Visible light communication (VLC) systems relying on commercial-off-the-shelf (COTS) devices have gathered momentum recently, due to the pervasive adoption of LED lighting and mobile devices. However, the achievable throughput by such practical systems is still several orders below those claimed by controlled experiments with specialized devices. In this paper, we engineer CoLight aiming to boost the data rate of the VLC system purely built upon COTS devices. CoLight adopts COTS LEDs as its transmitter, but it innovates in its simple yet delicate driver circuit wiring an array of LED chips in a combinatorial manner. Consequently, modulated signals can directly drive the on-off procedures of individual chip groups, so that the spatially synthesized light emissions exhibit a varying luminance following exactly the modulation symbols. To obtain a readily usable receiver, CoLight interfaces a COTS PD with a smartphone through the audio jack, and it also has an alternative MCU-driven circuit to emulate a future integration into the phone. The evaluations on CoLight are both promising and informative: they demonstrate a throughput up to 80 kbps at a distance of 2 m, while suggesting various potentials to further enhance the performance.

This paper experimentally demonstrates a new integrated visible light communication and positioning (VLCP) system to support both the communication and positioning services. To maximize the system transmission data rate while meeting different quality-of-service (QoS) requirements of devices (minimum data rate and positioning accuracy constraints), aQoS-driven joint the adaptive modulation, subcarrier allocation and pre-equalization is presented to improve the system performance. The experimental results indicate that the presented integrated VLCP system achieve the higher positioning accuracy than the existing integrated VLCP system, and also verify that the proposed QoS-driven optimized design archives higher data rate, positioning accuracy and QoS satisfied probability, compared with other existing designs.

With the rapid development of the Internet of Things (IoT) in the smart city, smart grid, and smart industry, indoor communication and positioning are important for IoT. However, radio-frequency (RF)-based wireless networks may fail to guarantee different quality-of-service (QoS) requirements of devices, due to the limited bandwidth, severe interference, and multipath reflections. Hence, this article presents a new integrated visible light communication (VLC) and VLC positioning (VLCP) network for IoT to provide both high-speed communication and high-accuracy positioning services. As the network consists of multiple VLC access points (APs), we propose jointly optimizing the AP selection, bandwidth allocation, adaptive modulation, and power allocation approach to satisfy different QoS requirements of indoor devices while maximizing the network data rate. A low-complexity iterative algorithm is presented to solve the resource management (RM) optimization problem by decomposing it into two subproblems. Finally, a robust handover mechanism and a pedestrian dead reckoning (PDR)-assisted VLCP scheme are presented to maintain good performance under line-of-sight (LOS) blockages. The simulation results verify that the proposed solutions outperform other existing solutions in terms of effectively enhancing the data rate, improving the positioning accuracy, and guaranteeing devices' QoS requirements. In detail, the mean position error is reduced from 20 to 4.3 cm by using our presented integrated VLCP model. The proposed RM approach achieves a satisfied QoS level improvement of up to 20.3% compared with the non-QoS-driven RM approach, and it achieves the high data rate up to 1.31 Gb/s.

Internet of Things (IoT) has attracted much interest due to its wide applications, such as smart city, manufacturing, transportation, and healthcare. Social and cognitive IoT is capable of exploiting social networking characteristics to optimize network performance. Considering the fact that the IoT devices have different Quality-of-Service (QoS) requirements [ranging from ultrareliable and low-latency communications (URLLCs) to minimum data rate], this article presents a QoS-driven social-aware-enhanced device-to-device (D2D) communication network model for social and cognitive IoT by utilizing social orientation information. We model the optimization problem as a multiagent reinforcement learning formulation, and a novel coordinated multiagent deep-reinforcement-learning-based resource management approach is proposed to optimize the joint radio block assignment and the transmission power control strategy. Meanwhile, the prioritized experience replay (PER) and the coordinated learning mechanisms are employed to enable communication links to work cooperatively in a distributed manner, which enhances the network performance and access success probability. The simulation results corroborate the superiority in the performance of the presented resource management approach, and it outperforms other existing approaches in terms of meeting the energy efficiency and the QoS requirements.

