Modelling a Learning-Based Dynamic Tree Routing Model for Wireless Mesh Access Networks

Link asymmetry in wireless mesh access networks(WMAN)of Mobile ad-hoc Networks(MANETs)is due mesh routers’transmission range.It is depicted as significant research challenges that pose during the design of network protocol in wireless networks.Based on the extensive review,it is noted that the substantial link percentage is symmetric,i.e.,many links are unidirectional.It is identified that the synchronous acknowledgement reliability is higher than the asynchronous message.Therefore,the process of establishing bidirectional link quality through asynchronous beacons underrates the link reliability of asym-metric links.It paves the way to exploit an investigation on asymmetric links to enhance network functions through link estimation.Here,a novel Learning-based Dynamic Tree routing(LDTR)model is proposed to improve network performance and delay.For the evaluation of delay measures,asymmetric link,interference,probability of transmission failure is evaluated.The proportion of energy consumed is used for monitoring energy conditions based on the total energy capacity.This learning model is a productive way for resolving the routing issues over the network model during uncertainty.The asymmetric path is chosen to achieve exploitation and exploration iteratively.The learning-based Dynamic Tree routing model is utilized to resolve the multi-objective routing problem.Here,the simulation is done with MATLAB 2020a simulation environment and path with energy-efficiency and lesser E2E delay is evaluated and compared with existing approaches like the Dyna-Q-network model(DQN),asymmetric MAC model(AMAC),and cooperative asymmetric MAC model(CAMAC)model.The simulation outcomes demonstrate that the anticipated LDTR model attains superior network performance compared to others.The average energy consump-tion is 250 J,packet energy consumption is 6.5 J,PRR is 50 bits/sec,95%PDR,average delay percentage is 20%.

Joint Resource Allocation and Admission Control in Sliced Fog Radio Access Networks

Network slicing based fog radio access network(F-RAN) has emerged as a promising architecture to support various novel applications in 5 G-and-beyond wireless networks. However, the co-existence of multiple network slices in F-RANs may lead to significant performance degradation due to the resource competitions among different network slices. In this paper, the downlink F-RANs with a hotspot slice and an Internet of Things(Io T) slice are considered, in which the user equipments(UEs) of different slices share the same spectrum. A novel joint resource allocation and admission control scheme is developed to maximize the number of UEs in the hotspot slice that can be supported with desired quality-of-service, while satisfying the interference constraint of the UEs in the Io T slice. Specifically, the admission control and beamforming vector optimization are performed in the hotspot slice to maximize the number of admitted UEs, while the joint sub-channel and power allocation is performed in the Io T slice to maximize the capability of the UEs in the Io T slice tolerating the interference from the hotspot slice. Numerical results show that our proposed scheme can effectively boost the number of UEs in the hotspot slice compared to the existing baselines.

Applications of Access Networks in India

1 IntroductionIndia has a population of over 1 billion, thesecond largest in the world, with a territo-ry area of 3.3 million square kilometresand 28 states; it is the largest country inSouth Asia. Since independence in 1947, In-dia has made great progress on its national e-conomy and infrastructure. By December

The Interplay between Artificial Intelligence and Fog Radio Access Networks

The interplay between artificial intelligence(AI) and fog radio access networks(F-RANs) is investigated in this work from two perspectives: how F-RANs enable hierarchical AI to be deployed in wireless networks and how AI makes F-RANs smarter to better serve mobile devices. Due to the heterogeneity of processing capability, the cloud, fog, and device layers in F-RANs provide hierarchical intelligence via centralized, distributed, and federated learning. In addition, cross-layer learning is also introduced to further reduce the demand for the memory size of the mobile devices. On the other hand, AI provides F-RANs with technologies and methods to deal with massive data and make smarter decisions. Specifically, machine learning tools such as deep neural networks are introduced for data processing, while reinforcement learning(RL) algorithms are adopted for network optimization and decisions. Then, two examples of AI-based applications in F-RANs, i.e., health monitoring and intelligent transportation systems, are presented, followed by a case study of an RL-based caching application in the presence of spatio-temporal unknown content popularity to showcase the potential of applying AI to F-RANs.

