Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized mobile cloud computing toward mobile edge computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also discuss a set of issues, challenges, and future research directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

A Survey on Mobile Edge Computing: The Communication Perspective

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An Introduction To The Event Related Potential Technique

Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized Mobile Cloud Computing towards Mobile Edge Computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also present a research outlook consisting of a set of promising directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

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

The fifth generation (5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability, and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation (6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle (UAV) communication networks, thus achieving a space-air-ground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6 GHz, millimeter wave (mmWave), terahertz (THz), and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence (AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable faster and further communications to the extent that the boundary between physical and cyber worlds disappears.

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Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts

Mobile edge computing (MEC) has been recognized as a promising technique to provide enhanced computation services for low-power wireless devices at the network edge. How to evaluate the timeliness of the task and data delivery is critical for the development of MEC applications. Considering a wireless powered MEC system, in this letter we study the average age of information (AoI), which is a crucial performance metric to measure the freshness of information. Specifically, in the considered system, a sensor node harvests energy from an energy transmitter and transmits computation tasks to the MEC server. The charging time of the sensor node’s capacitor, the waiting time and service time at the MEC server are taken into account when calculating the average AoI. The closed-form expression of the average AoI is obtained accordingly and evaluated through numerical simulations.

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Average Age of Information in Wireless Powered Mobile Edge Computing System

Covert communication can hide the information transmission process from the warden to prevent adversarial eavesdropping. However, it becomes challenging when the warden can move. In this paper, we propose a covert communication scheme against a mobile warden, which maximizes the connectivity throughput between a multi-antenna transmitter and a full-duplex jamming receiver with the covert outage probability (COP) limit. First, we analyze the monotonicity of the COP to obtain the optimal location the warden can move. Then, under this worst situation, we optimize the transmission rate, the transmit power and the jamming power of covert communication to maximize the connection throughput. This problem is solved in two stages. Under this worst situation, we first maximize the connection probability over the transmit-to-jamming power ratio within the maximum allowed COP for a fixed transmission rate. Then, the Newton’s method is applied to maximize the connection throughput via optimizing the transmission rate iteratively. Simulation results are presented to evaluate the effectiveness of the proposed scheme.

Multi-Antenna Covert Communication With Jamming in the Presence of a Mobile Warden

Multicast transmission is known as an efficient mechanism for offering the same services for different terminals. However, the power consumption is surprisingly arisen due to terminals with the worst channel quality while maintaining the Quality of Service (QoS) and data decoding requirements. In order to address this problem, we examine the energy saving performance of an efficient algorithm called Unicast Support Multicast (USM), which can dynamically and expeditiously use unicast transmission as an additional support for multicast transmission. The USM algorithm can overcome the inherent drawbacks of multicast transmission, and decrease the power consumption with QoS guarantee. Numerical results based on the conducted theoretical analysis demonstrate that power consumption is reduced with USM while fulfilling the data rate and decoding requirements. In addition, the energy efficiency of USM is superior compared to pure multicast transmission.

Energy efficiency of Unicast Support Multicast with QoS guarantee

This paper addresses the resource allocation problem in collaborative relay-assisted OFDMA networks. Recent works on the subject have mainly considered symmetric source-to-relay and relay-to-destination resource allocations, which limits the achievable gains through relaying. In this paper our focus is two-fold. Firstly, we consider the problem of asymmetric radio resource allocation, where the objective is to maximize the system throughput of the source-to-destination link under various constraints. In particular, we consider optimization of the set of collaborative relays and link asymmetries together with subcarrier and power allocation. Secondly, we pay attention to the effects of imperfections in the channel-state information needed in the resource allocation decisions. We derive theoretical expressions for the solutions and illustrate them through simulations. The results validate clearly the additional performance gains through asymmetric cooperative scheme compared to the other recently proposed resource allocation schemes.

Asymmetric resource allocation for collaborative relay OFDMA networks with imperfect CSI

In this work, we propose a dynamic optimization scheme for an edge computing system with multiple users, where the radio and computational resources, and offloading decisions, can be dynamically allocated with the variation of computation demands, radio channels and the computation resources. Specifically, with the objective to minimize the energy consumption of the considered system, we propose a joint computation offloading, radio and computational resource allocation algorithm based on Lyapunov optimization. Through minimizing the derived upper bound of the Lyapunov drift-plus-penalty function, the main problem is divided into several sub-problems at each time slot and are addressed separately. The simulation results demonstrate the effectiveness of the proposed scheme.

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Zheng Chang

Papers

Average Age of Information in Wireless Powered Mobile Edge Computing System

Multi-Antenna Covert Communication With Jamming in the Presence of a Mobile Warden

Energy efficiency of Unicast Support Multicast with QoS guarantee

Asymmetric resource allocation for collaborative relay OFDMA networks with imperfect CSI

Dynamic Resource Allocation and Computation Offloading for Edge Computing System