With the growing demand for computation-intensive applications, multi-access edge computing (MEC) has emerged as a critical paradigm that decentralizes computation and storage by bringing resources closer to users. As distributed computing undergoes ongoing development propelled by the advancements in the Internet of Things (IoT) and mobile communication technologies, the issue of edge node cooperation and resource sharing needs to be investigated. In this paper, the issue of edge node cooperation and resource sharing is modeled as a two-layer framework. More specifically, in the lower layer, a heuristic matching algorithm between users and edge nodes is developed, and a resource sharing algorithm among edge nodes in the same coalition is proposed. In the upper layer, a centralized coalition formation algorithm is designed based on the Hungarian method, and then we further define the coalition rules among edge nodes and propose a distributed coalition formation algorithm. Simulation results demonstrate that the proposed algorithms reduce the network cost effectively compared with non-cooperative schemes. Moreover, we analyze the impact of various network parameters on the network cost, thereby providing insights for future optimization and development in MEC networks.

This paper addresses the coalition formation and the resource allocation in a device-to-device assisted mobile edge computing network, where the user equipments (UEs) collaborate to share the communication bandwidth and the computation resources for the task offloading. Our goal is to minimize the task execution cost, which is defined as the weighted sum of energy consumption and processing delay. In particular, we model waiting time of UEs in a coalition for the task offloading and incorporate it in the task execution cost. Therefore, we propose a three-layer hierarchical optimization framework which integrates the convex optimization, the heuristic algorithm, and the coalition game theory. In particular, we propose a double weighted mutation genetic algorithm to enhance the convergence of the algorithm, which applies weighted mutations to the offloading leader and the offloading order in the coalition. Furthermore, the task execution costs in both middle and upper layers are analytically evaluated. Simulation results validate the effectiveness of our proposed algorithms in reducing the task execution costs and speeding up the convergence.

Integrated satellite-terrestrial networks (ISTNs) have played a crucial role in next-generation wireless systems. In this paper, we introduce partial non-orthogonal multiple access (p-NOMA) into ISTNs for downlink transmission, focusing on the system performance of satellite user equipments (UEs) and terrestrial UEs with co-channel interference and imperfect successive interference cancellation. We employ the Poisson point process to model the spatial distribution of the ground base stations, with Shadowed-Rician fading for satellite-terrestrial links and Rayleigh fading for terrestrial links. The closed-form expressions for the outage probability and average achievable rate of both satellite UEs and terrestrial UEs are derived. Additionally, we analyze the performance of the p-NOMA scheme and present the comparisons with non-orthogonal multiple access (NOMA) and orthogonal multiple access schemes. We validate the analytical results through simulations, confirming that p-NOMA outperforms NOMA in terms of both outage probability and average achievable rate. Moreover, we investigate the impact of p-NOMA parameters on the average achievable rate in the terrestrial network, providing insights for optimizing system performance.

We devise a cutting-edge near-field terahertz (THz) covert communication strategy with noise uncertainty where the beam is focused at a specific location, defined by both distance and direction. Leveraging unique near-field properties, the strategy combats eavesdroppers by increasing the capacity gap between legitimate and eavesdropping channels. We first develop a novel performance analytical framework for the near-field THz covert communication system, based on which we derive closed-form expressions for key performance metrics and thresholds, including the average covert probability, covert outage probability, covert rate, optimal detection threshold, and received power threshold of the eavesdropper. To further improve the secrecy performance, we design a new true-time-delay (TTD)-based piecewise approximation hybrid beamforming scheme for maximizing the covert rate, while effectively mitigating the negative impact caused by the beam split effect. Our numerical results demonstrate that the near-field THz covert communication strategy effectively combats eavesdroppers at all distances in the sector covering the main beam, demonstrating its practical significance for future wireless networks.

In this article, we develop a dynamic weighting strategy which considers the residual energy of different devices in aerial edge computing networks, and formulate a weighted energy consumption optimization problem aimed at extending device operating duration. To solve the formulated problem, we develop a clustering algorithm using K-means++ to establish optimal user-to-unmanned-aerial-vehicle access relationships, and the optimization problem is decomposed into trajectory, transmit power, and bandwidth subproblems. Each subproblem is sequentially solved by using the successive convex approximation algorithm, and the entire optimization problem is resolved by using the block coordinate descent algorithm. Simulation results demonstrate the effectiveness of our proposed weighting strategy in managing the energy levels of users, which prolongs the operational duration of the devices.

