Backhaul Network Research Articles

Post-Disaster Communications: Enabling Technologies, Architectures, and Open Challenges

The number of disasters has increased over the past decade where these calamities significantly affect the functionality of communication networks. In the context of 6G, airborne and spaceborne networks offer hope in disaster recovery to serve the underserved and to be resilient in calamities. Therefore, our paper reviews the state-of-the-art literature on post-disaster wireless communication networks and provides insights for the future establishment of such networks. In particular, we first give an overview of the works investigating the general procedures and strategies for facing any large-scale disaster. Then, we present technological solutions for post-disaster communications, such as the recovery of the terrestrial infrastructure, installing aerial networks, and using spaceborne networks. Afterwards, we shed light on the technological aspects of post-disaster networks, primarily the physical and networking issues. We present the literature on channel modeling, coverage and capacity, radio resource management, localization, and energy efficiency in the physical layer part, and discuss the integrated space-air-ground architectures, routing, delay-tolerant/software-defined networks, and edge computing in the networking layer part. This paper also includes interesting simulation results which can provide practical guidelines about the deployment of ad hoc network architectures in emergency scenarios. Finally, we present several promising research directions, namely backhauling, cache-enabled and intelligent reflective surface-enabled networks, placement optimization of aerial base stations (ABSs), and the mobility-related aspects that come into play when deploying aerial networks, such as planning their trajectories and the consequent handovers (HOs).

Joint Link Scheduling and Routing in Two-Tier RF-Energy-Harvesting IoT Networks

This article considers routing and link scheduling in a two-tier wireless backhaul network. The first tier consists of routers and the second tier consists of radio frequency (RF)-energy-harvesting Internet-of-Things (IoT) devices that rely on routers for energy. Our aim is to derive the shortest time division multiple access (TDMA) link schedule that satisfies the traffic demand of routers and energy demand of IoT devices. We formulate a linear program (LP) to jointly derive a routing and link schedule solution. We also propose a heuristic link scheduler called transmission set generation (TSG) to generate transmission sets and to derive the transmit power allocation of routers. In addition, we present a novel routing metric that considers RF-energy-harvesting devices on a given path. TSG on average achieves 31.25% shorter schedules as compared to competing schemes. Finally, our novel routing metric results in link schedules that are at most 24.75% longer than those computed by LP.

Towards InAs/InP Quantum-Dash Laser-Based Ultra-High Capacity Heterogeneous Optical Networks: A Review

The unprecedented increase in internet traffic witnessed in the last few years has pushed the community to explore heterogeneous optical networks, including free-space-optics (FSO) communication, radio-over-fiber (RoF), wireless (WL), and their convergent hybrid technologies. This stems from the possibility of seamless integration with the existing fiber-optic backhaul networks while providing much-needed flexibility and scalability. Moreover, efficient optical transceivers, particularly light sources in the form of semiconductor laser diodes, are key in meeting the future demands of the next generation green optical access networks. In this respect, InAs/InP Quantum-dash (Qdash) nanostructure-based lasers have shown tremendous progress in the past few years with applications spanning from a wavelength division multiplexed (WDM) optical communication to recently, millimeter-wave (MMW) over fiber networks. This waveguide-based laser diode (LD) has demonstrated a rule-changing broad multi-wavelength lasing emission, thanks to the inherent and wavelength-tunable wide gain profile offered by the Qdash active-gain region covering S- to U-band regions. Moreover, exploiting mode-locking and optical injection locking assisting techniques, highly coherent InAs/InP Qdash comb laser source at 1550 nm and 1610 nm have been respectively realized, thus opening a new paradigm for their potential applications in green optical and 5G access networks. In this work, progress on utilizing InAs/InP Qdash LD, supporting several sub-carriers, in energy-efficient ~1550 nm and ~1610 nm WDM heterogeneous optical networks with single-mode-fibers (SMF) has been highlighted, exhibiting aggregate data rates of 11 – 12 Tb/s by employing a single device, and accommodating PAM4 and higher-order 32-QAM modulation schemes. Moreover, the recent deployment of this LD in the RoF domain, targeting MMW frequency band, for convergent fiber-wireless networks, is also summarized, with demonstrated 25 to >100 GHz MMW beat-tone frequency generates and transmission of up to 24 Gb/s.

