The need of telecommunications operators to reduce Capital and Operational Expenditures in networks which traffic is continuously growing has made them search for new alternatives to simplify and automate their procedures. Because of the different transport network segments and multiple layers, the deployment of end-to-end services is a complex task. Also, because of the multiple vendor existence, the control plane has not been fully homogenized, making end-to-end connectivity services a manual and slow process, and the allocation of computing resources across the entire network a difficult task. The new massive capacity requested by Data Centers and the new 5G connectivity services will urge for a better solution to orchestrate the transport network and the distributed computing resources. This article presents and demonstrates a Network Slicing solution together with an end-to-end service orchestration for transport networks. The Network Slicing solution permits the co-existence of virtual networks (one per service) over the same physical network to ensure the specific service requirements. The network orchestrator allows automated end-to-end services across multi-layer multi-domain network segments making use of the standard Transport API (TAPI) data model for both l0 and l2 layers. Both solutions will allow to keep up with beyond 5G services and the higher and faster demand of network and computing resources.

In IoT era, the growth of data variety is driven by cross-domain data fusion. In this paper, we advocate that “local production for local consumption (LPLC) paradigm” can be an innovative approach in cross-domain data fusion, and propose a new framework, geolocation-centric information platform (GCIP) that can produce and deliver diverse spatio-temporal content (STC). In the GCIP, (1) infrastructure-based geographic hierarchy edge network and (2) adhoc-based STC retention system are interplayed to provide both of geolocation-awareness and resiliency. Then, we discussed the concepts and the technical challenges of the GCIP. Finally, we implemented a proof-of-concepts of GCIP and demonstrated its efficacy through practical experiments on campus IPv6 network and simulation experiments.

Recently, new optimization machines based on non-silicon physical systems, such as quantum annealing machines, have been developed, and their commercialization has been started. These machines solve the problems by searching the state of the Ising spins, which minimizes the Ising Hamiltonian. Such a property of minimization of the Ising Hamiltonian can be applied to various combinatorial optimization problems. In this paper, we introduce the coherent Ising machine (CIM), which can solve the problems in a milli-second order, and has higher performance than the quantum annealing machines especially on the problems with dense mutual connections in the corresponding Ising model. We explain how a target problem can be implemented on the CIM, based on the optimization scheme using the mutually connected neural networks. We apply the CIM to traveling salesman problems as an example benchmark, and show experimental results of the real machine of the CIM. We also apply the CIM to several combinatorial optimization problems in wireless communication systems, such as channel assignment problems. The CIM's ultra-fast optimization may enable a real-time optimization of various communication systems even in a dynamic communication environment.

In this paper, a Proof-of-Concept (PoC) architecture is constructed, and the effectiveness of mmWave overlay heterogeneous network (HetNet) with mesh backhaul utilizing route-multiplexing and Multi-access Edge Computing (MEC) utilizing prefetching algorithm is verified by measuring the throughput and the download time of real contents. The architecture can cope with the intensive mobile data traffic since data delivery utilizes multiple backhaul routes based on the mesh topology, i.e. route-multiplexing mechanism. On the other hand, MEC deploys the network edge contents requested in advance by nearby User Equipment (UE) based on pre-registered context information such as location, destination, demand application, etc. to the network edge, which is called prefetching algorithm. Therefore, mmWave access can be fully exploited even with capacity-limited backhaul networks by introducing the proposed algorithm. These technologies solve the problems in conventional mmWave HetNet to reduce mobile data traffic on backhaul networks to cloud networks. In addition, the proposed architecture is realized by introducing wireless Software Defined Network (SDN) and Network Function Virtualization (NFV). In our architecture, the network is dynamically controlled via wide-coverage microwave band links by which UE's context information is collected for optimizing the network resources and controlling network infrastructures to establish backhaul routes and MEC servers. In this paper, we develop the hardware equipment and middleware systems, and introduce these algorithms which are used as a driver of IEEE802.11ad and open source software. For 5G and beyond, the architecture integrated in mmWave backhaul, MEC and SDN/NFV will support some scenarios and use cases.

The Internet of Things (IoT) with its support for cyber-physical systems (CPS) will provide many latency-sensitive services that require very fast responses from network services. Mobile edge computing (MEC), one of the distributed computing models, is a promising component of the low-latency network architecture. In network architectures with MEC, mobile devices will offload heavy computing tasks to edge servers. There exist numbers of researches about low-latency network architecture with MEC. However, none of the existing researches simultaneously satisfy the followings: (1) guarantee the latency of computing tasks and (2) implement a real system. In this paper, we designed and implemented an MEC based network architecture that guarantees the latency of offloading tasks. More specifically, we first estimate the total latency including computing and communication ones at the centralized node called orchestrator. If the estimated value exceeds the latency requirement, the task will be rejected. We then evaluated its performance in terms of the blocking probability of the tasks. To analyze the results, we compared the performance between obtained from experiments and simulations. Based on the comparisons, we clarified that the computing latency estimation accuracy is a significant factor for this system.