With the diversification of wireless applications, the traffic patterns in the evolving wireless networks are becoming more dynamic and heterogeneous. Although numerous methods have been developed for spatio-temporal analysis, the impact of traffic patterns on spatial capacity has yet to be fully addressed. To this end, this paper studies the spatial outage capacity (SOC) in Poisson networks with Bernoulli traffic, which answers the question: “What is the maximum density of concurrently active links that satisfy a certain outage constraint?” We perform the analysis by integrating stochastic geometry with queueing theory and derive the meta distribution (MD) of signal-to-interference ratio (SIR). Unlike the conventional approaches that approximate the MDs by beta distributions, we consider the spatio-temporal correlations of the dominant interference exactly while treating the remaining interference in an average sense. Our analysis maintains tractability and achieves a highly accurate characterization of the SIR, especially for dense networks in the high-reliability regime that is particularly significant for network design. Moreover, we prove that the SOC in the high-reliability regime is achieved when all transmitters are always active. Simulations validate the accuracy of the theoretical results and show that the packet arrival rate has a marginal effect on the SOC as well as the corresponding SIR MD. We also show that the optimal density that maximizes the SOC is approximately inversely proportional to the packet arrival rate.

Distinguishing the near-field and far-field regions in line-of-sight (LoS) multiple-input multiple-output (MIMO) systems is crucial, as their distinct characteristics significantly impact performance and system design. In this paper, we propose a novel criterion for identifying the near-field and far-field regions based on the number of independent spatial streams. We introduce and derive a closed-form expression of effective degree of freedom (EDoF) for LoS MIMO systems by taking into account both the phase differences and path attenuation. Then, the spatial multiplexing distance (SMD) and resolvable distance (RD) are derived to define the boundary of the near field. Based on these boundaries, we propose a hybrid search-gradient descent (HSGD) algorithm to estimate the near-field channel information, which combines a coarse search through non-uniform step sizes with a precise estimation based on the gradient descent. Our numerical results unveil that i) the EDoF can be accurately calculated using the closed-form expression, ii) the HSGD algorithm achieves at least 28.72% improvement over the polar-domain simultaneous iterative gridless weighted (PSIGW) algorithm and 22.91% improvement over the orthogonal matching pursuit (OMP) algorithm across the different signal-to-noise ratio (SNR), and iii) the HSGD algorithm achieves at least 95.84% improvement over the PSIGW algorithm and 79.83% improvement over the OMP algorithm across varying communication distances.

This paper investigates an unmanned aerial vehicle (UAV)-base station (BS) integrated network, where a UAV transmits downlink secrecy data to multiple ground cognitive users while a ground BS utilizes jamming beamforming to help the UAV counter the eavesdropping attack of a ground eavesdropper. In particular, we consider the imperfect eavesdropping and jamming channel state information (CSI) related to the eavesdropper. To maximize the minimum sum secrecy rate of the cognitive users, a robust secure transmission scheme is proposed. The UAV trajectory, UAV transmit power, BS beamforming, and user scheduling are jointly optimized with the constraints of the communication quality of the primary users served by the BS and the UAV available propulsion energy. We formulate a non-convex optimization problem which is challenging to be solved mathematically, and we utilize an alternating optimization technique to divide the original problem into three sub-problems, i.e., UAV trajectory sub-problem, transmit power sub-problem, and user scheduling sub-problem. Besides, they can be solved by the successive convex approximation, semi-definite relaxation and S-procedure, and bivariate relaxation methods, respectively. Moreover, we explore the impact of different parameters of the proposed transmission scheme on the minimum sum secrecy rate of the cognitive users, and verify the superiority of the proposed robust secure transmission scheme design.