Design of Survivable Wireless Backhaul Networks Withreliability Considerations

Design of Survivable Wireless Backhaul Networks Withreliability Considerations

Power Efficiency Analysis of Spatial Diversity Based Vertical FSO Links With Pointing Error in Multiple Beam Transmissions

In this paper, we analyzed the diversity performance with increased pointing error caused by multiple beam transmissions for spatial diversity based vertical free space optical (FSO) back-haul links. For power-limited FSO systems, the spatial diversity technique can be employed to mitigate the atmospheric fading issues in vertical FSO links. However, the arrangement of multiple transmitters to achieve independent channels can cause additional alignment errors in the misalignment detection process of pointing, acquisition, and tracking (PAT) systems, as demonstrated by the experiment results. The increase of misalignment makes the pointing loss severe to reduce the achievable diversity gain, which results in insufficient received power to satisfy the system requirements. The system optimization with the statistical misalignment model can mitigate the effect of increased pointing error and improve the diversity gain as the number of channels increases. The proposed scheme provides an enhanced link margin for designing seamless FSO wireless back-haul networks for next-generation wireless communication systems.

NSGA-II Based Joint Topology and Routing Optimization of Flying Backhaul Networks

This paper addresses the problem of optimizing the deployment of Flying Backhaul Networks (FBNs). The latter comprise Unmanned Aerial Vehicles (UAVs), which are used as access points to provide coverage to a set of ground nodes deployed in a target area. The optimization problem is addressed by means of a Multi-Objective Optimization Algorithm (MOEA), which calculates Pareto curves of UAV placement, providing different trade-offs between the considered objectives: (1) to minimize the number of UAVs, and (2) to maximize the Packet Delivery Ratio (PDR). The selected MOEA is NSGA-II. An embedded single objective Genetic Algorithm (inner-GA) is used to optimize routing, finding the paths that maximize the PDR. In order to obtain consistent solutions for the PDR taking into account MAC layer contention, the scheme makes use of an existing fixed-point algorithm (FPA). Simulation results were obtained for different scenarios combining average versus maximin PDR objective funtions, two different routing optimization algorithms, as well as single sink versus multiple sink traffic patterns.

An Energy-Efficient Internet of Things Relaying System for Delay-Constrained Applications

The emerging Internet-of-things (IoT) systems contain a large number of small wireless devices with limited energy, communication, and computational capabilities. In such systems, a helping station located between the IoT devices and backhaul servers can be deployed to broadcast the IoT devices to the backhaul networks. This paper investigates a hybrid energy-efficient framework using multiple energy harvested relays with data buffering capabilities. The relays are powered by a hybrid energy supply consisting of a traditional electric grid and renewable energy grid. We propose an energy efficient novel approach aiming to support the wireless uplink transmission from IoT devices to backhaul servers with an acceptable delay threshold or transmission deadline. A mathematical mixed-integer linear programming (MILP) optimization problem is formulated to optimize the relays’ placement and energy consumption considering the association between relays and devices, instantaneous relays’ battery level, and transmit power budget. Due to the non-convex nature of the formulated optimization problem, we propose two heuristic low-complexity solutions to solve this problem. Finally, we compare the performance of the proposed algorithms with exhaustive search solutions as a benchmark.

Challenges and Research Advancement in 5G Wireless Backhaul Networks

5G networks should achieve Gigabit speed in the future cellular network. Getting higher speed is a considerable challenge to manage the 5G Wireless Backhaul Network functionally. This research studies two network wireless backhaul architectures such as small cell networks and millimeter-wave transmission technologies for Centralized and Distributed scenarios. In addition, for various network topologies and wireless backhaul network frequency bands, energy efficiency is compared. Numeric comparative findings give guidance for deploying inexpensive and high energy capability of future 5G wireless backhaul networks

Non-Mechanical Beam Steering and Adaptive Beam Control Using Variable Focus Lenses for Free-Space Optical Communications

Free-space optical communications (FSOCs) are gaining popularity as a promising solution to the capacity crunch of aerial and satellite backhaul networks for next-generation mobile communication systems. A major technical challenge associated with such FSOC systems in motion is the pointing, acquisition, and tracking (PAT). To facilitate PAT, it is absolutely necessary to steer the optical beam over a wide angle and also adjust the beam divergence angle adaptively to the link condition and the amount of pointing error. The conventional methods to steer the optical beam and/or to adjust the beam divergence angle rely on mechanical mechanisms. Recently, the optical beam steering technique using variable focus lenses has been proposed and demonstrated. By using an on-axis variable focus lens followed by two decentered variable focus lenses, we can steer the optical beam over a wide range in a non-mechanical fashion. In this paper, we explore the possibility of using variable focus lenses for the realization of beam steering and adaptive beam control for FSOCs. For this purpose, we employ three variable focus lenses, one on-axis lens for adaptive beam divergence control and two decentered lenses for two-dimensional beam steering. We demonstrate the simultaneous beam steering and adaptive beam control capability of this variable focus lens-based system over a 104-m long free-space optical link. We evaluate the maximum beam steering angle and beam quality as we vary the offset distance of decentered variable focus lenses. Also evaluated experimentally is the impact of gravity on the beam quality. Finally, we show that the beam steering and adaptive beam control techniques implemented by variable focus lenses improve the performance of 10-Gb/s FSOC system considerably in the presence of pointing errors.