Hierarchical Content Caching in Fog Radio Access Networks:Ergodic Rate and Transmit Latency

In order to alleviate capacity constraints on the fronthaul and decrease the transmit latency, a hierarchical content caching paradigm is applied in the fog radio access networks(F-RANs). In particular, a specific cluster of remote radio heads is formed through a common centralized cloud at the baseband unit pool, while the local content is directly delivered at fog access points with edge cache and distributed radio signal processing capability. Focusing on a downlink F-RAN, the explicit expressions of ergodic rate for the hierarchical paradigm is derived. Meanwhile, both the waiting delay and latency ratio for users requiring a single content are exploited. According to the evaluation results of ergodic rate on waiting delay, the transmit latency can be effectively reduced through improving the capacity of both fronthaul and radio access links. Moreover, to fully explore the potential of hierarchical content caching, the transmit latency for users requiring multiple content objects is optimized as well in three content transmission cases with different radio access links. The simulation results verify the accuracy of the analysis, further show the latency decreases significantly due to the hierarchical paradigm.

Low-cost,large-coverage,and high-flexibility coherent PON for next-generation access networks:advances,challenges,and prospects[Invited]

Increasing bandwidth requirements have posed significant challenges for traditional access networks.It is difficult for intensity modulation/direct detection to meet the power budget and flexibility requirements of the next-generation passive optical network(PON)at 100G and beyond considering the new requirements.This is driving researchers to develop novel optical access technologies.Low-cost,wide-coverage,and high-flexibility coherent PON is emerging as a strong contender in the competition.In this article,we will review technologies that reduce the complexity of coherent PON(CPON),enabling it to meet the commercial requirements.Also,advanced algorithms and architectures that can enhance system coverage and flexibility are also discussed.

Scenario Modeling-Aided AP Placement Optimization Method for Indoor Localization and Network Access

Owing to the ubiquity of wireless networks and the popularity of WiFi infrastructures,received signal strength(RSS)-based indoor localization systems have received much attention.The placement of access points(APs)significantly influences localization accuracy and network access.However,the indoor scenario and network access are not fully considered in previous AP placement optimization methods.This study proposes a practical scenario modelingaided AP placement optimization method for improving localization accuracy and network access.In order to reduce the gap between simulation-based and field measurement-based AP placement optimization methods,we introduce an indoor scenario modeling and Gaussian process-based RSS prediction method.After that,the localization and network access metrics are implemented in the multiple objective particle swarm optimization(MOPSO)solution,Pareto front criterion and virtual repulsion force are applied to determine the optimal AP placement.Finally,field experiments demonstrate the effectiveness of the proposed indoor scenario modeling method and RSS prediction model.A thorough comparison confirms the localization and network access improvement attributed to the proposed anchor placement method.

Distortion minimization for multimedia transmission in NOMA HAP-UAV integrated aerial access networks

Aerial access networks have been envisioned as a promising 6G solution to enhance the ground communication systems in both coverage and capacity. To better utilize the spectrum and fully explore different channel characteristics, this paper constructs an integrated network comprising the High Altitude Platform(HAP) and Unmanned Air Vehicles(UAVs) with the NonOrthogonal Multiple Access(NOMA) technology. In order to improve the transmission quality of images and videos, a power management scheme is proposed to minimize the distortion of the transmissions from the HAP and UAVs to the terminals. The power control is formulated as a non-convex problem constrained by the maximal transmit power and the minimal terminal rate requirements. The variable substitution and the first-order Tailor’s expansion is used to transform it into a sequence of convex problems, which are subsequently solved through the gradient projection method. Simulation demonstrates the signal distortion and error rate improvement achieved by the proposed algorithm.

50 GHz optical true time delay beamforming in hybrid optical/mm-wave access networks with multi-core optical fiber distribution

We propose and experimentally validate an optical true time delay beamforming scheme with straightforward integration into hybrid optical/millimeter（mm）-wave access networks. In the proposed approach, the most complex functions, including the beamforming network, are implemented in a central office, reducing the complexity and cost of remote antenna units. Different cores in a multi-core fiber are used to distribute the modulated signals to high-speed photodetectors acting as heterodyne mixers. The mm-wave carrier frequency is fixed to 50 GHz（VBand）, thereby imposing a progressive delay between antenna elements of a few picoseconds. That true time delay is achieved with an accuracy lower than 1 ps and low phase noise.