Edge computing offers computing capability with ultra-low response times by leveraging servers close to end-user devices. Due to the mobility of end-user devices, the latency between the servers and the end-user devices can become long and the response time might become unacceptable for an application service. Service (container) migration that follows the handover of end-user devices retains the response time. Service migration following the mass movement of people in the same geographic area and at the same time due to an event (e.g., commuting) generates heavy bandwidth usage in the mobile backhaul network. Heavy usage by service migration reduces available bandwidth for ordinary application traffic in the network. Shaping the migration traffic limits the bandwidth usage while delaying service migration and increasing the response time of the container for the moving end-user device. Furthermore, targets of migration decisions increase (i.e., the system load) because delaying a migration process accumulates containers waiting for migration. In this paper, we propose a migration scheduling method to control bandwidth usage for migration in a network and ensure timely processing of service migration. Simulations that compare the proposal with state-of-the-art methods show that the proposal always suppresses the bandwidth usage under the predetermined threshold. The method reduced the number of containers exceeding the acceptable response time up to 40% of the compared state-of-the-art methods. Furthermore, the proposed method minimized the targets of migration decisions.

Spectral graph theory provides an algebraic approach to investigate the characteristics of weighted networks using the eigenvalues and eigenvectors of a matrix (e.g., normalized Laplacian matrix) that represents the structure of the network. However, it is difficult to accurately represent the structures of large-scale and complex networks (e.g., social network) as a matrix. This difficulty can be avoided if there is a universality, such that the eigenvalues are independent of the detailed structure in large-scale and complex network. In this paper, we clarify Wigner's Semicircle Law for weighted networks as such a universality. The law indicates that the eigenvalues of the normalized Laplacian matrix of weighted networks can be calculated from a few network statistics (the average degree, average link weight, and square average link weight) when the weighted networks satisfy a sufficient condition of the node degrees and the link weights.

To reduce peak-to-average power ratio, we propose a method of choosing suitable vectors in a partial transmit sequence technique. Conventional approaches require that a suitable vector be selected from a large number of candidates. By contrast, our method does not include such a selecting procedure, and instead generates random vectors from the Gaussian distribution whose covariance matrix is a solution of a relaxed problem. The suitable vector is chosen from the random vectors. This yields lower peak-to-average power ratio than a conventional method.

The application of network function virtualization (NFV) and software-defined networking (SDN) to passive optical networks (PONs) is attracting attention for the deployment of cost-effective access network systems. This paper presents a novel architecture of a programmable finite state machine (P-FSM) as a hardware accelerator for protocol processing in an optical line terminal (OLT). The P-FSM is programmable hardware that manages various types of FSMs to enhance flexibility in OLTs and achieve wired-rate performance with a negligible increase in total chip area. The P-FSM is implemented using three key technologies: a specific architecture for state management of communications protocols to minimize the logic area, a memory distributed implementation to minimize the program memory, and a new branch operation to minimize the memory area and reduce processing time. Evaluation results show that the P-FSM can handle 10G-EPON/NG-PON2 communications protocols in the same architecture while achieving wired-rate performance. The increase in the total designed area is only 1.5% to 4.9% depending on the number of protocols supported compared to the area of a conventional communications SoC without flexibility. We also clarify that our architecture has the scalability needed to modify the number of FSMs and the maximum number of ONU connections according to the system scale.

In video distribution services such as video streaming, the providers must satisfy the various quality demands of the users. One of the human-centric indexes used to assess video quality is the quality of experience (QoE). In video streaming, the video bitrate, video freezing time, and video bitrate switching are significant determiners of QoE. To provide high-quality video streaming services, adaptive streaming using the Moving Picture Experts Group dynamic adaptive streaming over Hypertext Transfer Protocol (MPEG-DASH) is widely utilized. One of the conventional bitrate selection methods for MPEG-DASH selects the bitrate such that the amount of buffered data in the playback buffer, i.e., the playback buffer level, can be maintained at a constant value. This method can avoid buffer overflow and video freezing based on feedback control; however, this method induces high-frequency video bitrate switching, which can degrade QoE. To overcome this issue, this paper proposes a bitrate selection method in an adaptive video steaming for MPEG-DASH to improve the QoE by minimizing the bitrate fluctuation. To this end, the proposed method does not change the bitrate if the playback buffer level is not around its upper or lower limit, corresponding to the full or empty state of the playback buffer, respectively. In particular, to avoid buffer overflow and video freezing, the proposed method selects the bitrate based on proportional-derivative (PD) control to maintain the playback buffer level at a target level, which corresponds to an upper or lower threshold of the playback buffer level. Simulations confirm that, the proposed method offers better QoE than the conventional method for users with various preferences.

This paper proposes a dual linear-polarized open-ended waveguide subarray designed for use in phased array antennas. The proposed subarray is a one-dimensional linear array that consists of open-ended waveguide antenna elements and suspended stripline feed networks to realize vertical and horizontal polarizations. The antenna includes a novel suspended stripline-to-waveguide transition that combines double- and quad-ridge waveguides to minimize the size of the transition and enhance the port isolation. Metal posts are installed on the waveguide apertures to eliminate scan-blindness. Prototype subarrays are fabricated and tested in an array of 16 subarrays. The experimental tests and numerical simulations indicate that the prototype subarray offers a low reflection coefficient of less than -11.4dB, low cross-polarization of less than -26dB, and antenna efficiency above 69% in the frequency bandwidth of 14%.

