The satellite-terrestrial integrated networks (STINs) bring a wider range of communication connections to 6G. Due to the reduction in the base station coverage and the number of users continues to increase, user-centric access network (UCAN) has become a more common access method. However, more access options and more complex co-frequency interference make communication resource allocation more difficult. To address this issue, this paper proposes a multi-objective optimization method for communication resources based on heterogeneous graph representation in UCAN. Firstly, this method utilizes heterogeneous graphs to represent network topology and communication resources, extracting a mixture of discrete and continuous decision space from the attributes of nodes and edges. Secondly, a multi-objective optimization model is established to simultaneously optimize the interference, throughput, and energy consumption in UCAN through user access selection and power control, and solved using algorithm. Finally, compared with the benchmark methods, the superiority of the proposed method is demonstrated.

The integration of satellite and terrestrial networks has ushered in a new era of communication capabilities. In satellite-terrestrial integrated network (STIN), full-frequency reuse introduces substantial inter-satellite interference and inter-beam interference, leading to a reduction in system capacity. Considering the extensive coverage area and high mobility of low Earth orbit (LEO) satellites, the acquisition of satellite-ground channel state information (CSI) is inherently imprecise, significantly affecting the performance gains of beamforming techniques. We propose a Graph Attention Network(GAT)-based approach to reduce system interference by optimizing beamforming. In detail, we represent the network topology as a graph, where nodes represent desired links and edges signify interference links. This transforms the NP-hard problem into a graph optimization task. In GAT, it can uncover the concealed influences of inter-satellite and inter-beam interference. This entails learning high-dimensional feature information from networks with similar structures while disregarding state variations in low-dimensional spaces. This approach enhances system robustness. Through simulation results, our proposed beamforming method demonstrates effective interference suppression with low computational complexity, leading to increased system throughput. Moreover, the method exhibits robustness in the presence of corrupted input data.

The widespread employ of Internet of Things (IoT) devices relies on the massive deployment of sensor nodes and data collection timely. Benefit from development of low-Earth orbit (LEO) satellite technology, the LEO Satellite is considered an effective way for achieving wider coverage to terrestrial IoT devices in remote area. However, it is challenging to obtain perfect channel state information (CSI) in LEO satellite system because estimation error and longer round trip time in practice. To overcome this problem, we propose max–min fairness (MMF) robust beamforming deterministic uncertainty model of imperfect CSI convex-concave optimization algorithm (D-ICCA) and stochastic uncertainty model of imperfect CSI convex-concave optimization algorithm (S-ICCA) in LEO satellite communication system, respectively. MMF optimization problems are formulated under the constraints of the maximum per-antennas power constraint in the LEO satellite communication system. In deterministic uncertainty model of imperfect CSI, we obtain the lower bound of CSI by the Cauchy–Schwarz inequality first. Then, we transform the formulated MMF optimization problem to a series of standard convex problem and solve convex optimization subproblems by adopting the alternating direction method of multipliers (ADMM) to obtain suboptimal robust beamforming vectors. In stochastic uncertainty model of imperfect CSI, we model the MMF optimization problem with stochastic phase error and solve the MMF optimization problem via ADMM with closed-from solution to obtain suboptimal robust beamforming vectors. Finally, simulation results demonstrate that the proposed D-ICCA and S-ICCA beamforming algorithms can achieve better performance than ConADMM and FFA-SCA without robust design.

The autonomous cooperation of multiple unmanned aerial vehicles (UAVs) will effectively improve the efficiency of task completion and meet the needs of task diversity. The information interaction and mutual control between UAVs restrict the autonomy of multi-UAVs. The number and selection of control units not only affect the equipment cost of the network but also affect the stability of the network. Link information, such as bandwidth resources and the computing power of the control unit, also affect the resource adjustment of other related links. In order to improve the efficiency and stability of UAVs computing first network, considering the number of control units and link information, this article creatively puts forward the concepts of incidence control, sign incidence control, and incidence complete control. The minimum incidence control number and incidence complete control number of general graphs are calculated. When the network topology of UAV meets the requirements of path, circle, and star, the exact value of the sign incidence control number is calculated. When the network topology of UAV meets the requirements of the complete graph, complete bipartite graph, and wheel graph, the bounds of the sign incidence control number are calculated. The number of control units of the UAV network is further determined.

