Fiber-wireless Access Networks Research Articles

An efficient deep learning mechanisms for IoT/Non-IoT devices classification and attack detection in SDN-enabled smart environment

In recent years, the development of Internet of Things (IoT) applications has increased, resulting in higher demands for sufficient bandwidth, data rates, latency, and quality of service (QoS). In advanced communications, managing network resources for allocating IoT services and identifying the exact IoT devices connected to a network is a major concern. The existing studies have introduced various methods for classifying IoT devices in a network. However, the previous studies faced challenges like limited attributes, low efficiency, inappropriate features, and computational complexities. Also, the existing studies failed to concentrate on IoT/Non-IoT classification along with attack detection. Detecting attacks on IoT devices is critical for making network services more effective. Thus, the proposed study introduces an efficient IoT device classification and attack detection mechanism using software defined networking (SDN)-enabled fiber-wireless access networks internet of things (FiWi IoT) architecture. Initially, an effective resource allocation process is performed to mitigate the delay constraint issues by introducing a hybrid parallel neural network-based dynamic bandwidth allocation (DBA) method. Then, the input traffic information is gathered from the resource-efficient SDN-enabled FiWi IoT network, and the input data is pre-processed to eliminate unwanted noises using min-max normalization and standardization. Next, the essential attributes are extracted to attain enhanced classification performance. To reduce the feature dimensionality problem and thereby solve complexity issues, the most optimal features are selected by a new chaotic seagull optimization (CSO) approach. After that, IoT/non-IoT classification is performed using a transformer-driven deep intelligent model. Finally, the attacks are detected and classified by introducing a novel slice attention-based deep capsule autoencoder (SA_DCAE) model. For experimentation, the Python 3.7.0 tool is used in this work, and the performance of proposed classifiers is measured by evaluating varied matrices. Also, the comparison analysis proves the superiority of the proposed techniques to other existing methods.

Seamlessly Converged Fiber-Wireless Access Networks with Dynamic Sub-wavelength Switching and Tunable Photonic mmWave Generation

Seamlessly Converged Fiber-Wireless Access Networks with Dynamic Sub-wavelength Switching and Tunable Photonic mmWave Generation

Hybrid hierarchical aggregation with semi dynamic optical line terminal distribution algorithms optimization for ethernet passive optical networks

The goal of hybrid fiber-wireless (Fi-Wi) access networks is to ubiquitously integrate the accessible vast amounts of optical network bandwidth with wireless network mobility at minimal cost and simple network installation. Fi-Wi networks can employ both Radio over Fiber (RoF) and Radio and Fiber (R&F) technologies. The difference between them is that R&F uses two MAC controls: one for optical fiber and one for wireless networks. One can reduce interference within the wireless subnetwork while avoiding the negative effects of fiber optic propagation delays on the network. RoF, on the other hand, uses MAC control for both optical and wireless networks, resulting in network latency and congestion. This paper demonstrates (i) the use of semi-dynamic bandwidth allocation and (ii) the use of hierarchical frame aggregation for access in next-level integrated Ethernet passive optical network EPON/WLAN-based generations and presents the ongoing research to improve the Quality of Service in wireless and fiber access networks. The study includes an offered load up to 10 Gbps, reaching the up-to-date levels. The obtained results reveal that the data, voice, and video latency are reduced, respectively, by 35%, 25%, and 30%. At the same time, the corresponding throughput is increased, respectively, for data, voice, and video by 35%, 25%, and 30%.

