Vehicular content networks (VCNs), which distribute medium-volume contents to vehicles in a fully distributed manner, represent the key enabling technology of vehicular infotainment applications. In ...VCNs, the road-side units (RSUs) cache replicas of contents on the edge of networks to facilitate the timely content delivery to driving-through vehicles when requested. However, due to the limited storage at RSUs and soaring content size for distribution, RSUs can only selectively cache content replicas. The edge caching scheme in RSUs, therefore, becomes a fundamental issue in VCNs. This paper addresses the issue by developing an edge caching scheme in RSUs. Specifically, we first analyze the features of vehicular content requests based on the content access pattern, vehicle's velocity, and road traffic density. A model is then proposed to determine whether and where to obtain the replica of content when the moving vehicle requests it. After this, a cross-entropy-based dynamic content caching scheme is proposed accordingly to cache the contents at the edge of VCNs based on the requests of vehicles and the cooperation among RSUs. Finally, the performance of the proposed scheme is evaluated by extensive simulation experiments.
With the development of the Internet of Things (IoT) technology, massive amounts of sensor data in applications such as fire monitoring need to be transmitted to edge servers for timely processing. ...However, there is an energy-hole phenomenon in transmitting data only through terrestrial multi-hop networks. In this study, we focus on the data collection task in an unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) network, where a UAV is deployed as the mobile data collector for the ground sensor nodes (SNs) to ensure high information freshness. Meanwhile, the UAV is equipped with an edge server for data caching. We first establish a rigorous mathematical model in which the age of information (AoI) is used as a measure of information freshness, related to both the data collection time and the UAV's flight time. Then a mixed-integer non-convex optimization problem is formulated to minimize the peak AoI of the collected data. To solve the problem efficiently, we propose an iterative two-step algorithm named the AoI-minimized association and trajectory planning (AoI-MATP) algorithm. In each iteration, the optimal SN-collection point (CP) associations and CP locations for the parameter ε are first obtained by the affinity propagation clustering algorithm. The optimal UAV trajectory is found using an improved elite genetic algorithm. Simulation results show that based on the optimized ε, the AoI-MATP algorithm can achieve a balance between data collection time and flight time, reducing the peak AoI of the collected data.
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Wireless Sensor Networks (WSNs) have emerged as an efficient solution for numerous real-time applications, attributable to their compactness, cost-effectiveness, and ease of deployment. The rapid ...advancement of 5G technology and mobile edge computing (MEC) in recent years has catalyzed the transition towards large-scale deployment of WSN devices. However, the resulting data proliferation and the dynamics of communication environments introduce new challenges for WSN communication: (1) ensuring robust communication in adverse environments and (2) effectively alleviating bandwidth pressure from massive data transmission. In response to the aforementioned challenges, this paper proposes a semantic communication solution. Specifically, considering the limited computational and storage resources of WSN devices, we propose a flexible Attention-based Adaptive Coding (AAC) module. This module integrates window and channel attention mechanisms, dynamically adjusts semantic information in response to the current channel state, and facilitates adaptation of a single model across various Signal-to-Noise Ratio (SNR) environments. Furthermore, to validate the effectiveness of this approach, the paper introduces an end-to-end Joint Source Channel Coding (JSCC) scheme for image semantic communication, employing the AAC module. Experimental results demonstrate that the proposed scheme surpasses existing deep JSCC schemes across datasets of varying resolutions; furthermore, they validate the efficacy of the proposed AAC module, which is capable of dynamically adjusting critical information according to the current channel state. This enables the model to be trained over a range of SNRs and obtain better results.
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In this work, we focus on a drone-fleet-enabled package delivery scenario, in which multiple drones fly from a start point and cooperatively deliver packages to the ground users in the presence of a ...number of no-fly zones (NFZs). We first mathematically model the package delivery scenario in a rigorous manner. Then, a package value maximization problem is established to optimize the flight trajectory and package delivery under the constraints of drone load and collision as well as NFZs. The formulated problem is a highly challenging mixed-integer non-convex problem. To facilitate solving it, we transform the formulated problem into an equivalent problem with special structure by using some appropriate transformations, based on which a low-complexity algorithm with favorable performance is developed using the penalty convex-concave procedure method. Finally, numerical results demonstrate the superiority of the proposed solution.
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The flower pollination algorithm (FPA) is a novel heuristic optimization algorithm inspired by the pollination behavior of flowers in nature. However, the global and local search processes of the FPA ...are sensitive to the search direction and parameters. To solve this issue, an improved flower pollination algorithm based on cosine cross-generation differential evolution (FPA-CCDE) is proposed. The algorithm uses cross-generation differential evolution to guide the local search process, so that the optimal solution is achieved and sets cosine inertia weights to increase the search convergence speed. At the same time, the external archiving mechanism and the adaptive adjustment of parameters realize the dynamic update of scaling factor and crossover probability to enhance the population richness as well as reduce the number of local solutions. Then, it combines the cross-generation roulette wheel selection mechanism to reduce the probability of falling into the local optimal solution. In comparing to the FPA-CCDE with five state-of-the-art optimization algorithms in benchmark functions, we can observe the superiority of the FPA-CCDE in terms of stability and optimization features. Additionally, we further apply the FPA-CCDE to solve the robot path planning issue. The simulation results demonstrate that the proposed algorithm has low cost, high efficiency, and attack resistance in path planning, and it can be applied to a variety of intelligent scenarios.
