Wireless Backhaul Research Articles

Joint link-level and network-level reconfiguration for urban mmWave wireless backhaul networks

Due to the rapid densification of small cells in 5G and beyond cellular networks, deploying wired high-bandwidth connections to every small cell base station (BS) is difficult, particularly in older metropolitan areas where infrastructure for fiber deployment is lacking. For this reason, mmWave wireless backhaul has been proposed as a cost-effective and flexible alternative that has the potential to support the high data rates needed to accommodate backhaul traffic demands. To address the robustness of such networks, we investigate a novel relay-assisted backhaul architecture, where a number of small-cell BSs and relays are deployed, e.g. on the lampposts of urban streets. In this scenario, the interconnected logical links constitute a mesh network, which offers opportunities for both link-level and network-level reconfiguration to overcome blockages and/or node failures. We present two joint link-network level reconfiguration schemes for recovery after exceptional events. One prioritizes relay path (link-level) reconfiguration and uses alternate network-level paths only if necessary. The other splits traffic on both reconfigured logical links and backup network paths to improve throughput. Through simulation, the reconfiguration schemes are shown to not only provide near-optimal backhaul survivability but to also maintain high network throughput across a range of scenarios for urban mmWave backhaul networks. The schemes are also validated to significantly outperform existing purely link-level and purely network-level reconfiguration schemes.

Mobile relays for urban rail transportation systems

Assuring an uninterrupted high Quality of Service (QoS) of railway communications between on-board terminals and base stations creates challenges for the provider. This is partly explained by the inherent mobility and the high penetration loss of carriages. Deploying mobile relays in public transportation is possible with a 100%-compatible LTE/EPC architecture. This effectively ensures that the electromagnetic insulation is kept to a minimum as QoS on board can be dramatically affected and worsened within the railway vehicles. Yet all users’ traffic congregates via the radio backhaul link and needs to take into consideration the extra packet-overhead and signaling messages that as a general rule get transmitted via the fixed links. The paper’s aim is to analyze the performance of mobile relays in loaded conditions comparing this to the standard direct mode. We propose an analytical model to compute the signaling rate. We parametrize it with experiments done on a testbed with real radio transmissions and show that signaling has no major impact on performance. We then evaluate the QoS experienced by passengers by means of simulations for two representative services: Web browsing and voice communications. The packet loss ratio for voice communications is reduced at the expense of a slight end-to-end latency increase thanks to mobile relays. During the high load conditions there is a significant reduction in the load time of a Web page and the throughput is increased.

WITHDRAWN: A study on single frequency network on high speed train

Abstract This paper presents a comprehensive study on millimetre wave (mmWave)-based mobile hotspot network (MHN) system for high-speed train (HST) communications, including system design, field trial, channel modeling based on measurement campaign, simulation and validation. Firstly, the physical layer specification and single frequency network (SFN) which includes MHN enhanced design (MHN-E) and the overview of the MHN system is provided. Secondly, For MHN conventional (MHN-C) and MHN-E systems, the prototypes and the overall design is presented and the MHN-C prototype and demonstrations with the MHN-E prototype are analysed with the help of results of field trial which conducted at Seoul subway line 8.Thirdly, the paper presents a characteristics of a measurement campaign investigating channel which is based on rural HST environment. Lastly, the performance of the MHNE system is validated by the help of computer simulation. The simulation is done at the speed of 500 km/h under the QuaDRiGa channel model which is also known as the good method for validation of HST communication systems, since it is impractical by real testbeds now. The simulation results revealed that with a peak data rate which exceeding 5 Gbps at a speed of 500 km/h the MHN-E system can able to provide a broadband mobile wireless backhaul (MWB).

Caching Placement and Resource Allocation for Cache-Enabling UAV NOMA Networks

This article investigates the cache-enabling unmanned aerial vehicle (UAV) cellular networks with massive access capability supported by non-orthogonal multiple access (NOMA). The delivery of a large volume of multimedia contents for ground users is assisted by a mobile UAV base station, which caches some popular contents for wireless backhaul link traffic offloading. In cache-enabling UAV NOMA networks, the caching placement of content caching phase and radio resource allocation of content delivery phase are crucial for network performance. To cope with the dynamic UAV locations and content requests in practical scenarios, we formulate the long-term caching placement and resource allocation optimization problem for content delivery delay minimization as a Markov decision process (MDP). The UAV acts as an agent to take actions for caching placement and resource allocation, which includes the user scheduling of content requests and the power allocation of NOMA users. In order to tackle the MDP, we propose a Q-learning based caching placement and resource allocation algorithm, where the UAV learns and selects action with \emph{soft ${\varepsilon}$-greedy} strategy to search for the optimal match between actions and states. Since the action-state table size of Q-learning grows with the number of states in the dynamic networks, we propose a function approximation based algorithm with combination of stochastic gradient descent and deep neural networks, which is suitable for large-scale networks. Finally, the numerical results show that the proposed algorithms provide considerable performance compared to benchmark algorithms, and obtain a trade-off between network performance and calculation complexity.