A novel fuzzy-based algorithm for ONU placement in FiWi broadband access network

Optical network unit (ONU) placement is an essential challenge in fiber-wireless (FiWi) access networks, which affects the development cost and quality of services. Recently, some intelligent methods for ONU placement were developed and achieved encouraging results; however, their performance is far from the ideal state. A hybrid ONU placement method (AOFCM) based on Fuzzy C-Means (FCM) and Arithmetic Optimization (AO) algorithm is presented in this work, which makes full use of the merits of both algorithms. The AOFCM is a population-based iterative algorithm that models the ONU placement as a multi-modal optimization problem. It starts the optimization process with a collection of individuals. An individual contains the coordinates of multiple ONUs. AOFCM sequentially applies the FCM and the AO algorithms to the population such that the fitness of each individual is improved. With a test on four placement benchmarks, the proposed AOFCM is proven to significantly improve counterpart algorithms in cost minimization and convergence speed.

Performance analysis of a heterogeneous network employing DAPSK based OFDMA-PON

Recent mobile broadband networks require heterogeneous networks supporting high capacity on demand. A hybrid Fiber-Wireless (Fi-Wi) access network integrating Differential Amplitude and Phase Shift Keying (DAPSK) based — Orthogonal Frequency Division Multiple Access (OFDMA) Passive Optical Network (PON) and 4G wireless network using Radio over Fiber (RoF) technique is proposed. The proposed heterogeneous network is simulated, and the performance is analyzed in terms of Bit Error Rate (BER), Error Vector Magnitude (EVM), Capacity, and Spectral efficiency. The proposed network is simulated considering a higher data rate of 10 and 25 Gbps, and the effect of system parameters like Laser Power, Fiber Length, and Number of users is analyzed. The results show that a higher network capacity of 720 Gbps with an average capacity of about 45 Gbps and a higher spectral efficiency of 4.85 bps/Hz is achieved for the multi-user heterogeneous network link with sixteen users. The minimum value of optical power sufficient to achieve the desired BER is found to be −6 dBm. The suitability of the proposed integrated architecture in supporting multiple services is analyzed by considering different services at each UE. The spectral efficiency of the multi-service link varies from 3 to 4 bps/Hz.

Fiber Wireless (FiWi) Access Network Planning & Deployment using Reptile Search Algorithm

Aim: The aim of this study is the deployment of components in an efficient manner to make a cost-effective FiWi network. Background: Fiber Wireless access network is the boost to broadband access technology for providing network services to Internet users at a lower cost. Deployment of components in FiWi access network is very crucial since it affects the deployment cost and network performance. Objective: We investigate the planning process for efficient placement of components in FiWi access networks. For optimizing the position of components (wireless routers and ONUs) in the network, a novel nature inspired Reptile Search Algorithm (RSA) is proposed in the paper. Methods: Extensive simulation is carried out to implement proposed work. A simulation model and code is developed in MATLAB to get the optimized position of components for existing and proposed algorithms. Result: We compare the performance of proposed algorithm with existing algorithm. The obtained results show that the proposed algorithm has superior performance than the existing algorithm. Conclusion: The present work optimizes the position of components using RSA algorithm. RSA returns the lower number of required wireless routers/ONUs, lesser TCD, increased AONUC, fast convergence rate, lesser execution run time than WSSA algorithm. The outcome of the paper highlights the importance of the proposed work in network planning and component deployment in FiWi access network.

QoS-Aware Reliable Architecture for Broadband Fiber-Wireless Access Networks

In the era of continuous traffic demands, failure of fiber-wireless (FiWi) access network components, such as optical network unit (ONU), access point (AP), or fiber links, compromises the user connectivity and leads to enormous traffic loss. In this article, we propose a novel strategy for FiWi network planning to ensure reliability and survivability of the network. Moreover, our proposed FiWi planning strategy satisfies the required quality of service (QoS) to the users even in the case of failures. It has been shown that by deploying the proposed network framework, user services like received signal strength, throughput, delay, etc., are not significantly affected even when there is a failure. The position of backup ONU-AP is optimized in the FiWi network using a stochastic optimization algorithm. Furthermore, we compare different scenarios wherein backup ONU-AP is equipped with varying antenna configurations, such as omnidirectional antenna, sector antenna, and point-to-point (P2P) link to provide the required services to the users. Simulation results show that the P2P solution offers better services compared to sector or omnidirectional antenna configurations. Moreover, results demonstrate that the proposed survivable FiWi network can be successfully deployed without compromising the QoS requirement of the users. In addition, the article also provides reliability of the proposed survivable FiWi network.

