A Novel Terabit Grid-of-Beam Optical Wireless Multi-User Access Network With Beam Clustering

In this paper, we put forward a proof of concept for sixth generation (6G) Terabit infrared (IR) laser-based indoor optical wireless networks. We propose a novel double-tier access point (AP) architecture based on an array of arrays of vertical cavity surface emitting lasers (VCSELs) to provide a seamless grid-of-beam coverage with multi-Gb/s per beam. We present systematic design and thorough analytical modeling of the AP architecture, which are then applied to downlink system modeling using non-imaging angle diversity receivers (ADRs). We propose static beam clustering with coordinated multi-beam joint transmission (CoMB-JT) for network interference management and devise various clustering strategies to address inter-beam interference (IBI) and inter-cluster interference (ICI). Non-orthogonal multiple access (NOMA) and orthogonal frequency division multiple access (OFDMA) schemes are also adopted to handle intra-cluster interference, and the resulting signal-to-interference-plus-noise ratio (SINR) and achievable data rate are derived. The network performance is studied in terms of spatial distributions and statistics of the downlink SINR and data rate through extensive computer simulations. The results demonstrate that data rates up to 15 Gb/s are achieved within the coverage area and a properly devised clustering strikes a balance between the sum rate and fairness depending on the number of users.

Intelligent Reflecting Surfaces assisted Laser-based Optical Wireless Communication Networks

The increasing demand for wireless networks of higher capacity requires key-enabling technologies. Optical wireless communication (OWC) arises as a complementary technology to radio frequency (RF) systems that can support high aggregate data rates. However, OWC systems face some challenges including beam-blockage. Intelligent reflecting surfaces (IRSs) can offer alternative pathways for the optical signal, ensuring continuous connectivity. In this work, we investigate the potential of using IRS in an indoor OWC network. In particular, we define a system model of indoor OWC that employs IRS in conjunction with angle diversity transmitters (ADT) using vertical-cavity surface-emitting laser (VCSEL) arrays. The VCSEL beam is narrow, directed, and easy to block, however, it can deliver high data rates under eye safety regulations. Simulation results show that the deployment of IRS can significantly improve the achievable data rates of Laser-based OWC systems.

Deep Learning-based Power Allocation in Rate Splitting Optical Wireless Networks

Optical wireless communication (OWC) provides high aggregate data rates in the range of Terabits per second (Tb/s). Specifically, OWC using infrared lasers as transmitters has been considered as a strong candidate in the next generation of wireless communication. Rate splitting (RS) is a transmission scheme derived to improve spectral efficiency in dense wireless networks. In RS, the transmitted power is allocated to different messages, common and private messages, serving multiple users simultaneously, where each user can decode the desired message following a certain procedure. Moreover, two-tier precoding RS scheme has been proposed to overcome the limitations of traditional RS in multi-group scenarios. In this context, power allocation (PA) is a crucial issue, which can affect the performance of RS. Therefore, we formulate a PA optimization problem to enhance the data rates of RS-based OWC networks. However, such optimization problems are complex due to the use of different messages intended to the users. In this paper, we design and train a deep neural network (DNN) model to determine the power allocated to the messages of RS, while fulfilling the demands of users. The results show the accuracy of our trained DNN model when used in an online phase.

Multiuser beam steering OWC system based on NOMA

In this paper, we propose applying Non-Orthogonal Multiple Access (NOMA) technology in a multiuser beam steering OWC system. We study the performance of the NOMA-based multiuser beam steering system in terms of the achievable rate and Bit Error Rate (BER). We investigate the impact of the power allocation factor of NOMA and the number of users in the room. The results show that the power allocation factor is a vital parameter in NOMA-based transmission that affects the performance of the network in terms of data rate and BER.

Relay Assisted Multiuser OWC Systems under Human Blockage

This paper proposes using cooperative communication based on optoelectronic (O-E-O) amplify-and-forward relay terminals to reduce the influence of the blockage and shadowing resulting from human movement in a beam steering Optical Wireless Communication (OWC) system. The simulation results indicate that on average, the outage probability of the cooperative communication mode with O-E-O relay terminals is two orders of magnitude lower than the outage probability of the system without relay terminals.

AI-Driven Resource Allocation in Optical Wireless Communication Systems

Visible light communication (VLC) is a promising solution to satisfy the extreme demands of emerging applications. VLC offers bandwidth that is orders of magnitude higher than what is offered by the radio spectrum, hence making best use of the resources is not a trivial matter. There is a growing interest to make next generation communication networks intelligent using AI based tools to automate the resource management and adapt to variations in the network automatically as opposed to conventional handcrafted schemes based on mathematical models assuming prior knowledge of the network. In this article, a reinforcement learning (RL) scheme is developed to intelligently allocate resources of an optical wireless communication (OWC) system in a HetNet environment. The main goal is to maximise the total reward of the system which is the sum rate of all users. The results of the RL scheme are compared with that of an optimization scheme that is based on Mixed Integer Linear Programming (MILP) model.