Review of optical and wireless backhaul networks and emerging trends of next generation 5G and 6G technologies

AbstractMobile Backhauling provides an interface between radio controller and base stations, mostly realized with a physical medium such as optical fibers or microwave radio links. With the huge mobile traffic due to an increase in mobile subscribers as well as deployment of 4G and 5G cellular network technologies, better solutions for capacity and coverage should be provided in order to enhance spectral efficiency. For 4G cellular networks, mobile backhaul networks deal with capacity, availability, deployment cost, and long‐distance reaches. In addition, mobile backhaul networks based on the 5G network incurs additional challenges that include 1 ms or less ultralow latency time requirements and ultra‐dense nature of the network capabilities. Therefore, for 5G technologies, latency delay, QoS, packet efficiency, noise suppression, and mitigation techniques, efficient modulation schemes, and packet network timing synchronization are some aspects that are to be dealt with while designing efficient backhaul approaches (wired/wireless). Current backhaul systems typically use cost‐effective solutions (eg, ‐Wi‐Fi and WiMAX)‐based packet‐switched technologies, especially Ethernet/Internet technologies and high‐speed optical fiber links.

Utility-Based Wireless Routing Algorithm for Massive MIMO Heterogeneous Networks

With the development of 5G communication, massive multiple input multiple output (MIMO) technology is getting more and more attention. Massive MIMO uses a large amount of simultaneous transmitting and receiving antennas to reduce power consumption and raise the level of transmission quality. Meanwhile, the diversification of user equipment (UE) in the 5G environment also makes heterogeneous networks (HetNets) more prevalent. HetNets allow UE of different network standards to access small cells, while the base stations of small cells access a macro base station (BS) to form a multihop wireless heterogeneous backhaul network. However, how to effectively combine these two technologies by efficiently allocating the antennas of each BS during the route construction process of heterogeneous wireless backhaul networks is still an important issue that is yet to be solved. In this paper, we propose an algorithm called preallocated sequential routing (PSR). Based on the links’ channel conditions and the available antennas and location of BSs, it builds a wireless heterogeneous network backhaul topology and adjusts each link’s transmitting and receiving antennas to maximize total utility. Simulation results showed that the proposed algorithm significantly improved the overall utility and the utility of the outer area of heterogeneous networks.

Non-Orthogonal Wireless Backhaul Design for Cell-Free Massive MIMO: An Integrated Computation and Communication Approach

In cell-free massive multiple-input-multiple-output system with wireless backhaul, the distributed access points (APs) and the center processing unit (CPU) are connected via wireless links. Hence, the limited backhaul bandwidth becomes a critical challenge to uplink transmission. To save the bandwidth while maintaining high transmission accuracy, we propose to deploy non-orthogonal transmissions in backhaul link and jointly optimize the detection computation mappings at the APs and the CPU under the non-orthogonal backhaul. First, we formulate the joint design problem subject to backhaul bandwidth constraint aiming at a better end-to-end transmission accuracy. Then, the non-trivial problem is parameterized and solved with a novel model-driven deep neural network, where wireless backhaul is integrated as a neural computing layer by exploiting the reciprocity between non-orthogonal transmission and additive operation. Evaluations show that, the proposed integration method outperforms the conventional approaches by a margin in both backhaul bandwidth cost and the symbol error rate.

Optimizing mmWave Wireless Backhaul Scheduling

Millimeter wave (mmWave) communication not only provides ultra-high speed radio access but is also ideally suited for efficient and flexible wireless backhauling. Specifically for dense deployments, a mmWave macro base station (MBS) that serves a large number of mmWave micro base stations (μBSs) is much more cost effective than legacy cellular architectures which connect μBSs to the core network through fibers. In addition, μBSs can cooperate with each other by acting as relay nodes. The directional nature of mmWave communication allows for spatial reuse, even in the presence of interference, which can be exploited to optimize mmWave wireless backhaul performance. The optimization opportunistically prioritizes the use of good connections at the MBS and further leverages compact and concurrent transmissions between μBS. Relays and directional antennas speed up communication, but increase the complexity of the scheduling problem. In this work, we study the mmWave backhaul scheduling problem and derive an MILP formulation for it as well as upper and lower bounds. We prove that the problem is NP-hard and can be approximated, but only if interference is negligible. By means of numerical simulations, we compare theoretical results with heuristics in small system sizes. Results validate the analysis and demonstrate the high performance of our heuristics in realistic cellular settings.