Super-Broadband Optical Access Networks in 6G: Vision, Architecture, and Key Technologies

The sixth generation (6G) mobile networks are envisioned to provide ubiquitous super-band-width access services in the future. Academia and industry are making efforts to explore 6G technologies, especially enabling technologies of 6G radio access networks (RANs). Meanwhile, as the cornerstone of communication networks, optical fiber networks will continue playing a vital role in the 6G era. Next-generation OANs (NG-OANs), which are regarded as the main force of ultra-gigabit access, can provide users with stable super-broadband services, and are expected to support various super-bandwidth applications, including 3D holographic communication, 8K video streaming services, and so on. 6G RANs and NG-OANs are optional solutions to provide super-broadband access services, and their suitable scenarios to serve are different due to their pros and cons. It is envisioned that 6G RANs and NG-OANs will coexist and develop together in the 6G era. Toward this end, we provide in this article a detailed analysis of the architecture, enabling technologies, applications, and challenges of NG-OANs, and perform some comparisons between 6G RANs and NG-OANs on several critical metrics. After that, we propose a vision for the integrated fiber-wireless access networks supporting super-broadband services, and speculate on some potential challenges ahead.

TDM-PON and LTE-A Based Cost-Efficient FiWi Access Network Deployment

In recent times, usage of fixed wireless access (FWA) is gaining momentum even though fiber based existing services such as fiber-to-the-home (FTTH) are widely used for home Internet applications. We explore a time-division multiplexing passive optical network (TDM-PON) and long term evolution advanced (LTE-A) based cost-efficient access network planning strategy for combined usage of FWA and FTTH with the same network infrastructure. The proposed fiber-wireless (FiWi) access network satisfies all feasibility constraints and users’ quality of service (QoS) requirements. The proposed planning method judiciously identifies the network architecture and user service mode (FWA/FTTH).

Photonics-Assisted Millimeter-Wave Communication System Based on Low-Bit Gaussian Mixture Model Adaptive Vector Quantization

The quantization technique with a low-bit resolution can significantly reduce the cost and power consumption of analog-to-digital converter (ADC). It will play an important role in energy conservation and cost reduction for the incoming B5G millimeter-wave (MMW) communication systems. In this paper, we propose and demonstrated experimentally a low-bit Gaussian mixture model (GMM) based non-uniform adaptive vector quantization (AVQ) scheme for the low-cost intensity modulated envelope detection photonics-assisted 28 GHz MMW communication system for the first time. The principles of GMM-based one-dimensional adaptive scalar quantization (ASQ) and multi-dimensional AVQ are first introduced, and then are used to realize the low-bit non-uniform adaptive quantization for reducing the ADC bit resolution of MMW receiver. Furthermore, the performance of traditional uniform quantization, the present <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> -means and proposed GMM-based non-uniform ASQ/AVQ schemes are evaluated and compared in detail. Utilizing the proposed GMM-based AVQ scheme, the ADC quantization resolution in our MMW receiver can be reduced from 5 bits of the traditional uniform quantization to as low as 2 bits, without noticeable performance penalty. Moreover, as compared with the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> -means-based quantization scheme, the MMW receiver enabled by GMM-based ASQ/AVQ scheme can save about half of the quantization time under similar performance. This is mainly because the clustering based on probability converges faster than the Euclidean distance, which significantly reduces the number of iterations required. Therefore, the GMM-based AVQ scheme is a promising solution to realize high performance ADCs with low-bit resolution for future MMW-enabled optical fiber wireless access networks.