Energy Efficient Laser-Based Optical Wireless Communication Networks

Rising data demands are a growing concern globally. The task at hand is to evolve current communication networks to support enhanced data rates while maintaining low latency, energy consumption and costs. To meet the above challenge, Optical Wireless Communication (OWC) technology is proposed as a solution to complement traditional Radio Frequency (RF) based communication systems. Recently, Vertical Cavity Surface Emitting Lasers (VCSELS) have been considered for data transmission in OWC indoor environments due to their ability to transmit power through narrow, near-circular beams to receivers. In this paper, we study the energy efficiency of a VCSEL-based OWC system in an indoor environment and compare it to that of a Light Emitting Diode (LED) based system. The main findings show that the VCSEL system performs better and has higher energy efficiency.

Rate Splitting for 6G Optical Wireless Networks

This paper evaluates the performance of rate splitting (RS), a robust interference management scheme, in an optical wireless communication (OWC) network that uses infrared lasers referred to as vertical-cavity surface-emitting lasers (VCSELs) as optical transmitters. In 6G OWC, providing high spectral and energy efficiency requires advanced multiple access schemes that can serve multiple users simultaneously in a non-orthogonal fashion. In this context, RS has the potential to manage multi-user interference at high data rates compared to orthogonal transmission schemes. Simulation results show the high performance of RS compared to baseline approaches.

Multi-User Rate Splitting in Optical Wireless Networks

Optical wireless communication (OWC) has recently received massive interest as a new technology that can support the enormous data traffic increasing on daily basis. Laser-based OWC networks can provide terabits per second (Tbps) aggregate data rates. However, the emerging OWC networks require clusters of optical transmitters to provide uniform coverage for multiple users. In this context, multi-user interference (MUI) is a crucial issue that must be managed efficiently to provide high spectral efficiency. Rate splitting (RS) is proposed as a transmission scheme to serve multiple users simultaneously by splitting the message of a given user into common and private messages, and then, each user decodes the desired message following a certain procedure. In radio frequency (RF) networks, RS provides higher spectral efficiency compared with orthogonal and non-orthogonal transmission schemes. Considering the high density of OWC networks, the performance of RS is limited by the cost of providing channel state information (CSI) at transmitters and by the noise resulting from interference cancellation. In this work, a user-grouping algorithm is proposed and used to form multiple groups, each group contains users spatially clustered. Then, an outer precoder is designed to manage inter-group interference following the methodology of blind interference alignment (BIA), which reduces the requirements of CSI at RF or optical transmitters. For intra-group interference, RS is applied within each group where the users belonging to a given group receive a unique common message on which their private messages are superimposed. Furthermore, an optimization problem is formulated to allocate the power among the private messages intended to all users such that the sum rate of the network is maximized.

Energy Efficient UAV-Based Service Offloading over Cloud-Fog Architectures

Unmanned Aerial Vehicles (UAVs) are poised to play a central role in revolutionizing future services offered by the envisioned smart cities, thanks to their agility, flexibility, and cost-efficiency. UAVs are being widely deployed in different verticals including surveillance, search and rescue missions, delivery of items, and as an infrastructure for aerial communications in future wireless networks. UAVs can be used to survey target locations, collect raw data from the ground (i.e., video streams), generate computing task(s) and offload it to the available servers for processing. In this work, we formulate a multi-objective optimization framework for both the network resource allocation and the UAV trajectory planning problem using Mixed Integer Linear Programming (MILP) optimization model. In consideration of the different stake holders that may exist in a Cloud-Fog environment, we minimize the sum of a weighted objective function, which allows network operators to tune the weights to emphasize/de-emphasize different cost functions such as the end-to-end network power consumption (EENPC), processing power consumption (PPC), UAVs total flight distance (UAVTFD), and UAVs total power consumption (UAVTPC). Our optimization models and results enable the optimum offloading decisions to be made under different constraints relating to EENPC, PPC, UAVTFD and UAVTPC which we explore in detail. For example, when the UAVs propulsion efficiency (UPE) is at its worst (10% considered), offloading via the macro base station is the best choice and a maximum power saving of 34% can be achieved. Extensive studies on the UAVs coverage path planning (CPP) and computation offloading have been conducted, but none has tackled the issue in a practical Cloud-Fog architecture in which access, metro and core layers are considered in the service offloading in a distributed architecture like the Cloud-Fog.