Optimal and Approximation Algorithms for Joint Routing and Scheduling in Millimeter-Wave Cellular Networks

Millimeter-wave (mmWave) communication is a promising technology to cope with the exponential increase in 5G data traffic. Such networks typically require a very dense deployment of base stations. A subset of those, so-called macro base stations, feature high-bandwidth connection to the core network, while relay base stations are connected wirelessly. To reduce cost and increase flexibility, wireless backhauling is needed to connect both macro to relay as well as relay to relay base stations. The characteristics of mmWave communication mandates new paradigms for routing and scheduling. The paper investigates scheduling algorithms under different interference models. To showcase the scheduling methods, we study the maximum throughput fair scheduling problem. Yet the proposed algorithms can be easily extended to other problems. For a full-duplex network under the no interference model, we propose an efficient polynomial-time scheduling method, the {\em schedule-oriented optimization}. Further, we prove that the problem is NP-hard if we assume pairwise link interference model or half-duplex radios. Fractional weighted coloring based approximation algorithms are proposed for these NP-hard cases. Moreover, the approximation algorithm parallel data stream scheduling is proposed for the case of half-duplex network under the no interference model. It has better approximation ratio than the fractional weighted coloring based algorithms and even attains the optimal solution for the special case of uniform orthogonal backhaul networks.

Performance of Full-Duplex Wireless Back-Haul Link under Rain Effects Using E-Band 73 GHz and 83 GHz in Tropical Area

This paper presents rain attenuation effects on the performance of the full-duplex link in a tropical region based on one-year measurement data at 73.5- and 83.5-GHz E-band for distances of 1.8 km (longer links) and 300 m (shorter links). The measured rain attenuations were analyzed for four links, and the throughput degradation due to rain was investigated. The findings from this work showed that the rain attenuation for both frequencies (73.5 and 83.5 GHz) of E-band links are the same. The rain rates above 108 and 193 mm/h caused an outage for the longer and shorter links, respectively. The 73.5 and 83.5 GHz bands can support the full-duplex wireless back-haul link under rainy conditions with outage probability of 2.9×10−4 and 6×10−5 for the longer and shorter links, respectively. This work also finds that the heavy rain with rain rates above 80 mm/h for long link and 110 mm/h for short link causes about 94% and 0.90% degradation of maximum throughput. The application of these findings would help improve the architecture and service of full-duplex wireless E-band links that are established at other sites and in other tropical areas.

Backhaul-Aware Resource Allocation and Optimum Placement for UAV-Assisted Wireless Communication Network

Driven by its agile maneuverability and deployment, the unmanned aerial vehicle (UAV) becomes a potential enabler of the terrestrial networks. In this paper, we consider downlink communications in a UAV-assisted wireless communication network, where a multi-antenna UAV assists the ground base station (GBS) to forward signals to multiple user equipments (UEs). The UAV is associated with the GBS through in-band wireless backhaul, which shares the spectrum resource with the access links between UEs and the UAV. The optimization problem is formulated to maximize the downlink ergodic sum-rate by jointly optimizing UAV placement, spectrum resource allocation and transmit power matrix of the UAV. The deterministic equivalents of UE’s achievable rate and backhaul capacity are first derived by utilizing large-dimensional random matrix theory, in which, only the slowly varying large-scale channel state information is required. An approximation problem of the joint optimization problem is then introduced based on the deterministic equivalents. Finally, an algorithm is proposed to obtain the optimal solution of the approximate problem. Simulation results are provided to validate the accuracy of the deterministic equivalents, and the effectiveness of the proposed method.

Unified Performance Analysis of Hybrid FSO/RF System With Diversity Combining

Hybrid free space optical (FSO)/radio frequency (RF) systems have been proved to be reliable for high-data-rate wireless backhauls. In this article, we present a unified performance analysis of the hybrid FSO/RF transmission system which transmits identical data in both links and implements two popular diversity combining schemes, namely, selection combining (SC) and maximal ratio combining (MRC), in the receiver. Specially, for the FSO link, the Gamma-Gamma turbulence with pointing errors under heterodyne detection (HD) and intensity modulation/direction detection (IM/DD) is considered in our analysis while the general κ-μ shadowed fading which unifies popular RF fading models is employed for the analysis of the RF link. As a result, unified closed-form expressions of outage probabilities and average bit error rates for different modulation schemes are derived. A preliminary extension of the RF link to multi-input-multi-output (MIMO) transmission is also analyzed. Analytical and Monte Carlo simulation results are provided to characterize the performance of the hybrid FSO/RF link which is compared to the single FSO link and the single RF link. The agreement between the analytical and simulation results confirms the unification of various FSO channels and RF fading scenarios into a single closed-form expression.

