Machine-to-Machine (M2M) communication plays a pivotal role in the evolution of Internet of Things (IoT). Cellular networks are considered to be a key enabler for M2M communications, which are originally designed mainly for Human-to-Human (H2H) communications. The introduction of M2M users will cause a series of problems to traditional H2H users, i.e., interference between various traffic. Resource allocation is an effective solution to these problems. In this paper, we consider a shared resource block (RB) and power allocation in an H2H/M2M coexistence scenario, where M2M users are subdivided into delay-tolerant and delay-sensitive types. We first model the RB-power allocation problem as maximization of capacity under Quality-of-Service (QoS) constraints of different types of traffic. Then, a learning framework is introduced, wherein a complex agent is built from simpler subagents, which provides the basis for distributed deployment scheme. Further, we proposed distributed Q-learning based autonomous RB-power allocation algorithm (DQ-ARPA), which enables the machine type network gateways (MTCG) as agents to learn the wireless environment and choose the RB-power autonomously to maximize M2M pairs' capacity while ensuring the QoS requirements of critical services. Simulation results indicates that with an appropriate reward design, our proposed scheme succeeds in reducing the impact of delay-tolerant machine type users on critical services in terms of SINR thresholds and outage ratios.

In this paper, we propose a high-speed full-duplex optical wireless communication system using a single channel imaging receiver for personal area network applications. This receiver is composed of an imaging lens, a small sensitive-area photodiode, and a 2-aixs actuator and it can reject most of the background light. Compared with the previously proposed system with single wide field-of-view (FOV) non-imaging receiver, the coverage area at 12.5 Gb/s is extended by > 20%. Furthermore, since the rough location information of the user is available in our proposed system, instead of searching for the focused light spot over a large area on the focal plane of the lens, only a small possible area needs to be scanned. In addition, by pre-setting a proper comparison threshold when searching for the focused light spot, the time needed for searching can be further reduced. Proof-of-concept experiments have been carried out and the results show that with this partial searching algorithm and pre-set threshold, better performance is achieved.

Network Function Virtualization (NFV) enables the embedding of Virtualized Network Function (VNF) into commodity servers. A sequence of VNFs can be chained in a particular order to form a service chain (SC). This paper considers placing multiple SCs in a geo-distributed edge system owned by multiple service providers (SPs). For a pair of SC and SP, minimizing the placement cost while meeting a latency constraint is formulated as an integer programming problem. As SC clients and SPs are self-interested, we study the matching between SCs and SPs that respects individual's interests yet maximizes social welfare. The proposed matching approach excludes any blocking individual and block pair which may jeopardize the stability of the result. Simulation results show that the proposed approach performs well in terms of social welfare but is suboptimal concerning the number of placed SCs.

Communication networks for wide-scale distributed energy resources (DERs) including photovoltaics (PVs), wind, storage and battery systems and electric vehicles (EVs) will be indispensable in future power grids. In this paper, we compare optical fronthaul networks using existing optical ground wires (OPGWs) for centralized radio access network (C-RAN) architecture to realize cost effective wireless communication network expansion including low population area. We investigate the applicability of optical data transport technologies of physical layer split (PLS), analog radio-on-fiber (ARoF), and common public radio interface (CPRI). The deployment costs of them are comparatively analyzed. It was shown that physical layer split and analog radio-on-fiber with subcarrier multiplexing (SCM) result in lower cost than other technologies.

We investigate the capacity limitations of a WDM ring fiber-radio backbone incorporating wavelength interleaving where each base station drives a sectorized antenna interface. We also investigate the issues related to the merging of such networks with standard WDM infrastructures. The investigations show that re-allocating the interleaved WDM channels to fit within a 100 GHz block enables the millimeter-wave (mm-wave) fiber-radio system with sectorized antenna interfaces to integrate easily with WDM systems. The performance of a variety of channel allocations for the merged fiber-radio network is examined and simulation studies of the transmission of multiple channels are carried out. The overall network capacity of the merged mm-wave fiber-radio network is improved with the proposed channel allocation schemes.

In this paper, we present a new electro-optic (EO) probing system based on heterodyne detection. The use of a recirculating frequency shifter allows to expand the bandwidth of the system far beyond what is attainable with a conventional heterodyne EO set-up. The performance for the frequencies up to 50GHz is analysed to forecast the viability of the system up to the THz range.

Due to most of the existing graph repartitioning methods are known for poor efficiency in distributed environments. In this paper, we introduce a new graph repartitioning method with two phases in distributed environments. In the first phase, a local method is designed to identify all the potential candidate vertices that should be moved to the other partitions at once in each partition locally. In the second phase, a streaming graph processing model is adopted to reassign the candidate vertices to achieve lightweight graph repartitioning. During the reassignment of the vertex, we propose an objective function to balance both the load balance and the number of crossing edges among the distributed partitions. The experimental results with a large set of real word and synthetic graph datasets show that the communication cost can be reduced by nearly 1 to 2 orders of magnitude compared with the existing methods.