In industrial environments, over several decades, Automated Guided Vehicles (AGVs) and Autonomous Mobile Robots (AMRs) have served to improve efficiencies of intralogistics and material handling tasks. However, for system integrators, the choice and effective deployment of improved, suitable and reliable communication and control technologies for these unmanned vehicles remains a very challenging task. Specifics of communication for AGVs and AMRs imposes stringent performance requirements on latency and reliability of communication links which many existing wireless technologies struggle to satisfy. In this paper, a review of latest AGVs and AMRs research results in the past decade is presented. The review encompasses results from different past and present research domains of AGVs. In addition, performance requirements of communication networks in terms of their latencies and reliabilities when they are deployed for AGVs and AMRs coordination, control and fleet management in smart manufacturing environments are discussed. Integration challenges and limitations of present state-of-the-art AGV and AMR technologies when those technologies are used for facilitating AGV-based smart manufacturing and factory of the future applications are also thoroughly discussed. The paper also present a thorough discussion of areas in need of further research regarding the application of 5G networks for AGVs and AMRs fleet management in smart manufacturing environments. In addition, novel integration ideas by which tactile Internet, 5G network slicing and virtual reality applications can be used to facilitate AGV and AMR based factory of the future (FoF) and smart manufacturing applications were motivated.

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A Review of Recent Advances in Automated Guided Vehicle Technologies: Integration Challenges and Research Areas for 5G-Based Smart Manufacturing Applications

Densification of network base stations is indispensable to achieve the stringent Quality of Service (QoS) requirements of future mobile networks. However, with a dense deployment of transmitters, interference management becomes an arduous task. To solve this issue, exploring radically new network architectures with intelligent coordination and cooperation capabilities is crucial. This survey paper investigates the emerging user-centric cell-free massive multiple-input multiple-output (MIMO) network architecture that sets a foundation for future mobile networks. Such networks use a dense deployment of distributed units (DUs) to serve users; the crucial difference from the traditional cellular paradigm is that a specific serving cluster of DUs is defined for each user. This framework provides macro diversity, power efficiency, interference management, and robust connectivity. Most importantly, the user-centric approach eliminates cell edges, thus contributing to uniform coverage and performance for users across the network area. We present here a guide to the key challenges facing the deployment of this network scheme and contemplate the solutions being proposed for the main bottlenecks facing cell-free communications. Specifically, we survey the literature targeting the fronthaul, then we scan the details of the channel estimation required, resource allocation, delay, and scalability issues. Furthermore, we highlight some technologies that can provide a management platform for this scheme such as distributed software-defined network (SDN) and self-organizing network (SON). Our article serves as a check point that delineates the current status and indicates future directions for this area in a comprehensive manner.

User-centric Cell-free Massive MIMO Networks: A Survey of Opportunities, Challenges and Solutions.

Densification of network base stations is indispensable to achieve the stringent Quality of Service (QoS) requirements of future mobile networks. However, with a dense deployment of transmitters, interference management becomes an arduous task. To solve this issue, exploring radically new network architectures with intelligent coordination and cooperation capabilities is crucial. This survey paper investigates the emerging user-centric cell-free massive Multiple-input multiple-output (MIMO) network architecture that sets a foundation for future mobile networks. Such networks use a dense deployment of distributed units (DUs) to serve users; the crucial difference from the traditional cellular paradigm is that a specific serving cluster of DUs is defined for each user. This framework provides macro diversity, power efficiency, interference management, and robust connectivity. Most importantly, the user-centric approach eliminates cell edges, thus contributing to uniform coverage and performance for users across the network area. We present here a guide to the key challenges facing the deployment of this network scheme and contemplate the solutions being proposed for the main bottlenecks facing cell-free communications. Specifically, we survey the literature targeting the fronthaul, then we scan the details of the channel estimation required, resource allocation, delay, and scalability issues. Furthermore, we highlight some technologies that can provide a management platform for this scheme such as distributed software-defined network (SDN). Our article serves as a check point that delineates the current status and indicates future directions for this area in a comprehensive manner. 

