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 become 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. A cross entropy based scheme is proposed accordingly to cache the efficient content at the edge of VCNs. Lastly, the performance of the proposed scheme is evaluated by extensive simulation experiments.

The Internet of Things (IoT) has emerged as one of the key features of the next-generation wireless networks, where timely delivery of status update packets is essential for many real-time IoT applications. Age of Information (AoI) is a new metric to measure the freshness of update. The reduction of the violation probability that AoI of status updates exceeds a given age constraint is of great significance for guaranteeing the information freshness in IoT systems. By modeling the IoT networks as M/M/1 and M/D/1 queuing systems, this work focuses on characterizing the violation probability of peak AoI and AoI in IoT systems, where a sensor delivers updates to a monitor under M/M/1 and M/D/1 queues with first-come-first-served policy. From a time-domain perspective, we explore the correlation between interdeparture time and system time, by which the closed-form expressions of peak AoI distribution and the violation probability for any AoI constraint are derived. The obtained results induce accurate characterizations for probability distribution functions of peak AoI and AoI. Consequently, accurate characterizations of average AoI and the variance of AoI are obtained. Then, for peak AoI and AoI, the optimal generation rate of the status update that induces the minimal violation probability is also found. The numerical results show that the optimal update rate can significantly reduce the AoI violation probability for a wide range of AoI constraints. The theoretical findings and predictions are verified by numerical simulation results as well as provide guidance for the design of IoT networks.

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.

The large amount of data amongst billions of devices deployed for Industrial Internet of Things (IIoT) cause a massive energy demands. Driven by the pursuit of green communication, this paper presents space-reserved cooperative caching in the 5th generation (5G) mobile heterogeneous networks for IIoT, where the caching space in base stations (BSs) is largely utilized to store the fixed caching data (FCD) prefetched from the servers, and the reserved space is to temporarily store the data to be wirelessly transmitted (DWT). With the constraint that the quality of service is guaranteed, we propose an algorithm to obtain the optimal proportion between the two parts of the caching space for the purpose of reducing the average energy consumption. Simulation results verified that the proposed caching scheme is more efficient than the conventional one with respect to the average energy consumption.

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 conventional integrated sensing and communication (ISAC) systems, the multiplicative fading of radar signals and space division multiple access (SDMA) restrict system performance. This work proposes a novel rate splitting multiple access (RSMA)-reconfigurable intelligent surface (RIS)-assisted ISAC system to improve the sensing performance, where RIS is deployed to simultaneously assist target detection and RSMA-aided multi-user communication for a dual-functional base station (BS). The objective of this work is to maximize the SNR of the target detection by optimizing the rate splitting, active beamforming at BS, and passive beamforming at the RIS. To solve this non-convex problem, an iterative algorithm is proposed exploiting majorization-minimization (MM), the approximation of the difference of two convex functions (DC), and the penalty method. Finally, simulation results verify the effectiveness of the proposed algorithm and demonstrate a clear sensing gain of the proposed RSMA-RIS-assisted ISAC scheme, approaching the upper bound, due to the special transmission mechanism of rate splitting in RSMA, and the cascaded passive beamforming of order O(N4) from RIS, respectively.