The static deployment of Virtualized Network Functions (VNFs) introduces 1) significant degradation of Quality of Service (QoS), 2) inefficiency in the network and computing resource utilization, and 3) Network Function Virtualization (NFV)-based services with insufficient scalability, optimality, and flexibility. Caching VNFs is a promising solution to satisfy the dynamic demand to deploy a variety of VNFs and to maximize the performance as well as cost effectiveness. Although the concept of Content Delivery Network (CDN) is popular for efficiently caching and distributing contents, VNF deployment does not realize the benefit of CDN-based caching approaches. The challenges to caching VNFs are 1) to cover the large variety of VNFs and their properties, including the necessity of service chaining, and 2) to achieve high acceptance ratio given the limited availability of resources. This paper proposes Function Delivery Network (FDN), which is a cluster of distributed edge hypervisors for caching VNFs over a Software-Defined Network (SDN). The deployment and quality of the network function can be significantly improved by serving them closer to the end-users from the cached VNFs. FDN introduces a new strategy called Value-based caching that considers 1) the locality of reference and performance parameters of network and edge hypervisors together and 2) a partial deployment of service chains across multiple edge hypervisors for further efficient utilization of hypervisors resources. Evaluations on different patterns of input requests confirm that Value-based caching introduces significant improvement on both QoS and resource utilization in NFV.

This paper proposes an optimization approach that designs the backup network with the minimum total capacity to protect the primary network from random multiple link failures with link failure probability. In the conventional approach, the routing in the primary network is not considered as a factor in minimizing the total capacity of the backup network. Considering primary routing as a variable when deciding the backup network can reduce the total capacity in the backup network compared to the conventional approach. The optimization problem examined here employs robust optimization to provide probabilistic survivability guarantees for different link capacities in the primary network. The proposed approach formulates the optimization problem as a mixed integer linear programming (MILP) problem with robust optimization. A heuristic implementation is introduced for the proposed approach as the MILP problem cannot be solved in practical time when the network size increases. Numerical results show that the proposed approach can achieve lower total capacity in the backup network than the conventional approach.

This paper proposes an efficient server selection scheme in successive participation scenario with participating-domain segmentation. The scheme is utilized by distributed processing systems for real-time interactive communication to suppress the communication latency of a wide-area network. In the proposed scheme, users participate for server selection one after another. The proposed scheme determines a recommended server, and a new user selects the recommended server first. Before each user participates, the recommended servers are determined assuming that users exist in the considered regions. A recommended server is determined for each divided region to minimize the latency. The new user selects the recommended available server, where the user is located. We formulate an integer linear programming problem to determine the recommended servers. Numerical results indicate that, at the cost additional computation, the proposed scheme offers smaller latency than the conventional scheme. We investigate different policies to divide the users' participation for the recommended server finding process in the proposed scheme.

We study wireless networked control systems (WNCSs), where controllers (CLs), controlled objects (COs), and other devices are connected through wireless networks. In WNCSs, COs can become unstable due to bursty packet losses and random delays on wireless networks. To reduce these network-induced effects, we utilize the packetized predictive control (PPC) method, where future control vectors to compensate bursty packet losses are generated in the receiving horizon manner, and they are packed into packets and transferred to a CO unit. In this paper, we extend the PPC method so as to compensate random delays as well as bursty packet losses. In the extended PPC method, generating many control vectors improves the robustness against both problems while it increases traffic on wireless networks. Therefore, we consider control vector selection to improve the robustness effectively under the constraint of single packet transmission. We first reconsider the input strategy of control vectors received by COs and propose a control vector selection scheme suitable for the strategy. In our selection scheme, control vectors are selected based on the estimated average and variance of round-trip delays. Moreover, we solve the problem that the CL may misconceive the CO's state due to insufficient information for state estimation. Simulation results show that our selection scheme achieves the higher robustness against both bursty packet losses and delays in terms of the 2-norm of the CO's state.

A triple-band CP rectenna for ambient RF energy harvesting is presented in this paper. A simple broadband CP slot antenna has been proposed with the bandwidth of 51.1% operating from 1.53 to 2.58GHz, which can cover GSM-1800, UMTS-2100 and 2.45GHz WLAN bands. Accordingly, a triple-band rectifying circuit is designed to convert RF energy in the above bands, with the maximum RF-DC conversion efficiency of 42.5% at a relatively low input power of -5dBm. Additionally, the rectenna achieves the maximum conversion efficiency of 12.7% in the laboratory measurements. The measured results show a good performance in the laboratory measurements.