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User-Centric Cell-Free Massive MIMO Networks: A Survey of Opportunities, Challenges and Solutions

Towards a fully connected intelligent digital world, 5G and beyond networks experience a new era of Internet of intelligence with connected people and things. This new era brings challenging demands to the network, such as high spectral efficiency, low-latency, high-reliable communication, and high energy efficiency. One of the major technological breakthroughs to cope with these unprecedented demands is the cell-free (CF) massive multiple-input multiple-output (mMIMO) systems. In CF mMIMO, a large number of distributed access points are connected to a central processing unit, and serve a smaller number of users over the same time-frequency resources. The system has shown a great potential in improving the network performance in various perspectives compared to the co-located mMIMO and conventional small-cell systems. Furthermore, the system can be flexibly integrated with various emerging techniques/technologies for 5G and beyond networks to boost the network performance in different perspectives. Despite the substantial reported theoretical gains of CF mMIMO systems, the full picture of a practical scalable deployment of the system is not clear yet. In this paper, we provide a comprehensive survey of different aspects of the CF mMIMO system from the general system model, the detailed system operation, the limitations towards a practically implemented system to the potential of integrating the system with emerging techniques/technologies. Besides, we provide a number of timely open problems and future research directions to fully exploit the CF mMIMO system potential in delivering the anticipated requirements of future wireless networks. 

Cell-Free Massive MIMO: A Survey

Mobile edge computing (MEC) is emerging to support delay-sensitive 5G applications at the edge of mobile networks When a user moves erratically among multiple MEC nodes, the challenge of how to dynamically migrate its service to maintain service performance (ie, user-perceived latency) arises However, frequent service migration can significantly increase operational cost, incurring the conflict between improving performance and reducing cost To address these mis-aligned objectives, this paper studies the performance optimization of mobile edge service placement under the constraint of long-term cost budget It is challenging because the budget involves the future uncertain information (eg, user mobility) To overcome this difficulty, we devote to leveraging the power of prediction and advocate predictive service placement with predicted near-future information By using two-timescale Lyapunov optimization method, we propose a $T$ -slot predictive service placement ( PSP ) algorithm to incorporate the prediction of user mobility based on a frame-based design We characterize the performance bounds of PSP in terms of cost-delay trade-off theoretically Furthermore, we propose a new weight adjustment scheme for the queue in each frame named PSP-WU to exploit the historical queue information, which greatly reduces the length of queue while improving the quality of user-perceived latency Rigorous theoretical analysis and extensive evaluations using realistic data traces demonstrate the superior performance of the proposed predictive schemes

Leveraging the Power of Prediction: Predictive Service Placement for Latency-Sensitive Mobile Edge Computing

Cell-free massive multiple-input multiple-output (MIMO) is a novel beyond 5G (B5G) and 6G paradigm that, through the use of a common central processing unit (CPU), coordinates a large number of distributed access points (APs) to coherently serve mobile stations (MSs) on the same time/frequency resource. By exploiting the characteristics of new less-congested millimeter wave (mmWave) frequency bands, these networks can improve the overall system spectral and energy efficiencies by using low-complexity hybrid precoders/decoders. For this purpose, the system must be correctly dimensioned to provide the required quality of service (QoS) to MSs under different traffic load conditions. However, only heavy traffic load conditions are usually taken into account when analysing these networks and, thus, many APs might be underutilized during low traffic load periods, leading to an inefficient use of resources and waste of energy. Aiming at the implementation of energy-efficient AP switch on/off strategies, several approaches have been proposed in the literature that only consider rather unrealistic uniform spatial traffic distribution in the whole coverage area. Unlike prior works, this paper proposes energy efficient AP sleep-mode techniques for cell-free mmWave massive MIMO networks that are able to capture the inhomogeneous nature of spatial traffic distribution in realistic wireless networks. The proposed framework considers, analyzes and compares different AP switch ON-OFF (ASO) strategies that, based on the use of goodness-of-fit (GoF) tests, are specifically designed to dynamically turn on/off APs to adapt to both the number and the statistical distribution of MSs in the network. Numerical results show that the use of properly designed GoF-based ASO strategies under a non-uniform spatial traffic distribution can serve to considerably improve the achievable energy efficiency.

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Energy-Efficient Access-Point Sleep-Mode Techniques for Cell-Free mmWave Massive MIMO Networks With Non-Uniform Spatial Traffic Density

Network slicing is a novel 5G paradigm that exploits the virtualization and softwarization of networks to create different logical network instances over a common network infrastructure. Each instance is tailored for specific Quality of Service (QoS) profiles so that network slicing can simultaneously support several services with diverse requirements. Network slicing can be applied at the Core Network or at the Radio Access Network (RAN). RAN slicing is particularly relevant to support latency-sensitive or time-critical applications since the RAN accounts for a significant part of the end-to-end transmission latency. In this context, this study proposes a novel latency-sensitive 5G RAN slicing solution. The proposal includes schemes to design slices and partition (or allocate) radio resources among slices. These schemes are designed with the objective to satisfy both the rate and latency demands of diverse applications. In particular, this study considers applications with deterministic aperiodic, deterministic periodic and non-deterministic traffic. The latency-sensitive 5G RAN slicing proposal is evaluated in Industry 4.0 scenarios where stringent and/or deterministic latency requirements are common. However, it can be evolved to support other verticals with latency-sensitive or time-critical applications.