Implementation of Marin Predators Algorithm for optimizing the position of multiple Optical Network Units in Fiber Wireless Access Networks

• The problem of the optimal placement of multiple ONUs in FiWi networks is solved using- Marin predators algorithm (MPA) • A cost function is defined in terms of the average distance among ONUs and users. • The optimized locations are used in a developed simulation model to analyze the performance of FiWi network in terms of throughput and average propagation delay of FiWi access network. • The results obtained through the MPA are benchmarked with respect to the Harris Hawks Optimization (HHO), Whale Optimization algorithm (WOA), Moth-Flame optimization (MFO) and Greedy algorithms. Fiber-Wireless (FiWi) access network is a hybrid network that offers huge bandwidth and ubiquity to the users and is expected to play a dominant role in the emerging next generation communication networks. In this manuscript, a novel Marine Predators algorithm (MPA) is used to optimally place multiple Optical Network Units (ONUs) in FiWi access network. The optimized locations are used in a developed simulation model to assess the performance of FiWi network in terms of throughput and average propagation delay considering peer-to-peer communication. Also, the optimizer’s performance was evaluated in terms of fitness value, exploration, exploitation, computational complexity and nature of convergence curve. The MPA's efficiency is benchmarked with respect to a heuristic, Greedy algorithm, as well as existing efficient metaheuristics – Moth-Flame Optimization (MFO), Whale Optimization algorithm (WOA) and Harris-Hawks Optimization (HHO). It was found that MPA outperforms Greedy, MFO, WOA and HHO algorithms in each of the cases.

Development and investigation of 5G fiber-wireless access network based hybrid 16 × 10 Gbps 2048 split TWDM/DWDM super PON for IoT applications

Development and investigation of 5G fiber-wireless access network based hybrid 16 × 10 Gbps 2048 split TWDM/DWDM super PON for IoT applications

A Fault-Tolerant Transmission Scheme in SDN-Based Industrial IoT (IIoT) over Fiber-Wireless Networks.

Driven by the emerging mission-critical and data-intensive applications in industrial intelligent manufacturing, the software-defined network (SDN) based fiber-wireless access network (FiWi) is attracting considerable attention thanks to its capability of central control and large bandwidth. However, the heterogeneity of the network leads to new challenges, since the packet loss can be caused either by the poor channel quality of wireless links or network component failures. A novel and adaptive mechanism combining sparse random linear network coding with parallel transmission (SNC-PT) is proposed to achieve the fault-tolerance against high packet loss rate and any network element malfunction. We illustrate the benefits of using the SNC-PT mechanism to improve fault tolerance by characterizing the network performance with respect to the completion time and goodput along with its relationship to channel quality and node failures. We show that significant performance gains can be obtained in comparison with conventional uncoded transmission based on transmission control protocol (TCP). The simulation results show that the SNC-PT mechanism is fault-tolerant, while it can significantly shorten the data transmission completion time to at least 12% of the baseline and increase the goodput by about 10% compared to other coding schemes such as random linear network coding.

Chaotic local search-based levy flight distribution algorithm for optimizing ONU placement in fiber-wireless access network

Fiber-wireless (FiWi) access networks smartly integrate the mobility, robustness, and ubiquity of wireless networks and the high capacity of fiber networks. A demanding task in FiWi networks is to find the optimal placement of optical network units (ONUs), which leads to resource, throughput, and cost optimization. Several studies have been carried out to solve the ONU placement problem. Most approaches achieve encouraging results; however, they suffer from trapping in local optima, and their performance is far from the ideal state. This paper introduces a chaotic local search-based levy flight distribution (CLS-LFD) algorithm to optimize the position of ONUs in the FiWi network. The proposed algorithm models the ONU placement as a constraint multi-modal optimization problem. The objective is to minimize the overall average distance between ONUs and users. With a test on four ONU placement benchmarks, the proposed CLS-LFD algorithm has shown significant improvement over the canonical LFD algorithm and several counterpart algorithms in terms of convergence performance and cost value.