Integrating unmanned aerial vehicles (UAVs) into emergency communications is a promising way to accomplish efficient network recovery with the advantages of UAV flexibility. To ensure information forwarding from the disaster area, this article considers an emergency communication scenario where a UAV provides uplink relaying services based on nonorthogonal multiple access (NOMA) for a set of disconnected ground wireless access points (APs) under the urban environment. To maximize the system uplink throughput, the UAV altitude, power control, as well as the bandwidth allocation between the access and backhaul links are jointly optimized. Especially, the constraint for the uplink rate fairness is also considered. Our formulated problem is nonconvex due to the complex uplink co-channel interference under the Line-of-Sight (LoS) probability-based Air-to-Ground (AtG) channel. To tackle this issue, we change our formulated problem into an equivalent form by coping with the information-causality and fairness constraints. Then, a joint altitude and resource allocation (JARA) algorithm is developed, which iteratively solves the altitude optimization subproblem and resource optimization subproblem until convergence. For each subproblem, we further introduce auxiliary variables so that it can be solved by using the successive convex approximation (SCA) method. Finally, two benchmarks are used for the throughput comparison, and simulation results verify that the system uplink throughput of our proposed algorithm is improved through the AtG LoS propagation advantage, uplink power control, as well as the bandwidth allocation between the access and backhaul links.

Device-to-device (D2D) communication can significantly improve network coverage and spectral efficiency. Meanwhile, non-orthogonal multiple access (NOMA) has recently been integrated with D2D communication to further improve connection density and satisfy explosive data rate requirements of end users. Considering quality of experience (QoE) has become an important indicator from the user perspective, in this paper, we study the QoE-driven resource allocation problem in a device-to-device (D2D) underlaying NOMA cellular network coexisting with D2D pairs and NOMA-based cellular users (CUs). Our target is to maximize the sum mean opinion scores (MOSs) of all users while guaranteeing the minimum QoE requirement of each CU and D2D pair, by jointly optimizing subchannel assignment and power allocation at CUs and D2D pairs. Since this problem is mixed-integer and non-convex, we first transform it into an equivalent yet more tractable form. Then, a two-stage iterative algorithm based on the alternating optimization framework and constrained concave-convex procedure technique is proposed to optimize subchannel assignment and power allocation alternately. Simulation results show that the proposed scheme outperforms the orthogonal multiple access solution and three NOMA based benchmark schemes in terms of QoE performance.

The ultradense network (UDN) is one of the most promising technologies in the fifth generation (5G) to address the network system capacity issue. It can enhance spatial reuse through the flexible, intensive deployment of small base stations. A universal 5G UDN architecture is necessary to realize the autonomous and dynamic deployment of small base stations. However, the security of the 5G UDN is still in its infancy, and the data communication security among the network entities is facing new challenges. In this paper, we proposed a new security based on implicit certificate (IC) scheme; the scheme solves the security problem among the access points (APs) in a dynamic APs group (APG) and between the AP and user equipment (UE). We present each phase regarding how two network entities obtain the Elliptic Curve Qu‐Vanstone (ECQV) implicit certificate scheme, verify each other’s identity, and share keys in an UDN. Finally, we extensively analyze our lightweight security communication model in terms of security and performance. The simulation on network bandwidth evaluation is also conducted to prove the efficiency of the solution.

The demands for vehicular Internet access are proliferating. To enable vehicular communications, roadside units (RSUs) can be deployed along the roadside to provide wireless coverage and network access for driving‐thru vehicles and the performance of vehicle to RSU communications have been studied in multiple contexts. However, there is not still an efficient media access control (MAC) scheme specific for the sparse highway environment. In this study, the authors investigate the MAC scheme of drive‐thru Internet in a sparse highway environment by a Markov chain encountering model. The analytical model incorporates the high‐node mobility with the modelling of distributed coordination function (DCF) and unveils the impacts of mobility velocity and number of vehicles on the throughput. On the basis of the model, they develop a new MAC scheme and show that when vehicle number is small the proposed MAC scheme can obtain higher throughput and mitigate the impacts of vehicle mobility on the system throughput, which is desirable for the sparse highway environment. Using extensive simulations, they validate the accuracy of the analytical model and effectiveness of the proposed MAC scheme.

