics, namely message reception probability, message reception interval, and information dissemination rate, for vehicle-to-everything (V2X) safety communication in urban scenarios. Each of the performance metrics can be expressed in a simple closed form under some moderate assumptions such as vehicles being positioned according to a Poisson process in a two-dimensional plane. Based on the obtained expressions, we analyze the dependence of these performance metrics on the message transmission interval, which is a typical parameter of congestion control of V2X communication. The results show that the optimal message transmission interval that minimizes the average message reception interval can be derived in a simple closed form. The information dissemination rate is insensitive to the message transmission interval.

This paper proposes a new concept Decentralized Broadcasting-NOMA (Non-Orthogonal Multiple Access) for PC5-based Cellular-Vehicle-to-Everything mode 4 (called mode 4) to accommodate more vehicles and pedestrians (called nodes) in Crash Warning System (CWS). The proposed concept is to apply NOMA to broadcast system with autonomous distributed random access. This paper develops two methods to enhance mode 4 in the proposed concept. The first method is that several nodes broadcast their signals in parallel with DB-NOMA. This method can boost the spectrum utilization efficiency. The second method is that relay nodes superpose their own transmission signal and other node's relay signal with DB-NOMA. This method can efficiently expand broadcast ranges without consuming the additional transmission slots. Simulations results revealed that the proposed method accommodated 119% more nodes compared with the original mode 4. Therefore, this paper concludes that the proposed concept is useful and the proposed methods based on the concept outperform the current mode 4.