SDN-Enabled FiWi-IoT Smart Environment Network Traffic Classification Using Supervised ML Models

Due to the rapid growth of the Internet of Things (IoT), applications such as the Augmented Reality (AR)/Virtual Reality (VR), higher resolution media stream, automatic vehicle driving, the smart environment and intelligent e-health applications, increasing demands for high data rates, high bandwidth, low latency, and the quality of services are increasing every day (QoS). The management of network resources for IoT service provisioning is a major issue in modern communication. A possible solution to this issue is the use of the integrated fiber-wireless (FiWi) access network. In addition, dynamic and efficient network configurations can be achieved through software-defined networking (SDN), an innovative and programmable networking architecture enabling machine learning (ML) to automate networks. This paper, we propose a machine learning supervised network traffic classification scheduling model in SDN enhanced-FiWi-IoT that can intelligently learn and guarantee traffic based on its QoS requirements (QoS-Mapping). We capture the different IoT and non-IoT device network traffic trace files based on the traffic flow and analyze the traffic traces to extract statistical attributes (port source and destination, IP address, etc.). We develop a robust IoT device classification process module framework, using these network-level attributes to classify IoT and non-IoT devices. We tested the proposed classification process module in 21 IoT/Non-IoT devices with different ML algorithms and the results showed that classification can achieve a Random Forest classifier with 99% accuracy as compared to other techniques.

Low-cost MIMO-RoF-PON architecture for next-generation integrated wired and wireless access networks

Next-generation integrated fiber-wireless access networks will require low-cost and high-capacity deployment to meet customer demand. A new configuration of radio over fiber–passive optical network (RoF-PON) architecture, including two 60 GHz multiple-input multiple-output (MIMO) based on a 5G universal filtered multicarrier waveform and wired signal utilizing orthogonal frequency division multiplexing (OFDM), is described. At the optical line terminal, MIMO signals are integrated as upper and lower sidebands of the wired OFDM signal. This integration approach, employing single-sideband frequency translation, reduces the complexity of the transceiver design and provides high spectral efficiency because the two MIMO-RoF and wired signals transmit at the same frequency. Improved techniques are also employed to upconvert and downconvert the 60 GHz millimeter wave (MMW), being remote optical heterodyning and self-heterodyning, respectively. The MIMO-RoF signals are therefore transmitted at low frequency over the standard single-mode fiber to avoid the impairments induced at higher frequencies, and the remote optical local oscillator is reused to downconvert the two 60 GHz MMWs, producing a cost-effective system. Simulation results demonstrate very satisfactory network performance when using a downstream link over a 20 km span standard PON.

Energy-Efficient Frame Aggregation Scheme in IoT Over Fiber-Wireless Networks

With the tremendous growth of traffic demand caused by the conventional service and emerging Internet-of-Things (IoT) applications, it is vitally challenging to support seamlessly access for billions of IoT devices along with existing Internet service. Fiber-Wireless (FiWi) access networks is an ideal solution for the next-generation access networks to support both IoT and conventional service. One of the main challenges faced by the design of an FiWi access network is the high energy consumption due to low utilization of optical network units (ONUs) and high control overhead of data transmission. In this article, An adaptive frame aggregation scheme with load transfer is proposed to reduce the energy consumption in FiWi. By evaluating the quality of wireless channel, the proposed scheme adaptively adjusts the length of the aggregated frame to reduce the energy consumption caused by the frequent preemption of wireless channel and the numerous retransmission of data frames resulted by poor channel quality. In the optical backhaul, according to the delay requirements of services with different priorities, the proposed scheme calculates the optimal frame length for each queue and performs load transfer among ONUs to dynamically distribute network load and maximize the sleep rate of ONUs for energy saving. Simulation results and theoretical analysis both unanimously show that the proposed scheme achieves significant amounts of energy saving, while preserving delay performance of various services.