Combining tiny sensors and wireless communication technology, wireless body area network (WBAN) is one of the most promising fields. Wearable and implantable sensors are utilized for collecting the physiological data to achieve continuously monitoring of people’s physical conditions. However, due to the openness of wireless environment and the significance and privacy of people’s physiological data, WBAN is vulnerable to various attacks; thus, strict security mechanisms are required to enable a secure WBAN. In this article, we mainly focus on a survey on the security issues in WBAN, including securing internal communication in WBAN and securing communication between WBAN and external users. For each part, we discuss and identify the security goals to be achieved. Meanwhile, relevant security solutions in existing research on WBAN are presented and their applicability is analyzed.

Being one of core characteristics for 5G cellular networks, ultra‐dense small cell network is an effective approach to reuse the spectrum and achieve high data rate transmission in the wireless communication networks. However, because of sharing the spectrum resources, the interference problem among the macrocell base stations (MBS) and the small cell base stations (SCBSs) is hard to address. In this study, the authors model the scenario as a Stackelberg game, where the MBS act as the leader and all SCBSs act as followers. In the game, the MBS set its interference penalty price first, based on the prices the MBS then determines its channel allocation schemes to all SCBSs. Observing the interference penalty price and the amount of allocated channels performed by the MBS, each SCBS then determines its transmit power to achieve its optimal utility. Because of the first‐move advantage, the MBS is able to predict the reactions of each SCBS and make optimal strategies. Simulation results show the correctness of the analysis and the significant benefits when the power control and channel allocation are jointly considered in the proposed schemes.

Internet of Things (IoT), which will create a huge network of billions or trillions of “Things” communicating with one another, are facing many technical and application challenges. This paper introduces the status of IoT development in China, including policies, R&D plans, applications, and standardization. With China's perspective, this paper depicts such challenges on technologies, applications, and standardization, and also proposes an open and general IoT architecture consisting of three platforms to meet the architecture challenge. Finally, this paper discusses the opportunity and prospect of IoT.

Quality of Service (QoS) and queue management are critical issues for broadcast scheme of IEEE 802.11 systems in Vehicular Ad hoc Networks (VANETs). However, existing 1-dimensional models of broadcast scheme in VANETs are unable to capture the complete QoS performance and queueing behavior due to the lack of an adequate finite buffer model. We present a 2-dimensional Markov chain that integrates the broadcast scheme of the 802.11 system and queueing processes into one model. The extra dimension, that models the queue length, accurately capture important QoS measures for realistic 802.11 broadcast systems with finite buffer under finite load. We derive an simplified method for solving the steady state probabilities of the Markov chain. The solutions are validated by extensive simulations. Based on this model, we also show numerical results to analyze the performance of the broadcast scheme in VANETs in terms of collision probability, throughput, queue length, and QoS measures, including blocking probability and queueing delay.

In this paper, the original Multiple Input Multiple Output (MIMO) Y channel is extended into a more generalized circumstance, called a generalized MIMO Y channel with general signal demands. The model consists of K(K≥2) nodes each equipped with Mkantennas and an intermediate relay equipped with N antennas. There is no direct link between the nodes. Therefore, supposing that node i and node j (i ≠ j∈{1,2,···, K}) exchange nijsignals, each node has to transmit mk(mk=Σi ≠ kknki, mk≤Mk) signals for other nodes in the MAC phase, and then receive mksignals in the BC phase, via the relay. Then, it's proved that Σk=1Kmkdegrees of freedom (DoF) can be achieved by making use of signal space alignment (SSA) and interference nulling beamforming in this model, when N ≥ 1/2(Σk=1Kmk) and (Mi+Mj) ≥ (N+nij).

The integration cellular networks, wireless local area networks (WLANs), and the new paradigm of mobile ad hoc networks (MANETs) is the trend for next generation mobile networks. And the multi-hop routing mechanism is an open and challenge issue in this area. In this paper, a multi-hop routing mechanism with fuzzy estimation of links for heterogeneous wireless networks (HWNs) is proposed. The mechanism comprises neighbor discover, gateway discover and route discovery, which supports the mobile hosts (MHs) outside of the service area to access BS/AP by multi-hop route. The quality of links is addressed and evaluated by comprehensive fuzzy estimation approach based on analytic hierarchy process (AHP). Furthermore, the route maintenance overhead is also analyzed and discussed. Simulations reveal that the proposed routing mechanism can effectively provide valid route and improve the quality of service and performance in HWNs.