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Latency-Sensitive 5G RAN Slicing for Industry 4.0

Two-tier networks combining an operator-managed infrastructure of macrocell base stations combined with a user-deployed network of femtocells have recently emerged in the context of modern wireless standards as a solution to meet the ambitious performance requirements envisaged in 4G/5G architectures. Most often, these systems require interference coordination schemes that allow near universal frequency reuse while maintaining a considerably high signal-to-interference-plus-noise ratio levels across the coverage area. In particular, fractional frequency reuse (FFR) and its variants are deemed to play a fundamental role in the next generation of cellular systems. This paper develops an analytical framework targeting the downlink performance evaluation of FFR-aided orthogonal frequency division multiple access-based two-tier heterogeneous networks. In the considered scenario, macrocell and femtocell tiers are assumed to be uncoordinated and co-channel deployed, thus representing a worst-case scenario in terms of inter-tier interference. The proposed framework allows the evaluation of the impact produced by both inter- and co-tier interferences on the performance of either the macro-users (MUs) or the femto-users. Analytical results are used to optimize the FFR parameters as a function of, for example, the density of MUs per cell, the resource block scheduling policy, the density of femto base stations per area unit, or the degree of isolation provided by wall penetration losses. Moreover, different optimization designs of the FFR component are proposed that allow a tradeoff between throughput performance and fairness by suitably dimensioning the FFR inner and outer areas and the corresponding frequency allocation.

Analysis and Optimization of FFR-Aided OFDMA-Based Heterogeneous Cellular Networks

Simultaneous wireless information and power transfer (SWIPT) has been advocated as a highly promising technology to provide near- perpetual operation to low-powered wireless devices in Internet-of-Things (IoT)-based wireless networks. In this paper, a SWIPT-enhanced cell-free massive MIMO network is proposed. In such a network, a large set of spatially distributed access points (APs) interconnected via a central processing unit (CPU) can collaboratively serve a large number of both energy harvesting mobile stations (MSs) (requiring wireless energy transfer) and conventional MSs (not requiring wireless energy transfer) on the same time-frequency resources. We consider spatially correlated Rician fading channels and the use of different precoding schemes that are based on different channel estimators differing on the assumed knowledge of the line-of-sight component. Mathematically manageable expressions are derived for the harvested energy during the downlink (DL) energy harvesting phase and the achievable spectral and energy efficiencies during the uplink (UL) payload transmission phase. A coupled UL/DL optimization problem is formulated aiming at finding the power control coefficients that maximize the minimum of the weighted achievable UL signal-to-interference-plus-noise ratios (SINRs) of all MSs. Extensive numerical results are presented that serve to highlight the existing trade-offs among the achievable spectral and energy efficiencies, the harvested energy, the energy dedicated to UL pilot transmission or the system configuration.

SWIPT-Enhanced Cell-Free Massive MIMO Networks

It is well known that per macro-site spectral efficiency (SE) can be increased through higher order sectorization (HOS) by radially partitioning the coverage area of each site into multiple sectors and reusing the spectral resources in each sector and across all sites. In order to further reinforce its benefits, HOS can be combined with fractional frequency reuse (FFR) techniques to improve the SE and/or energy efficiency (EE) of the network. This paper presents an analytical framework that is used to assess the sectorization performance in terms of both the SE and EE in the downlink of HOS/FFR-aided orthogonal frequency-division multiple access (OFDMA)-based macro-cellular networks. Tractable mathematical expressions are derived for the round robin, the proportional fair, and the maximum signal-to-interference-plus-noise ratio scheduling rules and the corresponding capacities. The results show the impact of the sectorization gain on the system performance for different cell-edge frequency reuse factor values. Furthermore, an optimization problem for the HOS/FFR-aided OFDMA-based network is addressed, allowing a tradeoff between the EE performance and fairness by suitably dimensioning the FFR inner and outer areas and the corresponding frequency allocation to each of these regions.

Jan Garcia-Morales

Papers

Energy-Efficient Access-Point Sleep-Mode Techniques for Cell-Free mmWave Massive MIMO Networks With Non-Uniform Spatial Traffic Density

Latency-Sensitive 5G RAN Slicing for Industry 4.0

Analysis and Optimization of FFR-Aided OFDMA-Based Heterogeneous Cellular Networks

SWIPT-Enhanced Cell-Free Massive MIMO Networks

Higher Order Sectorization in FFR-Aided OFDMA Cellular Networks: Spectral- and Energy-Efficiency