Mounting compact and lightweight base stations on unmanned aerial vehicles (UAVs) is a cost-effective and flexible solution to provide seamless coverage on the existing terrestrial networks. While the coverage probability in UAV-assisted cellular networks has been widely investigated, it provides only the first-order statistic of signal-to-interference-plus-noise ratio (SINR). In this paper, to analyze high-order statistics of SINR and characterize the disparity among individual links, we provide a meta distribution (MD)-based analytical framework for UAV-assisted cellular networks, in which the probabilistic line-of-sight channel and realistic antenna pattern are taken into account for air-to-ground transmissions. To accurately characterize the interference from UAVs, we relax the widely applied uniform off-boresight angle (OBA) assumption and derive the exact distribution of OBA. Using stochastic geometry, for both steerable and vertical antenna scenarios, we obtain mathematical expressions for the moments of condition success probability, the SINR MD, and the mean local delay. Moreover, we study the asymptotic behavior of the moments as network density approaches infinity. Numerical results validate the tightness of the theoretical results and show that the uniform OBA assumption underestimates the network performance, especially in the regime of moderate altitude of UAV. We also show that when UAVs are equipped with steerable antennas, the network coverage and user fairness can be optimized simultaneously by carefully adjusting the UAV parameters.

In order to satisfy the requirement of extremely high data rate in traffic hotspot regions, millimeter wave (mmWave) has attracted significant attention in wireless communication networks. While the coverage performance of mmWave networks based on the distribution of signal-to-interference-plus-noise ratio (SINR) has been widely studied, it provides only very limited information on the link reliability. In this paper, we provide a fine-grained performance analysis of the mmWave networks with hotspots. Specifically, we first establish a general and tractable framework to investigate the performance of mmWave networks using the Poisson cluster process integrated with several features of the mmWave band. Both open and closed association strategies are considered. To show what fraction of users in the networks achieves target reliability when the SINR is given, we derive the tier association probability and the moments of the conditional SINR distribution, based on which the exact meta distributions of SINR are given. Interestingly, in clustered mmWave networks, the widely used standard and generalized beta approximations do not work well when the blockage effect is severe. To resolve this issue, we provide a modified approximation by scaling the standard beta distribution, which is shown to be closer to the exact results. We conduct extensive simulations to study the impact of mmWave and deployment features on the performance of clustered mmWave networks. Numerical results reveal that the optimal scattering variance of mmWave base stations scales with the cluster size to maximize the number of concurrent reliable links, and increasing the antenna directivity results in more reliable communications than elevating the transmit power of mmWave base stations.

Deploying Sub-6GHz networks together with millimeter wave (mmWave) is a promising solution to achieve high data rates in traffic hotspots while guaranteeing sufficient coverage, where mmWave small cells are densely deployed to provide high quality of service. In this paper, we propose an analytical framework to investigate the integrated Sub-6GHz-mmWave cellular networks, in which the Sub-6GHz base stations (BSs) are modeled as a Poisson point process, and the mmWave BSs are clustered following a Poisson cluster process in traffic hotspots. We conduct stochastic geometry-based analysis and derive the performance metrics including the association probability, signal-to-interference-plus-noise ratio coverage probability and average achievable rate, which are validated to be accurate by Monte Carlo simulations. We analyze the impact of various deployment parameters on the network performance to give insights on the network design. In particular, it is shown that deploying mmWave small cells in traffic hotspots will outperform both traditional Sub-6GHz heterogeneous network and isolated mmWave system in terms of the coverage probability. It can also be shown that extremely high and extremely small association weight for mmWave BSs will deteriorate the performance for cell edge users and cell interior users, respectively. Moreover, there exists an optimal pre-decided dispersion parameter of mmWave BSs that contributes to the maximum coverage probability.

Deploying sub-6-GHz network together with millimeter wave (mm-wave) is a promising solution to simultaneously achieve sufficient coverage and high data rate. In heterogeneous networks, the traditional coupled access, i.e., users are constrained to be associated with the same base station in both downlink and uplink, is no longer optimal, and the concept of downlink and uplink decoupling (DUDe) has recently been proposed. In this paper, we analyze the coverage probability and area throughput for both the downlink and uplink of sub-6-GHz/mm-wave cellular networks with decoupled access. Compared with the existing works, we take uplink power control and mm-wave interference into account. Using the tools from stochastic geometry, the expressions of signal-to-interference-plus-noise ratio coverage probability, user-perceived rate coverage probability and the area throughput are derived. The impact of decoupled access and different small cells (SCells) is investigated. In particular, analytical results reveal that with decoupled access, UEs are more likely to be associated with SCells in uplink when the network is sparse, and the uplink traffic will be offloaded from sub-6-GHz SCells to mm-wave SCells when the network is dense. Moreover, the dense deployment of mm-wave SCells rather than sub-6-GHz SCells is more reasonable, and the DUDe is a key factor in improving the performance of dense cellular networks with multi-band.