Smart factory under Industry 4.0 and industrial Internet of Things (IoT) has attracted much attention from both academia and industry. In wireless industrial networks, industrial IoT and IoT devices have different quality-of-service (QoS) requirements, ranging from ultra-reliable low-latency communications (URLLC) to high transmission data rates. These industrial networks will be highly complex and heterogeneous, as well as the spectrum and energy resources are severely limited. Hence, this article presents a heterogeneous radio frequency (RF)/visible light communication (VLC) industrial network architecture to guarantee the different QoS requirements, where RF is capable of offering wide-area coverage and VLC has the ability to provide high transmission data rate. A joint uplink and downlink energy-efficient resource management decision-making problem (network selection, subchannel assignment, and power management) is formulated as a Markov decision process. In addition, a new deep post-decision state (PDS)-based experience replay and transfer (PDS-ERT) reinforcement learning algorithm is proposed to learn the optimal policy. Simulation results corroborate the superiority in performance of the presented heterogeneous network, and verify that the proposed PDS-ERT learning algorithm outperforms other existing algorithms in terms of meeting the energy efficiency and the QoS requirements.

With the rapid development of Internet of Things (IoT) in the smart city, smart grid and smart industry, indoor communication and positioning are important fields of applications for indoor IoT. This paper presents an integrated visible light communication and positioning (VLCP) system for indoor IoT, in order to provide the high-speed data rate and high-accuracy positioning for IoT devices. where the filter bank multicarrier-based subcarrier multiplexing (FBMC-SCM) technique is exploited to effectively reduce the out-of-band interference (OOBI) on both adjacent communication and positioning subcarriers. After that, we propose a coordinated resource allocation approach for the system with the purpose of maximizing the sum rate while guaranteeing the minimum data rates and positioning accuracy requirements of devices. To this end, we solve the optimization problem by decomposing it into two subproblems, where a low-complexity suboptimal subcarrier allocation approach is proposed and the sequential quadratic programming (SQP) method is adopted to solve the non-linearly constrained power allocation optimization problem. Numerical results verify the superiority in performance of the presented integrated VLCP system for indoor IoT, and the results also reveal that the proposed coordinated resource allocation approach can effectively improve the sum rate and the positioning accuracy compared with other resource allocation approaches.

In this paper, we propose a novel non-orthogonal multiple access (NOMA) technique from a spatial domain (SD) perspective for indoor multiple-input multiple-output visible light communication (MIMO- VLC) systems. By fully exploiting the spatial distributions of light-emitting diode (LED) transmitters in the ceiling and users over the receiving plane, SD-NOMA is achieved by assigning all the users to different LEDs in the MIMO-VLC system. Hence, each user only receives data from a specific LED and users assigned to the same LED can use the overall modulation bandwidth of the system. Moreover, a signal-to-noise ratio (SNR) based LED selection scheme is further proposed for each user to efficiently select its desired LED. The achievable rates of a general indoor MIMO-VLC system using conventional MIMO orthogonal frequency division multiple access (MIMO-OFDMA) and the proposed SD-NOMA are analytically derived. The superiority of SD-NOMA over conventional MIMO-OFDMA for multi-user MIMO-VLC systems is successfully verified by detailed analytical results.

In this paper, we firstly propose a joint subcarrier and power allocation approach for multi-user integrated visible light communication and positioning (VLCP) systems in the presence of practical unique optical constraints. The purpose of the proposed resource allocation approach is to maximize the sum rate of users and meanwhile guarantee the different minimum data rates and positioning accuracy requirements of users. Then, we solve the optimization problem by decomposing it into two subproblems, where a low-complexity suboptimal subcarrier allocation approach is proposed and the sequential quadratic programming (SQP) method is adopted to solve the non-linearly constrained power allocation optimization problem. Numerical results show that the proposed resource allocation approach can effectively improve the sum rate and the positioning accuracy of users compared with other resource allocation approaches.

Visible Light Communication (VLC) systems relying on commercial-off-the-shelf (COTS) devices have gathered momentum recently, due to the pervasive adoption of LED lighting and mobile devices. However, the achievable throughput by such practical systems is still several orders below those claimed by controlled experiments with specialized devices. In this paper, we engineer SynLight aiming to significantly improve the data rate of a practical VLC system. SynLight adopts COTS LEDs as its transmitter, but it innovates in its simple yet delicate driver circuit wiring an array of LED chips in a combinatorial manner. Consequently, modulated signals can directly drive the on-off procedures of individual chip groups, so that the spatially synthesized light emissions exhibit a varying luminance following exactly the modulation symbols. To obtain a readily usable receiver, SynLight interfaces a COTS Photo-Diode with a smartphone through the audio jack. The evaluations on SynLight are both promising and informative: they demonstrate a throughput up to 60 kbps, more than 50× of that achieved by state-of-the-art systems, while suggesting various potentials to further enhance the performance.