Application Aware Multiple Constraint Optimal Paths for Transport Network Using SDN

The backhaul networks for the 5G networks consist of different links that handle massive heterogeneous traffic. Fulfilling the QoS requirement of users to comply with the growth and increasing revenue is a challenge for the service providers. We address QoS parameters like bandwidth and delay for the user’s transport network. We use Software-Defined Networking and solve this problem. We have added a component Flowlet based Multiple Constraint Optimal Paths (MCOP) for packet forwarding by taking input as QoS requirements and creating a logical network in backhaul transport networks when needed for the elephant traffic. Due to security reasons, the transport network cannot access L7 to identify the application type. We have added an application identification component to detect the traffic type. We use an experimental platform using mininet and OpenFlow. Our proposed algorithm has higher QoS performance than the conventional method after the primary link exhaust capacity. It takes around 20 to 30 packets to learn the traffic type up to L6 parameters. Our approach identifies 73.10% of traffic type. The multipath usage helps improve revenue growth by assuring the dynamic allocation of the resources to the customer for elephant flow with the required QoS.

Wireless Last Mile Study in Rural Areas

Internet access has become a primary human need. During the COVID 19 pandemics, almost all activities such as studying and working online. However, several rural areas still did not have internet access due to weak cellular signals. Internet access in rural areas can have various alternatives, such as VSAT (satellite). It needs an inexpensive and precise way to complete the internet access coverage because many customers were concentrated in areas far from the VSAT terminal. WLAN 802.11n was an alternative way to expand the range of internet coverage with low cost and easy implementation. Our case study uses the 5GHz frequency with a sectoral antenna as the multi-hop point-to-point backhaul network's frequency to avoid the risk of channel interference on the backhaul. On the other hand, 2.4GHz frequency with an omnidirectional antenna serves smartphone customers. On the test results, the network latency between multihop access point, has a maximum value of 19,894 ms. This result means that the latency obtained can be categorized as preferred VoIP services based on ITUT G.1010 in the local network. Then for the customer on the fourth hop, 3968 meters from the VSAT terminal, the UDP data rate of 1.04Mbps was stable, and the TCP data rate decreased to 1.26Mbps. This paper emphasizes the use of multihop 5Ghz WLAN 802.11n as a backhaul to expand internet access coverage from VSAT in rural areas, where the concentration of customers was far apart and there were many buffalo horn barriers in traditional homes and buildings.

Beyond 4 × 100 Gbps Optical Backhaul Network With DSP Assistance Based Nonlinear Impairments Mitigation

AbstractBackhaul networking is the highlighted objective of today telecommunication structure. Additionally, the backhaul networking can be possible easily utilizing optical fiber networks (OFNs). This paper studies 4 × 100 Gbps framework of long haul capacity wavelength division multiplexing (WDM) system, taking into account the impairments of nonlinearities, amplified spontaneous emission (ASE) fiber dispersion. Digital signal processing based receiver is proposed to maintain performance of OFNs in presence of nonlinear issues. The complete procedure of proposed WDM based OFNs is verified theoretically. The simulation analysis proved the validation of presented model against nonlinear impairments and provides 2.1 bit error rate (BER) at 25 and 50 GHz channel spacing, 90 μm2 effective area and 500 km transmission length.