Deep reinforcement learning based computation offloading and resource allocation for low-latency fog radio access networks

Fog Radio Access Networks(F-RANs)have been considered a groundbreaking technique to support the services of Internet of Things by leveraging edge caching and edge computing.However,the current contributions in computation offloading and resource allocation are inefficient;moreover,they merely consider the static communication mode,and the increasing demand for low latency services and high throughput poses tremendous challenges in F-RANs.A joint problem of mode selection,resource allocation,and power allocation is formulated to minimize latency under various constraints.We propose a Deep Reinforcement Learning(DRL)based joint computation offloading and resource allocation scheme that achieves a suboptimal solution in F-RANs.The core idea of the proposal is that the DRL controller intelligently decides whether to process the generated computation task locally at the device level or offload the task to a fog access point or cloud server and allocates an optimal amount of computation and power resources on the basis of the serving tier.Simulation results show that the proposed approach significantly minimizes latency and increases throughput in the system.

Recent Advances of Multi-Channel Transmission in Metro Access Networks

We discuss the concept of coarse wavelength-division multiplexing (CWDM) for metro networks. After reviewing the requirements on components such as lasers and fiber, we propose different architectures for a flexible upgrade of existing CWDM systems.

Performance improvement for applying network virtualization in fiber-wireless(FiWi) access networks

Fiber-wireless(FiWi) access networks, which are a combination of fiber networks and wireless networks,have the advantages of both networks, such as high bandwidth, high security, low cost, and flexible access. However,with the increasing need for bandwidth and types of service from users, FiWi networks are still relatively incapable and ossified. To alleviate bandwidth tension and facilitate new service deployment, we attempt to apply network virtualization in FiWi networks, in which the network's control plane and data plane are separated from each other.Based on a previously proposed hierarchical model and service model for FiWi network virtualization, the process of service implementation is described. The performances of the FiWi access networks applying network virtualization are analyzed in detail, including bandwidth for links, throughput for nodes, and multipath flow transmission.Simulation results show that the FiWi network with virtualization is superior to that without.

Pricing-based edge caching resource allocaƟon in fog radio access networks

The edge caching resource allocation problem in Fog Radio Access Networks(F-RANs)is investigated.An incentive mechanism is introduced to motivate Content Providers(CPs)to participate in the resource allocation procedure.We formulate the interaction between the cloud server and the CPs as a Stackelberg game,where the cloud server sets nonuniform prices for the Fog Access Points(F-APs)while the CPs lease the F-APs for caching their most popular contents.Then,by exploiting the multiplier penalty function method,we transform the constrained optimization problem of the cloud server into an equivalent non-constrained one,which is further solved by using the simplex search method.Moreover,the existence and uniqueness of the Nash Equilibrium(NE)of the Stackelberg game are analyzed theoretically.Furthermore,we propose a uniform pricing based resource allocation strategy by eliminating the competition among the CPs,and we also theoretically analyze the factors that affect the uniform pricing strategy of the cloud server.We also propose a global optimization-based resource allocation strategy by further eliminating the competition between the cloud server and the CPs.Simulation results are provided for quantifying the proposed strategies by showing their efficiency in pricing and resource allocation.

A Distributed Intranet/Web Solution to Integrated Management of Access Networks

In this article, we describe the present situation of accessnetwork management, enumerate a few prob- lems during the developmentof network management systems, then put forward a distributedIntranet/Web solution named iMAN to the integrated management ofaccess networks, present its architecture and protocol stack, and de-scribe its application in practice.

Beamforming and fronthaul compression design for intelligent reflecting surface aided cloud radio access networks

Owing to the inherent central information processing and resource management ability,the cloud radio access network(C-RAN)is a promising network structure for an intelligent and simplified sixth-generation(6G)wireless network.Nevertheless,to further enhance the capacity and coverage,more radio remote heads(RRHs)as well as high-fidelity and low-latency fronthaul links are required,which may lead to high implementation cost.To address this issue,we propose to exploit the intelligent reflecting surface(IRS)as an alternative way to enhance the C-RAN,which is a low-cost and energy-efficient option.Specifically,we consider the uplink transmission where multi-antenna users communicate with the baseband unit(BBU)pool through multi-antenna RRHs and multiple IRSs are deployed between the users and RRHs.RRHs can conduct either point-to-point(P2P)compression or Wyner-Ziv coding to compress the received signals,which are then forwarded to the BBU pool through fronthaul links.We investigate the joint design and optimization of user transmit beamformers,IRS passive beamformers,and fronthaul compression noise covariance matrices to maximize the uplink sum rate subject to fronthaul capacity constraints under P2P compression and Wyner-Ziv coding.By exploiting the Arimoto-Blahut algorithm and semi-definite relaxation(SDR),we propose a successive convex approximation approach to solve non-convex problems,and two iterative algorithms corresponding to P2P compression and Wyner-Ziv coding are provided.Numerical results verify the performance gain brought about by deploying IRS in C-RAN and the superiority of the proposed joint design.

