ith the rapid development of mobile Internet and the Internet of things (IoTs), the demands for high-speed data applications, such as high-quality wireless video streaming, social networking, and machine-to-machine communication, have been growing exponentially recently. It is envisioned that total daily mobile traffic in the representative Western European countries will grow 67 times from 186 terabyte (TB) to 12540 TB from 2010 to 2020. Total worldwide mobile traffic of 351 exabyte (EB) in 2025 will represent a 174 percent increase compared with 2020 [1]. Currently, the cellular networks including the first generation (1G), second generation (2G), third generation (3G), and fourth generation (4G) are far from satisfying the significant traffic increments and the high energy efficiency (EE) because much of the power consumed by a base station (BS) is used to overcome path loss, which in turn causes interferences to other users. The fifth generation (5G) system deployed initially in 2020 is expected to provide approximately 1000 times higher wireless area capacity and save up to 90 percent of energy consumption per service compared with the current 4G system. More than 1000 Gb/s/km 2 area spectral capacity in dense urban environments, 10 times higher battery life of connected devices, and five times reduced end-to-end (E2E) latency are anticipated in 5G systems. The new 5G air interface and spectrum should be combined together with the long term evolution (LTE) and WiFi to provide universal high-rate coverage and seamless user experience [2].To achieve these goals in 5G systems, advanced radio access technologies and all-Internet Protocol (IP) open Internet network architectures should be evolved smoothly from 4G systems [3]. Accurately, the new breakthroughs in the baseband and radio frequency (RF) are required to enable computationally intensive operations and adapted to new air interfaces in 5G systems. A significant and advanced baseband computation is required to meet the complex requirements of new solutions such as large-scale cooperative signal processing in the physical layer. Meanwhile, the new breakthroughs in the integrated access node and heterogeneous convergence are required to enable the ultra dense radio nodes to work efficiently. The plug-and-play function becomes essential to commercial deployments, in which the available spectral resources should be allocated and the corresponding parameters should be self-organized. Furthermore, the softwaredefined air interface technologies should be seamlessly integrated into the 5G radio access network (RAN) architectures. The cloud computing based radio access infrastructures would provide on-demand resource processing, delay-aware storage, and high network capacity wherever needed. W 6IEEE Network • AbstractCompared with fourth generation cellular systems, fifth generation wireless communication systems are anticipated to provide spectral and energy efficiency growth by a factor of at least 10, and the area throughput growth by a factor of at least 25. T...

In cloud radio access networks (C-RANs), a substantial amount of data must be exchanged in both backhaul and fronthaul links, which causes high power consumption and poor quality of service (QoS) experience for real-time services. To solve this problem, a cluster content caching structure is proposed in this paper, which takes full advantage of distributed caching and centralized signal processing. In particular, redundant traffic on the backhaul can be reduced because the cluster content cache provides a part of required content objects for remote radio heads (RRHs) connected to a common edge cloud. Tractable expressions for both effective capacity and energy efficiency performance are derived, which show that the proposed structure can improve QoS guarantees with a lower power cost of local storage. Furthermore, to fully explore the potential of the proposed cluster content caching structure, the joint design of resource allocation and RRH association is optimized, and two distributed algorithms are accordingly proposed. Simulation results verify the accuracy of the analytical results and show the performance gains achieved by cluster content caching in C-RANs.

The simultaneous wireless transfer of information and power with the help of a relay equipped with multiple antennas is considered in this letter, where a "harvest-and-forward" strategy is proposed.In particular, the relay harvests energy and obtains information from the source with the radio-frequent signals by jointly using the antenna selection (AS) and power splitting (PS) techniques, and then the processed information is amplified and forwarded to the destination relying on the harvested energy.This letter jointly optimizes AS and PS to maximize the achievable rate for the proposed strategy.Considering the joint optimization is according to the non-convex problem, a two-stage procedure is proposed to determine the optimal ratio of received signal power split for energy harvesting, and the optimized antenna set engaged in information forwarding. Simulation results confirm the accuracy of the two-stage procedure, and demonstrate that the proposed "harvest-and-forward" strategy outperforms the conventional amplify-and-forward (AF) relaying and the direct transmission.

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