Comparative Analysis of Microwave Link Using Space and Hybrid Diversity Configuration on Mountain Topography Area

The development of information and communication technology (ICT) in Indonesia is increasing rapidly every year. However, this increase is not comparable to the distribution of technology in remote areas, especially areas with mountainous contours. So it takes a proper backhaul network design to deploy telecommunication services in remote areas. Microwave transmission technology is widely used as a backhaul network in mountainous areas because it can reach areas that are difficult to reach by fiber optic. However, multipath fading becomes a problem in microwave communication, so to solve it, we use the diversity configuration approach. Space diversity configuration is the system most often used, but in more extreme conditions it can use a hybrid diversity configuration which is a combination of space and frequency diversity. In this study, we designed and compared the performance of two types of diversity configurations, namely space and hybrid diversity in cross-mountainous areas using simulation software Pathloss 5.0. Before comparison, these paths were tested with a point-to-point configuration to assess microwave communication performance without diversity. Based on the simulation, the resulting cross-mountain microwave communication performance using point-to-point configuration results in 99.98179% availability and 5742.79 seconds unavailability in one year, these values are still far from the ITU-T G.821 standard, namely 99.99% availability. In the configuration using Space Diversity, the quality has increased, but it cannot meet ITU standards because it is only capable of producing 99.98333% to 99.98943% availability or comparable to un-availability for 5255.53 to 3332.48 seconds/year. Meanwhile, the hybrid diversity configuration can produce a performance that meets ITU standards with an availability of 99.99122% or equivalent to un-availability for 2769.79 seconds per year.

Light-Trail Design for 5G Backhaul: Architecture, SDN Impact and Coordinated Multipoint

5G promises to be revolutionary from the perspective of offering unprecedented bandwidth to the end user. In this pursuit, the limited spectrum of the wireless overlay, further constricted by distance, requires strong support from a backhaul network. Such a strong backhaul network should provide large bandwidth pipes with near proximity to the end user at low costs and using pragmatic technology. Naturally, an optical solution is best suited to meet the voluminous bandwidth requirements of the backhaul. This optical solution has to cater to dynamic bandwidth needs among base stations and provide rapid and smart provisioning to meet the requirement of new features such as Coordinated Multipoint (CoMP) among base stations, and yet be low cost. To this end, we propose the use of light-trails (LTs), which are a generalization of a lightpath that provides for dynamic bandwidth communication, sub-wavelength optical grooming and optical layer multicasting using contemporary optics. We observe that each feature of a LT, i.e., dynamic provisioning, optical multicast, and sub-wavelength grooming is strongly desired by the 5G backhaul, implying a clear mapping between them. We investigate the usage of light-trails as a 5G backhaul solution. We discuss the proposed architecture of light-trails for micro cells, pico cells, and femto cells. We present the LT design problem for 5G backhaul as a constrained optimization problem. We also present a mechanism to achieve coordinated multipoint using light-trails. A dynamic virtual topology growth algorithm for the backhaul is also presented and extensively evaluated. The light-trails approach is compared to other approaches, the use of an SDN controller is discussed and significant performance benefits are observed.

Time Sensitive Networking for 5G NR Fronthauls and Massive Iot Traffic

Integration of public fifth generation mobile network (5G) backhaul and non-public networks is key for the private/local 5G network ecosystem. However, such shared networks, namely, x-haul, must satisfy the extremely diverse traffic demands including low latency and massive number of internet of things (IoT) devices. We propose an x-haul platform with autonomous time aware shaper and adaptive mobile fronthaul compression, which simultaneously accommodates two 5G NR-class fronthauls (2*29.5 Gbps CPRI-equivalent rate) and backhaul traffic with 1,000 IoT devices. From an experiment we conducted to evaluate the proposed platform, mobile fronthaul traffic was transferred with 76-μs deterministic latency via 4 switches and 10-km optical fiber by autonomous time aware shaper while improving the achievable transmission rate of IoT traffic owing to the integration of adaptive compression.

Blockage tolerance in roadside millimeter-wave backhaul networks

With the proliferation of mobile devices with bandwidth-hungry applications, mmWave communication is considered a key enabling technology for 5G and beyond cellular networks. One very promising use of mmWave communication is in wireless backhaul, which has also been investigated by 3GPP as part of an integrated access and backhaul study. Unfortunately, the network performance is hard to predict due to the sensitivity of mmWave signals to blockages, which can result in frequent communication outages. In this paper, we consider wireless backhaul links deployed along the side of a road, which have been widely proposed both in urban environments and on highways. We first investigate the inherent robustness of an interference-free topology for roadside mmWave backhaul. Based on a novel four-type blockage model, we apply stochastic geometry to derive blockage probabilities as a function of the topology parameters and obstacle density, which yields insights that lead to a more robust topology. We then present mechanisms to tolerate any blockages that do occur through reconfiguration. Through extensive simulations, the performance of our proposed algorithms are evaluated for different road scenarios and network topologies. Results show that our algorithms not only achieve high throughputs close to the no-blockage case for mmWave backhaul, but also provide high blockage tolerance rates even in the presence of multiple obstacles along the road.