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Ultra-dense networks (UDNs), which can provide extremely high throughput and data rates, have been considered as one of the key techniques for the fifth generation mobile networks. However, it may ...cause severe inter-cell interference and significant energy consumption due to numerous base stations (BSs) being randomly deployed. To mitigate the interference and boost energy efficiency (EE) of the UDN effectively, we propose a cluster-based energy-efficient resource allocation scheme in this paper. The proposed scheme has two stages: clustering stage and resource allocation stage. In clustering stage, we use a modified K-means algorithm in BS-clustering process to dynamically adjust the number of BS-clusters based on the density of BSs. Then, in each BS cluster, we divide user equipments (UEs) into multiple UE-groups with minimum intra-cluster interference. In this way, the complexity of resource allocation can be greatly reduced. While in resource allocation stage, we design a two-step resource blocks assignment algorithm and an iterative energy efficient power allocation algorithm based on a non-cooperative game. Furthermore, we implement simulations under the realistic broadband channel propagation conditions and the simulation results show that the proposed approach can effectively mitigate the interference and improve the EE of UDN.
In future mobile networks, more and more machine-type communication (MTC) devices with different service requirements will be deployed. To meet the massive access needs of MTC, this paper develops a ...cluster-based congestion-mitigating access scheme (CCAS), with aim to mitigate the severe collision of MTC devices (MTCDs) that access to the base station (BS) concurrently. To this end, we first design a modified spectral clustering algorithm to group MTCDs into different clusters based on their locations and service requirements. Then, a device called MTC gateway (MTCG) is chosen by two steps to assist transmitting data for MTCDs in each cluster. In the data transmission process, MTCG is in charge of aggregating packets generated by MTCDs in a cluster and forwarding them to BS when the number of buffered packets reaches a certain threshold. To model the aggregation and forwarding process of each MTCG, we use queuing theory to analyze the access performance in terms of collision probability and access delay. In addition, we also implement simulations to further validate the accuracy of our analytical model and the effectiveness of CCAS. Numerical results, which are consistent with the theoretical values, show that the proposed CCAS can significantly decrease collision probability, and increase the number of successfully received packets of the system without increasing average access delay.
Wireless network virtualization (WNV) has drawn attention from the researchers ranging from academia to industry as one of the significant technologies in the cellular network communication. It is ...considered as a pioneer to achieve effective resource utilization with decreased operating expenses and capital expenses by decoupling the networks functionalities of coexisting virtual networks. It facilitates fast deployment of new services and novel technologies. WNV paradigm is in the early stages, and there is a large room for the research community to develop new architectures, systems, and applications. The availability of software-defined networking (SDN) and cloud/centralized radio access network (C-RAN) steers up the hope for the WNV realization. This paper surveys WNV along with the recent developments in SDN and C-RAN technologies. Based on these technologies and WNV concepts, we identify the requirements and opportunities of future cellular networks. We then propose a general architectural framework for the WNV based on SDN. In-depth discussion of challenges and research issues as well as promising approaches for future networks communication improvements are also proposed. Finally, we give several promising candidates of future network services for residential customers and business customers.
Reconfigurable intelligent surfaces (RISs) have the capability to change the wireless environment smartly Considering the attenuation of subchannels and crowding users involved in the wideband ...system, we introduce RISs into the multi-user multi-input single-output (MU-MISO) system with orthogonal frequency division multiplexing (OFDM) for performance enhancement. Maximizing the minimum rate of dense users in an MU-MISO-OFDM system assisted by RIS with an approximate practical model is formulated as the joint optimization problem involving subcarrier allocation, transmit precoding (TPC) matrices at the base station, and RIS passive beamforming. A coalition-game subcarrier allocation (CSA) algorithm is proposed to solve space–frequency resource allocation on subcarriers, which reforms the interference topology among dense users. Fractional programming and convex optimization method are used to optimize the TPC matrices and the RIS passive beamforming, which improves the spectral efficiency synthetically across all subchannels in the wideband system. Simulation results indicate that the CSA algorithm provides a significant gain for dense users. Besides, the proposed joint optimization method shows the considerable advantage of the RISs in the MU-MISO-OFDM system.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Relay nodes (RNs), as important components of heterogeneous networks introduced in Long-Term Evolution-Advanced systems, are employed to improve network capacity and extend cell coverage in a ...cost-effective manner. In heterogeneous relay networks, there are two types of user access connections: the direct link and the two-hop link. The former is used when a user accesses the base station (BS) directly, whereas the latter, which is composed of a backhaul link and an access link, is used when a user accesses the BS via an RN. For the RNs with in-band wireless backhauls, two-hop links operate in shared spectrum, and thus, resource allocation is a challenging issue to provide sufficient capacity for backhaul links while maintaining fair sharing of resources with normal macro users. In this paper, we develop a hierarchical game based on the Stackelberg model to address the resource allocation in heterogeneous relay networks. The proposed game consists of two subgames, namely, the backhaul-level game (BLG) and the access-level game (ALG), respectively. In the game model, RNs in backhaul links as leaders play the BLG, whereas mobile stations (MSs) in access links as followers play the ALG. By estimating the achievable rates of MSs, the leaders choose their optimal resource-allocation strategies, and then, the followers do the best responses to the leaders' strategies. Simulation results demonstrate that our proposed hierarchical game can guarantee the throughput balance between backhaul and access links, and thus, improve the user data rates and the overall system resource utilization, as compared with the resource-allocation schemes that consider backhaul and access links separately.
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