A reversed indoor multitarget localization system employing compressive sensing (CS) theory is proposed for the first time in terms of visible light positioning (VLP). Unlike conventional VLP systems, where targets process the received light signals to localize themselves, our system works reversely by using multiple photodiodes (PDs) mounted on the ceiling to localize mobile targets that carry light emitting diodes. By utilizing its nature of sparsity, the problem of multitarget localization is formulated as a problem of sparse matrix reconstruction, and a 3-step workflow is developed to solve the problem. In this workflow, first, a sensing matrix is redesigned by using QR decomposition to enable CS theory. Next, the conventional l1-minimization (l1M) algorithm which is highly vulnerable to noise in solving a localization problem is theoretically analyzed and subsequently improved by adopting a reweighted l1M approach. Finally, a subgrid localization algorithm is proposed to overcome a common unpractical assumption of on-grid locations, tackle the false peak problem in sparse matrix reconstruction, and ultimately improve the localization precision. The feasibility of our system and supporting algorithms is verified through extensive simulations. Our system demonstrates a good positioning accuracy of 7.4 cm by using 25 PDs when SNR = 20 dB. We also investigate the impact of various factors on the positioning performance, and the obtained results provide an insightful reference paving the way to a practical system design.

The explosive growth of the Internet has resulted in tremendous growth of the data centers which primarily serve as the cloud computing backbones. We consider the practical architecture of a real data center where different types of services are implemented in different tiers. We use Model Predictive Control (MPC) based energy aware scheduling algorithms to address the resource allocation problem for deferrable jobs in such a tiered architecture, where the switching cost is accounted for in two different ways. We compare the performance of these two algorithms with respect to the important performance parameters of cumulative electricity cost, cumulative renewable usage and cumulative number of switchings. We discuss the results to provide some insightful understanding on these issues.

This paper proposes a multicast traffic grooming scheme for efficient resource utilization in wavelength- division multiplexing (WDM) mesh networks. This Light-Tree Division -Adjacent Node Component based Grooming scheme (LTD-ANCG) is based on the idea of dividing a light-tree into smaller sub-light-trees. It improves the efficiency of resource utilization and lowers the optical- electronic-optical (OEO) conversion overhead. We use computer simulations to evaluate the performance of the scheme. Our simulations demonstrate that compared with existing algorithms, the new scheme significantly reduces the request blocking probability but can be implemented with very reasonable electronic processing.

Polarisation independent strained bulk RSOAs have been fabricated in the S-band for the first time. In system tests at 1.25 Gbit/s, the devices have been shown to operate over >60 nm with large return Path Loss Capabilities (PLC). The devices are capable of providing >25 dB PLC over a 60 nm span and hence the combination of two RSOAs provides PLC of >25 dB over a wavelength interval of >120 nm (1470 nm to 1590 nm). The temperature performance of the C/L band device has also been studied and a PLC of >20 dB has been shown at 60°C.

It is widely believed that IP over optical networks will be a major component of the next generation Internet However, it is not efficient to map a single multicast IP flow into one light-tree, since the bandwidth of an IP flow required is usually much less than that of a light-tree. In this paper, we study the problem of multicast flow aggregation (MFA) in the IP over optical two-layered networks under the overlay model, which can be defined as follows: given a set of head ends (i.e. optical multicasting sources), each of which can provide a set of contents (i.e. multicast IP flows) with different required transmission bandwidth, and a set of requested content at the access routers (i.e. optical multicasting destinations), find a set of light-trees as well as the optimal aggregation of multicast IP flows in each light-tree. We model MFA by a tri-partite graph with multiple criteria and show that the problem is NP-complete. Optimal solutions are designed by exploiting MFA to formulate an integer linear programming (ILP), with two parameters: the multicast receiving index alpha and the redundant transmitting index beta. We also propose a heuristic algorithm. Finally, we compare the performance of MFA for different combination of alpha and beta via experiments and show our heuristic algorithm is effective for large-scale network in numerical results

An architecture for the copy network that is an integral part of multicast ATM switches is described. The architecture makes use of the property that the broadcast banyan network (BBN) is nonblocking if the active inputs are cyclically concentrated and the outputs are monotone. In the architecture, by employing a token ring reservation scheme, the outputs of the copy network are reserved before a multicast cell is replicated. By the copy principle, the number of copies requested by a multicast call is not limited by the size of the copy network so that very large multicast switches can be configured in a modular fashion. The sequence of cells is preserved in the structure. Though physically separated, buffers within the copy network are completely shared, so that the throughput can reach 100%, and the cell delay and the cell loss probability can be made to be very small. The cell delay is estimated analytically and by computer simulation, and the results of both are found to agree with each other. The relationship between the cell loss probability under various traffic parameters and buffer sizes is studied by computer simulation.>