Evaluation of flying caching servers in UAV-BS based realistic environment

The dramatic growth of data traffic during the past decade has challenged wireless networks to provide new mechanisms to support such demand. Fast deployable wireless networks supported by Unmanned Aerial Vehicles (UAV) are a promising solution, especially to support in crowded scenarios with high peaks of traffic. Nevertheless, mounting a Base Station (BS) on UAVs (UAV-BSs) raises several challenges like the saturation of the backhaul (BH) link, needed for the communication between them and the Core Network (CN). In this work, this issue is addressed with the usage of the Multi-Access Edge Computing (MEC) technology, consisting on the placement of servers, providing computing platforms and storage, directly at the edge of these networks, e.g. on the UAV-BSs. In particular, we consider a portion of a Radio Access Network (RAN) composed by UAV-BSs, equipped with servers that provide the caching capability. The performance is evaluated, using realistic traffic demand, for different traffic characteristics, capacity of the cache server and users' density. Simulation results reveal that the usage of the MEC caching prevents the BH network saturation, since in case a requested content is locally cached, the BH network is not used. As consequences, the user coverage and the access capacity increase up to 33% and 70%, respectively and the experienced delay drops by 30%.

Designing a multi-layer edge-computing platform for energy-efficient and delay-aware offloading in vehicular networks

Vehicular networks are expected to support many time-critical services requiring huge amounts of computation resources with very low delay. However, such requirements may not be fully met by vehicle on-board devices due to their limited processing and storage capabilities. The solution provided by 5G is the application of the Multi-Access Edge Computing (MEC) paradigm, which represents a low-latency alternative to remote clouds. Accordingly, we envision a multi-layer job-offloading scheme based on three levels, i.e., the Vehicular Domain, the MEC Domain and Backhaul Network Domain. In such a view, jobs can be offloaded from the Vehicular Domain to the MEC Domain, and even further offloaded between MEC Servers for load balancing purposes. We also propose a framework based on a Markov Decision Process (MDP) to model the interactions among stakeholders working at the three different layers. Such a MDP model allows a Reinforcement Learning (RL) algorithm to take optimal decisions on both the number of jobs to offload between MEC Servers, and on the amount of computing power to allocate to each job. An extensive numerical analysis is presented to demonstrate the effectiveness of our algorithm in comparison with static policies not applying RL.

Polarization-transparent silicon photonic add-drop multiplexer with wideband hitless tuneability

Flexible optical networks require reconfigurable devices with operation on a wavelength range of several tens of nanometers, hitless tuneability (i.e. transparency to other channels during reconfiguration), and polarization independence. All these requirements have not been achieved yet in a single photonic integrated device and this is the reason why the potential of integrated photonics is still largely unexploited in the nodes of optical communication networks. Here we report on a fully-reconfigurable add-drop silicon photonic filter, which can be tuned well beyond the extended C-band (almost 100 nm) in a complete hitless (>35 dB channel isolation) and polarization transparent (1.2 dB polarization dependent loss) way. This achievement is the result of blended strategies applied to the design, calibration, tuning and control of the device. Transmission quality assessment on dual polarization 100 Gbit/s (QPSK) and 200 Gbit/s (16-QAM) signals demonstrates the suitability for dynamic bandwidth allocation in core networks, backhaul networks, intra- and inter-datacenter interconnects.

Extending P4 in-band telemetry to user equipment for latency- and localization-aware autonomous networking with AI forecasting

In beyond-5G networks, detailed end-to-end monitoring of specific application traffic will be required along with the access-backhaul-cloud continuum to enable low latency service due to local edge steering. Current monitoring solutions are confined to specific network segments. In-band network telemetry (INT) technologies for software defined network (SDN) programmable data planes based on the P4 language are effective in the backhaul network segment, although limited to inter-switch latency; therefore, link latencies including wireless and optical segments are excluded from INT monitoring. Moreover, information such as user equipment (UE) geolocation would allow detailed mobility monitoring and improved cloud-edge steering policies. However, the synchronization between latency and location information, typically provided by different platforms, is hard to achieve with current monitoring systems. In this paper, P4-based INT is proposed to be thoroughly extended involving UE. The INT mechanism is designed to provide synchronized and accurate end-to-end latency and geolocation information, enabling decentralized steering policies, i.e., involving UE and selected switches, without SDN controller intervention. The proposal also includes an artificial-intelligence-assisted forecast system able to predict latency and geolocation in advance and trigger faster edge steering.