In the near future, i.e., beyond 4G, some of the prime objectives or demands that need to be addressed are increased capacity, improved data rate, decreased latency, and better quality of service. To meet these demands, drastic improvements need to be made in cellular network architecture. This paper presents the results of a detailed survey on the fifth generation (5G) cellular network architecture and some of the key emerging technologies that are helpful in improving the architecture and meeting the demands of users. In this detailed survey, the prime focus is on the 5G cellular network architecture, massive multiple input multiple output technology, and device-to-device communication (D2D). Along with this, some of the emerging technologies that are addressed in this paper include interference management, spectrum sharing with cognitive radio, ultra-dense networks, multi-radio access technology association, full duplex radios, millimeter wave solutions for 5G cellular networks, and cloud technologies for 5G radio access networks and software defined networks. In this paper, a general probable 5G cellular network architecture is proposed, which shows that D2D, small cell access points, network cloud, and the Internet of Things can be a part of 5G cellular network architecture. A detailed survey is included regarding current research projects being conducted in different countries by research groups and institutions that are working on 5G technologies.

A Survey of 5G Network: Architecture and Emerging Technologies

After about a decade of intense research, spurred by both economic and operational considerations, and by environmental concerns, energy efficiency has now become a key pillar in the design of communication networks. With the advent of the fifth generation of wireless networks, with millions more base stations and billions of connected devices, the need for energy-efficient system design and operation will be even more compelling. This survey provides an overview of energy-efficient wireless communications, reviews seminal and recent contribution to the state-of-the-art, including the papers published in this special issue, and discusses the most relevant research challenges to be addressed in the future.

A Survey of Energy-Efficient Techniques for 5G Networks and Challenges Ahead

Emerging technologies, such as the Internet of Things, smart applications, smart grids, and machine-to-machine networks stimulate the deployment of autonomous, self-configuring, large-scale wireless sensor networks (WSNs). Efficient energy utilization is crucially important in order to maintain a fully operational network for the longest period of time possible. Therefore, network lifetime (NL) maximization techniques have attracted a lot of research attention owing to their importance in terms of extending the flawless operation of battery-constrained WSNs. In this paper, we review the recent developments in WSNs, including their applications, design constraints, and lifetime estimation models. Commencing with the portrayal of rich variety definitions of NL design objective used for WSNs, the family of NL maximization techniques is introduced and some design guidelines with examples are provided to show the potential improvements of the different design criteria.

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A survey of network lifetime maximization techniques in wireless sensor networks

Device-to-Device (D2D) communication has emerged as a promising technology for optimizing spectral efficiency in future cellular networks. D2D takes advantage of the proximity of communicating devices for efficient utilization of available resources, improving data rates, reducing latency, and increasing system capacity. The research community is actively investigating the D2D paradigm to realize its full potential and enable its smooth integration into the future cellular system architecture. Existing surveys on this paradigm largely focus on interference and resource management. We review recently proposed solutions in over explored and under explored areas in D2D. These solutions include protocols, algorithms, and architectures in D2D. Furthermore, we provide new insights on open issues in these areas. Finally, we discuss potential future research directions.

A Survey of Device-to-Device Communications: Research Issues and Challenges

The deferred acceptance algorithm proposed by Gale and Shapley (1962) has had a profound influence on market design, both directly, by being adapted into practical matching mechanisms, and, indirectly, by raising new theoretical questions. Deferred acceptance algorithms are at the basis of a number of labor market clearinghouses around the world, and have recently been implemented in school choice systems in Boston and New York City. In addition, the study of markets that have failed in ways that can be fixed with centralized mechanisms has led to a deeper understanding of some of the tasks a marketplace needs to accomplish to perform well. In particular, marketplaces work well when they provide thickness to the market, help it deal with the congestion that thickness can bring, and make it safe for participants to act effectively on their preferences. Centralized clearinghouses organized around the deferred acceptance algorithm can have these properties, and this has sometimes allowed failed markets to be reorganized.