Joint uplink and downlink resource allocation for low-latency mobile virtual reality delivery in fog radio access networks

Fog radio access networks(F-RANs),in which the fog access points are equipped with communication,caching,and computing functionalities,have been anticipated as a promising architecture for enabling virtual reality(VR)applications in wireless networks.Although extensive research efforts have been devoted to designing efficient resource allocation strategies for realizing successful mobile VR delivery in downlink,the equally important resource allocation problem of mobile VR delivery in uplink has so far drawn little attention.In this work,we investigate a mobile VR F-RAN delivery framework,where both the uplink and downlink transmissions are considered.We first characterize the round-trip latency of the system,which reveals its dependence on the communication,caching,and computation resource allocations.Based on this information,we propose a simple yet efficient algorithm to minimize the round-trip latency,while satisfying the practical constraints on caching,computation capability,and transmission capacity in the uplink and downlink.Numerical results show that our proposed algorithm can effectively reduce the round-trip latency compared with various baselines,and the impacts of communication,caching,and computing resources on latency performance are illustrated.

Hierarchical micro-mobility management in high-speed multihop access networks

This article integrates the hierarchical micro-mobility management and the high-speed multihop access networks （HMAN）, to accomplish the smooth handover between different access reuters. The proposed soft handover scheme in the high-speed HMAN can solve the micro-mobility management problem in the access network. This article also proposes the hybrid access muter （AR） advertisement scheme and AR selection algorithm, which uses the time delay and stable route to the AR as the gateway selection parameters. By simulation, the proposed micro-mobility,management scheme can achieve high packet delivery fraction and improve the lifetime of network.

Integral sliding-mode robust observer-based congestion control for wireless access networks

Designing a robust active queue management(RAQM)is mandatory to avoid congestion in networks with wireless access links,because transmission control protocol(TCP)can detect con-gestion after its occurrence in a communication network and wireless links suffer from bottleneck capacity variations caused by fading and packet error rate(PER)in the acknowledgement pack-ets.Furthermore,the average window size cannot be measured explicitly from the output signal and input and state delay are imposed to a network,which complicate theRAQMdesign problem in nonlinear models.So,the main contribution of this study is to design a robust observer based control procedure based on integral sliding mode protocol to estimate the average window size,to control congestion in a TCP/RAQM network and to compensate input and state delay.Sim-ulation results via professional simulator NS-2 and SIMULINK confirm that the procedure can effectively estimate the window size and can robustly avoid congestion.

Ubiquitous Access Technology for Wireless Digital Home Networks

As an important branch of telecommunication technology, digital home networks have quickly developed in recent years. Although architecture of the digital home network based on telecommunication networks has been standardized in China, only wireless access is defined to be allowable. Therefore, it becomes the focus of further research how to establish a wireless digital home network. This article proposes the concept and shows the architecture of ubiquitous access for wireless digital home networks. Moreover, key technologies for ubiquitous access are discussed here, including cognitive radio, the concept of wireless Mesh, generic link transfer mechanism, Quality of Service (QoS) guarantee mechanism, Electromagnetic Compatibility (EMC) and coexistence of heterogeneous systems.

Challenges for beyond 5G:ultra-densification of radio access network

Ultra-densification of radio access network(RAN)is a key to efficiently support the exponentially growing mobile data traffic in 5 G era.Furthermore,extremely high frequency band like mm Wave band was utilized to solve the bandwidth shortage problem.However,untra-dense reusing the same radio resource produced severe interference.And the mm Wave link was very harsh due to frequent blockage by obstacles.Therefore a new RAN architecture needed to be introduced to realize ultra-reliable communications in such a severe radio propagation environment.An architecture of distributed MIMO based RAN was presented.Then,enhanced interference coordination(e IC)was described.Finally,the effectiveness of distributed MIMO based RAN with e IC by computer simulation was showed.