Two-Layer Stackelberg Game-Based Offloading Strategy for Mobile Edge Computing Enhanced FiWi Access Networks

Carbon footprints of both computation and communications infrastructures attract growing public attention, raising concerns about global warming and motivating research efforts in developing energy-efficient solutions. Since Fiber-Wireless (FiWi) access networks have succeeded in interconnecting our digitalized world and mobile/multi-access edge computing (MEC) further removes unnecessary data transmission from optical backbone networks, MEC enhanced FiWi emerges as the win-win architecture for resource-hungry and delay-sensitive mobile apps. However, the assumption of unlimited and free resources offered by FiWi infrastructure is impractical, and energy-efficient offloading mechanisms for MEC enhanced FiWi still remain underexplored, conflicting with globally advocated green communications. This motivates us to design the Two-layer Stackelberg Game based Offloading (TSGO) strategy, including the FiWi layer and mobile edge computation offloading (MeCo) layer subgames capturing bandwidth allocation and offloading decision respectively. Then the backward induction and an iterative algorithm are exploited to acquire the Nash equilibrium of the two-layer Stackelberg game. Furthermore, we propose three energy efficiency benchmarks from both user-side and system-wide perspectives to evaluate mechanisms proposed for, but not limited to, FiWi, MEC, or a combination thereof. Simulation results validate the proposed TSGO strategy, which echoes the profound notion of green communications.

A Bi-Directional Multi-Band, Multi-Beam mm-Wave Beamformer for 5G Fiber Wireless Access Networks

An autonomous beamformer demonstrates multi-beam and multi-band signal transmission and reception with wide field-of-view (FoV) self-steering beam-tracking/-forming for future extreme broadband and dynamic mm-Wave fronthaul applications operating in 5G new radio (NR) frequencies. The experimental results show the novel autonomous beamformer system covering full FoV beamforming (180°) with a wideband 22-40 GHz home-designed antenna array, demonstrating simultaneously multi-band (24.75 and 37 GHz) signals receiving with enhanced mobile multi-Gb/s transmission. A system testbed is further implemented to achieve a mm-Wave bi-directional link between remote radio unit (RRU) and user equipment (UE) in a fiber-wireless integrated network. A wide FoV autonomous signal sensing for angle-of-arrival (AoA) information in receiver is fed forward for mirror-reversed multi-Gb/s signal transmitting over a 10-km fiber and 0.56-m wireless link, addressing fast-changing complex 5G transceiver alignments. To the best of our knowledge, this is the first demonstration of an integrated autonomous beamformer for mm-Wave multi-beam and multi-band mobile applications in a fiber-wireless integrated radio access network.

Optimizing multiple ONUs placement in Fiber-Wireless (FiWi) access network using Grasshopper and Harris Hawks Optimization Algorithms

FiWi network is a multi-domain network that integrates optical and wireless networks. Hybrid fiber-wireless (FiWi) access network endeavours at consolidating the huge amount of available bandwidth of optical networks and the ubiquity, mobility of wireless access networks with the motive of reducing cost and complexity. This manuscript entails investigations undertaken towards optimal placement of multiple Optical Network Units (ONUs) in FiWi network using two recent optimization algorithms named as Harris Hawks Optimization (HHO) and Grasshopper Optimization algorithms (GOA). The results of the investigations are then benchmarked with respect to the Whale Optimization algorithm (WOA). The outcomes demonstrate the superiority of the proposed HHO algorithm over GOA and WOA algorithms, and return the lowest value of cost function; WOA outperforms GOA in terms of improved convergence rate and time complexity. Additionally, the diversification and intensification features of HHO, GOA and WOA have been compared. In order to benchmark the performance of the HHO and GOA optimizers, a series of convergence curves corresponding to different values of controlling parameters are plotted, and their optimal values determined. The dependence of objective function value upon distribution of users and initial placement of ONUs is also studied; the random placement of users and deterministic placement of ONUs return the lowest value of objective function.