Joint pairing and resource allocation for backhaul of small cells using NOMA

Small cells is a promising technique to improve the spectral efficiency or quality-of-service (QoS) of a cellular network as it reduces the distance between the user and the base station (MBS). It has been proposed for indoor as well as outdoor users. For the outdoor scenario, the backhaul (the link from a small cell to the core network) of the small cell has always been a challenging issue. Different schemes have been proposed in the literature such as optical fiber, satellite and wirelessly through MBS. Wireless backhaul through MBS has gained a lot of attention in the literature and different resource allocation with orthogonal resources strategies have been proposed for it as well. Apart from orthogonal techniques, non-orthogonal multiple access (NOMA) is a multi access technique with the basic principle of sharing the same bandwidth resource between multiple users with varying power levels. Successive interference cancellation (SIC) is implemented on the receiver side to decode the data. This overall increases the spectrally efficiency of the network and make NOMA a promising candidate to be deployed on the backhaul of the small cell network. In this paper, we investigate the problem of pairing of small cells and the allocation of resources. Small cells' load information plays vital role to solve this problem. An optimization problem with an objective of maximizing the spectral efficiency (SE) of the backhaul network is formulated. The joint problem is decomposed and solved using a load-based heuristic for the backhaul of small cells. Furthermore, our performance evaluation shows that the proposed heuristic is able to achieve nearly-same spectral efficiency as that of exhaustive search with much less complexity.

Placement optimization of caching UAV-assisted mobile relay maritime communication

Recently, due to the deployment flexibility of unmanned aerial vehicles (UAVs), UAV-assisted mobile relay communication system has been widely used in the maritime communication. However, the performance of UAV-assisted mobile relay communication system is limited by the capacity of wireless backhaul link between base station and UAV In this paper, we consider a caching UAV-assisted decode-and-forward relay communication system in a downlink maritime communication. For the general case with multiple users, the optimal placement of UAV is obtained by solving the average achievable rate maximization problem through the one-dimensional linear search. For a special case with single user, we derive a semi closed-form expression of the optimal placement of UAV. Simulation results confirm the accuracy of analytical results and show that the optimal placement of UAV and the average achievable rate significantly depend on the cache capacity at UAV We also show the difference between the performances of the air-to-ground model and the air-to-sea model.

Low-Resolution ADC Quantized Full-Duplex Massive MIMO-Enabled Wireless Backhaul in Heterogeneous Networks Over Rician Channels

This paper studies the spectral/energy efficiency (SE/EE) of a heterogeneous network with the backhaul enabled by low-resolution analog-to-digital converters (ADCs) quantized full-duplex massive multiple-input multiple-output (MIMO) over Rician channels. Backhaul communication is completed over two phases. During the first phase, the macro-cell (MC) base station (BS) deploys massive receive antennas and a few transmit antennas; the small-cell (SC) BSs employ large-scale receive antennas and a single transmit antenna. For the second phase, the roles of the transmit and receive antennas are switched. Due to the low-resolution ADCs, we account for quantization noise (QN). We characterize the joint impact of the number of antennas, self-interference, SC-to-SC interference, QN, and Rician $K$ -factor. For the first phase, the SE is enhanced with the massive receive antennas and the loss due to QN is limited. For the second phase, the desired signal and QN have the same order. Therefore, the SE saturates with the massive transmit antennas. As the Rician $K$ -factor increases, the SE converges. Power scaling laws are derived to demonstrate that the transmit power can be scaled down proportionally to the massive antennas. We investigate the EE/SE trade-offs. The envelope of the EE/SE region grows with increase in the Rician $K$ -factor.