Deferred Acceptance Algorithms: History, Theory, Practice, and Open Questions

Device-to-device (D2D) communications bring significant benefits to mobile multimedia services in local areas. However, these potential advantages hinge on intelligent resource sharing between potential D2D pairs and cellular users. In this paper, we study the problem of energy-efficient uplink resource sharing over mobile D2D multimedia communications underlaying cellular networks with multiple potential D2D pairs and cellular users. We first construct a novel analytical model of energy efficiency for different sharing modes, which takes into account quality-of-service (QoS) requirements and the spectrum utilization of each user. Then, we formulate the energy-efficient resource sharing problem as a nontransferable coalition formation game, with the characteristic function that accounts for the gains in terms of energy efficiency and the costs in terms of mutual interference. Moreover, we develop a distributed coalition formation algorithm based on the merge-and-split rule and the Pareto order. The distributed solution is characterized through novel stability notions and can be adapted to user mobility. From it, we obtain the energy-efficient sharing strategy on joint mode selection, uplink reusing allocation, and power management. Extensive simulation results are provided to demonstrate the effectiveness of our proposed game model and algorithm.

Energy-Efficient Resource Sharing for Mobile Device-to-Device Multimedia Communications

Massive multimedia services have been considered as one the most prominent characteristics for smart cities. In this paper, we propose an energy-efficient content delivery system via the device-to-device communications, which realizes the large-scale content delivery among mobile devices with constrained energy, unpredictable demand, limited storage, random mobility, and opportunistic transmission. The highlights of this paper lie in two parts. On the theoretical end, through exploring the relationship among the coding, storage, and transmission, a systematic energy-saving content delivery fashion is investigated. On the technical end, a totally distributed content delivery system is designed in a simple and efficient manner, in which each device only utilizes local information to make decisions and implements its own scheme individually. Importantly, the proposed scheme is realized in a practical smart city system, and numerical results demonstrate that it is flexible to various users’ needs and communication environments.

Greening the Smart Cities: Energy-Efficient Massive Content Delivery via D2D Communications

Data service has been considered as one the most prominent characteristics for Industrial Internet of Things (IIoT). This paper studies how to design an optimal computing manner for a general IIoT system. On the theory end, we analyze the relationship between the data processing and the energy consumption through investigating the content correlation of the captured data. Importantly, we derive an exact expression for the performance of IIoT by combining computation with intelligence. On the application end, we design an efficient way to obtain a threshold by approximating the performances of different computing manners, and show how to apply it to practical IIoT applications. We believe that the proposed computation rules hold great significance for the IIoT designer, that is, it is better to use distributed computing manner when the content correlation is high, otherwise, centralized computing manner is better.

When Computation Hugs Intelligence: Content-Aware Data Processing for Industrial IoT

With the increasing popularity of traffic-intensive video applications, UDNs are treated as one of the most promising technologies for massive video delivery. However, due to the drastic interference between neighboring cells, how to achieve high energy and spectrum efficiency is still an open and challenging problem. This work proposes a systematic solution for content delivery over UDNs by integrating collaboration with intelligence. In particular, we first design a hybrid video coding scheme that is flexible and robust to the dynamic wireless environment. Then an active and proactive video update strategy is designed by intelligently alleviating the impact of the interference. Finally, a collaborative video scheduling scheme is developed to maximize the video quality as well as the energy and spectrum efficiency. Importantly, we summarize three fundamental design guidelines, and believe that they are useful for improving the transmission capacity of UDNs.

When Collaboration Hugs Intelligence: Content Delivery over Ultra-Dense Networks

It is crucial to consider timely status updates for machine type communications (MTC) in some scenarios, where a controller continuously obtains state information of targets from a sender to complete control or monitoring tasks, such as vehicular networking and environmental detection In this work, we measure the timeliness of the status by the recently proposed age of information (AoI) metric Different from the previous works about AoI, we consider the short packet feature of MTC in our system, where status packets will suffer from a significant packet error rate Considering that the status packets may not be decoded by the receiver correctly, this work investigates the performance of MTC under traditional protocol (the sender discards the error status packets directly) and automatic repeat-request (ARQ) protocol (the sender retransmits the error status packets), and obtains the approximated closed-form expressions of the average AoI, respectively Based on the closed-form expressions of the average AoI, we design two suboptimal blocklengths to minimize the average AoI under the two protocols Numerical results verify the correctness of theoretical analysis, and show that the proposed scheme can achieve almost the same optimization performance as the exhaustive search method Moreover, in the case of different packet generation rates, we find that the ARQ/traditional protocol can achieve better performance in low/high packet generation rate scenarios, respectively

Dan Wu

Papers

Energy-Efficient Resource Sharing for Mobile Device-to-Device Multimedia Communications

Greening the Smart Cities: Energy-Efficient Massive Content Delivery via D2D Communications

When Computation Hugs Intelligence: Content-Aware Data Processing for Industrial IoT

When Collaboration Hugs Intelligence: Content Delivery over Ultra-Dense Networks

Average Age of Information in Short Packet Based Machine Type Communication