In radio channel measurements and modeling, directional scanning via highly directive antennas is the most popular method to obtain angular channel characteristics to develop and evaluate advanced wireless systems for high frequency band use. However, it is often insufficient for ray-/cluster-level characterizations because the angular resolution of the measured data is limited by the angular sampling interval over a given scanning angle range and antenna half power beamwidth. This study proposes the sub-grid CLEAN algorithm, a novel technique for high-resolution multipath component (MPC) extraction from the multi-dimensional power image, so called double-directional angular delay power spectrum. This technique can successfully extract the MPCs by using the multi-dimensional power image. Simulation and measurements showed that the proposed technique could extract MPCs for ray-/cluster-level characterizations and channel modeling. Further, applying the proposed method to the data captured at 58.5GHz in an atrium entrance hall environment which is an indoor hotspot access scenario in the fifth generation mobile system, the multipath clusters and corresponding scattering processes were identified.

In this paper, an analysis method for calculating balanced and unbalanced modes of a small antenna is summarized. Modal condactances which relate dissipated power of the antenna are directly obtained from standard S-parameters that we can measure by a 2-port network analyzer. We demonstrate the validity and effectiveness of the proposed method by simulation and measurement for a dipole antenna with unbalaned feed. The ratio of unbalanced-mode power to the total power (unbalanced-mode power ratio) calculated by the proposed method agrees precisely with that yielded by the conventional method using measured radiation patterns. Furthermore, we analyze a small loop antenna with unbalanced feed by the proposed method and show that the self-balancing characteristic appears when the loop is set in resonant state by loading capacitances or the whole length of the loop is less than 1/20th the wavelength.

This paper proposes a novel flexible receiver with virtual channels for overloaded multiple-input multiple-output (MIMO) channels. The receiver applies extended rotation matrices proposed in the paper for the flexibility. In addition, adaptive selection of the extended rotation matrices is proposed for further performance improvement. We propose two techniques to reduce the computational complexity of the adaptive selection. As a result, the proposed receiver gives us an option to reduce the complexity with a slight decrease in the transmission performance by changing receiver configuration parameters. A computer simulation reveals that the adaptive selection attains a gain of about 3dB at the BER of 10^-3.

We propose to use clustered interference alignment for the situation where the backhaul link capacity is limited and the base station is cache-enabled given MIMO interference channels, when the number of Tx-Rx pairs exceeds the feasibility constraint of interference alignment. We optimize clustering with the soft cluster size constraint algorithm by adding a cluster size balancing process. In addition, the CSI overhead is quantified as a system performance indicator along with the average throughput. Simulation results show that cluster size balancing algorithm generates clusters that are more balanced as well as attaining higher long-term throughput than the soft cluster size constraint algorithm. The long-term throughput is further improved under high SNR by reallocating the capacity of the backhaul links based on the clustering results.

Full duplex (FD) communication can potentially double the throughput of a point-to-point link in wireless communication. Additionally, FD communication can mitigate the hidden node collision problem. The MAC protocols for FD communications are classified into two types; synchronous FD MAC and asynchronous one. Though the synchronous FD MAC mitigates hidden node collisions by using control frame, overhead duration for each data frame transmission may be a bottleneck for the networks. On the other hand, the asynchronous FD MAC mitigates the hidden node collisions by FD communication. However, it wastes more time due to transmission failure than synchronous FD MAC. Clarifying the effect of two major FD MAC types on networks requires a quantitative evaluation of the effectiveness of these protocols in networks with hidden node collisions. This paper proposes performance analysis of FD MAC protocols for wireless local area networks with hidden node collisions. Through the proposed analytical model, the saturated throughputs in FD WLANs with both asynchronous and synchronous FD MAC for any number of STAs and any payload size can be obtained.

In a dense wireless network, concurrent transmissions normally increase interference and reduce network performance. In such an environment, however, there is a possibility that a frame can be decoded correctly if its receive power is higher than that of another frame by some predefined value (i.e., the so-called capture effect). As a result, the unfairness of throughputs among network nodes likely occurs in that context. This research aims to quantify the throughput performance of only one access point Wireless Local Area Networks (WLANs) with dense network nodes in the presence of the capture effect. We first propose a new analytical model, which can express not only WLANs' throughputs but also WLANs' unfairness transmission. The validity of the proposed model is confirmed by simulation results. Second, relying on the model, we present a novel Medium Access Control (MAC) protocol-based solution, which realizes throughput fairness between network nodes induced by the capture effect.