Wireless Networks With Cache-Enabled and Backhaul-Limited Aerial Base Stations

Use of aerial base stations (ABSs) is a promising approach to enhance the agility and flexibility of future wireless networks. ABSs can improve the coverage and/or capacity of a network by moving supply towards demand. Deploying ABSs in a network presents several challenges such as finding an efficient 3D-placement of ABSs that takes network objectives into account. Another challenge is the limited wireless backhaul capacity of ABSs and consequently, potentially higher latency incurred. Content caching is proposed to alleviate the backhaul congestion and decrease the latency. We consider a limited backhaul capacity for ABSs due to varying position-dependent path loss values and define two groups of users (delay-tolerant and delay-sensitive) with different data rate requirements. We study the problem of jointly determining backhaul-aware 3D placement for ABSs, user-BS associations and corresponding bandwidth allocations while minimizing total downlink transmit power. Proposed iterative algorithm applies a decomposition method. First, the 3D locations of ABSs are found using semi-definite relaxation and coordinate descent methods, and then user-BS associations and bandwidth allocations are optimized. The simulation results demonstrate the effectiveness of the proposed algorithm and provide insights about the impact of traffic distribution and content caching on transmit power and backhaul usage of ABSs.

Mobile-aware and relay-assisted partial offloading scheme based on parked vehicles in B5G vehicular networks

Mobile edge computing (MEC) is an attractive solution for the contradiction between huge computation resources and limited processing capacity of vehicular terminals, especially for the emerging 5G and beyond 5G (B5G) vehicular networks. However, most of the existing studies focus either on data interactions among moving vehicles or communications between vehicles and road side units (RSUs), ignoring the unused resources of vehicles parked on the road. In this paper, we propose a mobile-aware vehicular edge computing (VEC) partial offloading scheme, which regard parked vehicles as static for data transmission. More precisely, the remote wireless backhaul transmission between several RSUs is replaced by static multi-hop relay transmission. In addition, for multi-vehicular tasks input, an edge caching scheme adopted to reduce communication cost of vehicles. An optimal problem that is solved by leveraging Lagrange duality. Simulation results show that the energy consumption is drastically decreased between vehicles-to-vehicles (V2V) and vehicles-to-infrastructure (V2I), and the computation overhead of vehicular communication system is reduced.

Stochastic Geometry Analysis of Wireless Backhaul Networks with Beamforming in Roadside Environments

Stochastic Geometry Analysis of Wireless Backhaul Networks with Beamforming in Roadside Environments

Resource allocation for energy efficient user association in user-centric ultra-dense networks integrating NOMA and beamforming

A coupling of wireless access via non-orthogonal multiple access and wireless backhaul via beamforming is a promising way for downlink user-centric ultra-dense networks (UDNs) to improve system performance. However, ultra-dense deployment of radio access points in macrocell and user-centric view of network design in UDNs raise important concerns about resource allocation and user association, among which notably is energy efficiency (EE) balance. To overcome this challenge, we develop a framework to investigate the resource allocation problem for energy efficient user association in such a scenario. The joint optimization framework aiming at the system EE maximization is formulated as a large-scale non-convex mixed-integer nonlinear programming problem, which is NP-hard to solve directly with lower complexity. Alternatively, taking advantages of sum-of-ratios decoupling and successive convex approximation methods, we transform the original problem into a series of convex optimization subproblems. Thenwe solve each subproblem through Lagrangian dual decomposition, and design an iterative algorithm in a distributed way that realizes the joint optimization of power allocation, sub-channel assignment, and user association simultaneously. Simulation results demonstrate the effectiveness and practicality of our proposed framework, which achieves the rapid convergence speed and ensures a beneficial improvement of system-wide EE.

Optimal frequency reuse scheme based on cuckoo search algorithm in Li‐Fi fifth‐generation bidirectional communication

Huge demand for bandwidth and capacity is exhibited by various wireless users and applications, for that purpose now the light-fidelity (Li-Fi)-based technologies are developing. In visible light communication, the hybrid networks based on Wi-Fi and Li-Fi has emerged recently. It is based on the concept of integrating small cell Li-Fi networks with large coverage radio frequency (RF) communication systems. For bidirectional data communication, the access links use shared bandwidth since the link of wireless backhaul invokes in the visible light spectrum. Due to the RF spectrum shortage, the bandwidth of Wi-Fi access point (AP) and the coverage of Li-Fi AP are limited in the outdoor environment. To tackle this issue, the authors propose a swarm intelligence-based improved cuckoo search into the frequency reuse of a hybrid Wi-Fi–Li-Fi network in the outdoor environment. The proposed approach employed bidirectional visible light propagation with non-orthogonal multiple access (NOMA) which is an effective approach towards fifth-generation wireless networks. The NOMA can help various users at the same time with the same frequency and multiple power levels. The system throughput and spectral efficiency are improved with dynamic frequency reuse scheme. The simulation results are compared with conventional techniques to show its effectiveness.