The plain bend in a pair of differential transmission lines causes a path difference, which leads to differential-to-common mode conversion due to the phase difference. This conversion can cause serious common-mode noise issues. We previously proposed a tightly coupled asymmetrically tapered bend to suppress forward differential-to-common mode conversion and derived the constraint conditions for high-density wiring. To provide sufficient suppression of mode conversion, however, the additional correction was required to make the effective path difference vanish. This paper proposes a practical and straightforward design methodology by using a very tightly coupled bend (decreasing the line width and the line separation of the tightly coupled bend). Full-wave simulations below 20GHz demonstrated that sufficient suppression of the forward differential-to-common mode conversion is successfully achieved as designed. Measurements showed that our design methodology is effective.

In this paper, the application of minimum mean square error (MMSE) pre-cancellation prior to belief propagation (BP) is proposed as a detection scheme for overloaded multiple-input multiple-output (MIMO) systems. In overloaded MIMO systems, the loops in the factor graph degrade the demodulation performance of BP. Therefore, the proposed scheme applies MMSE pre-cancellation prior to BP and reduces the number of loops. Furthermore, it is applied to the selected transmit and receive nodes so that the condition number of an inverse matrix in the MMSE weight matrix is minimized to suppress the residual interference and the noise after MMSE pre-cancellation. Numerical results obtained through computer simulation show that the proposed scheme achieves better bit error rate (BER) performance than BP without MMSE pre-cancellation. The proposed scheme improves the BER performance by 2.9-5.6dB at a BER of 5.0×10^-3 compared with conventional BP. Numerical results also show that MMSE pre-cancellation reduces the complexity of BP by a factor of 896 in terms of the number of multiplication operations.

Cognitive radio network (CRN) provides an effective way of improving efficiency and flexibility in spectrum usage. Due to the coexistence of secondary user (SU) and primary user (PU), managing interference is a critical issue to be addressed if we are to reap the full benefits. In this paper, we consider the problem of joint interference management and resource allocation in a multi-channel ad hoc CRN. We formulate the problem as an overlapping coalition formation game to maximize the sum rate of SU links while guaranteeing the quality of service (QoS) of PU links. In the game, each SU link can make an autonomous decision and is allowed to participate in one or more cooperative coalitions simultaneously to maximize its payoff. To obtain the solution of the formulated game, a distributed, self-organizing algorithm is proposed for performing coalition formation. We analyze the properties of the algorithm and show that SU links can cooperate to reach a final stable coalition structure. Compared with existing approaches, the proposed scheme achieves appreciable performance improvement in terms of the sum rate of SU links, which is demonstrated by simulation results.

This paper proposes non-orthogonal packet access based on low density signature with phase only adaptive precoding. The proposed access allows multiple user terminals to send their packets simultaneously for implementing massive connectivity, though only one antenna is put on every terminal and on an access point. This paper proposes a criterion that defines the optimum rotation angles for the phase only precoding, and an algorithm based on the steepest descent to approach the optimum rotation angles. Moreover, this paper proposes two complexity-reduced algorithms that converge much faster than the original algorithm. When 6 packets are transmitted in 4 time slots, i.e., overloading ratio of 1.5, the proposed adaptive precoding based on all the proposed algorithms attains a gain of about 4dB at the BER of 10^-4 in Rician fading channels.

Offset quadrature amplitude modulation based orthogonal frequency division multiplexing (OFDM/OQAM) is a promising multi-carrier modulation technique to achieve a low-sidelobe spectrum while maintaining orthogonality among subcarriers. However, a major shortcoming of OFDM/OQAM systems is the high peak-to-average power ratio (PAPR) of the transmit signal. To resolve the high-PAPR issue of traditional OFDM, a self-synchronized-scrambler-based selected-mapping has been investigated, where the transmit sequence is scrambled to reduce PAPR. In this method, the receiver must use a descrambler to recover the original data. However, the descrambling process leads to error propagation, which degrades the bit error rate (BER). As described herein, a partial scrambling overlapped selected mapping (PS-OSLM) scheme is proposed for PAPR reduction of OFDM/OQAM signals, where candidate sequences are generated using partial scrambling of original data. The best candidate, the one that minimizes the peak amplitude within multiple OFDM/OQAM symbols, is selected. In the proposed method, an overlap search algorithm for SLM is applied to reduce the PAPR of OFDM/OQAM signals. Numerical results demonstrate that our PS-OSLM proposal achieves better BER than full-scrambling overlapped SLM (FS-OSLM) in OFDM/OQAM systems while maintaining almost equivalent PAPR reduction capability as FS-OSLM and better PAPR than SLM without overlap search. Additionally, we derive a theoretical lower bound expression for OFDM/OQAM with PS-OSLM, and clarify the effectiveness of the proposed scheme.