Mobile Radio Access Networks Research Articles

Delay-sensitive resource allocation for IoT systems in 5G O-RAN networks

The rapid advancement in sensors and communications has led to the expansion of the Internet of Things (IoT) services, where many devices need access to the transport network using fixed or wireless access technologies and mobile Radio Access Networks (RAN). However, supporting IoT in RAN is challenging as IoT services may produce many short and variable sessions, impacting the performance of mobile users sharing the same RAN. To address this issue, network slicing is a promising solution to support heterogeneous service segments sharing the same RAN, which is a crucial requirement of the upcoming fifth-generation (5G) mobile network. This paper proposes a two-level network slicing mechanism for enhanced mobile broadband (eMBB) and Ultra-Reliable and Low Latency communications (URLLC) in order to provide end-to-end slicing at the core and edge of the network with the aim of reducing latency for IoT services and mobile users sharing the same core and RAN using the O-RAN architecture. The problem is modeled at both levels as a Markov decision process (MDP) and solved using hierarchical reinforcement learning. At a high level, an SDN controller using an agent that has been trained by a Double Deep Q-network (DDQN) allocates radio resources to gNodeBs (next-generation NodeB, a 5G base station) based on the requirements of eMBB and URLLC services. At a low level, each gNodeB using an agent that has been trained by a DDQN allocates its pre-allocated resources to its end-users. The proposed approach has been demonstrated and validated through a real testbed. Notably, it surpasses the prevalent approaches in terms of end-to-end latency.

A user subscription model in mobile radio access networks with network slicing

Network slicing is an architectural enabling technology that logically decouples the current cellular networks into infrastructure providers (InPs) and Network Slice Tenants (NSTs). The network resources (e.g., radio access resources at each cell) are owned by the InP, and are shared by the NSTs to provide a service to their mobile users. In this context, we proposed a business model that includes resource allocation and user subscription to NSTs in a competitive setting, and provides, among other things, closed-form expressions for the subscription indicators in equilibrium of each NST at each cell. This model relies on the widely adopted logit model to characterize user subscriptions. However, as a consequence of user mobility and radio propagation, some of the underlying assumptions in the logit model do not hold. Therefore, further research is needed to assess the accuracy of the results provided by the logit model in a mobile radio scenario. We carry out a thorough evaluation of the validity of the model by comparing its results against those obtained through computer simulation. Our simulation model includes complete and realistic characterizations of user mobility and radio propagation. From the results, we conclude that in most cases the logit model provides valid results in a mobile radio scenario.

Joint computation offloading and resource allocation strategy for D2D-assisted and NOMA-empowered MEC systems

Multi-access edge computing (MEC) emerged as a promising network paradigm that provides computation, storage and networking features within the edge of the pervasive mobile radio access network. This paper jointly considers computation offloading and resource allocation problem in device-to-device (D2D)-assisted and non-orthogonal multiple access (NOMA)-empowered MEC systems, where each mobile device (MD) is allowed to execute its task in one of the three ways, i.e., local computing, MEC offloading or D2D offloading. We invoke orthogonal multiple access (OMA) and NOMA schemes for MDs that select D2D offloading mode, allowing them to assign tasks to their peers using OMA or NOMA. The original problem is formulated as an overall energy consumption minimization problem, which proves to be NP-hard, making it intractable to solve optimally. We start from a simple case, OMA case and transform the original problem into two sub-problems, i.e., resource allocation sub-problem and computation offloading sub-problem and propose two heuristic algorithms to obtain the sub-optimal solutions of both sub-problems. Then, for the MDs selecting D2D offloading mode, we conduct user pairing and apply the NOMA scheme. Finally, simulation results demonstrate the efficiency of the proposed scheme when compared with the related schemes.

Structure learning‐based unsupervised root cause diagnosis for radio access networks

The next generation radio access networks (RAN) put forward higher requirements for the reliability of base stations. Telecom operators are facing a series of challenges such as network complexity and diversified user needs, which puts forward higher requirements for the performance of RAN. In order to provide users with high-quality experience, causes of performance problems must be quickly identified. Previous work on unsupervised RAN performance diagnosis mainly used correlation information of the data. This work introduces causality into performance diagnosis of RAN. A score-based directed acyclic graph (DAG) structure learning network is used to extract causal relations between key performance indicators (KPIs). In this study, an unsupervised root cause analysis (RCA) scheme, DAG-RCA, is proposed to achieve rapid diagnosis of abnormal performance on the edge nodes of the RAN. DAG-RCA decomposes the work into four phases: abnormal ranking, DAG generation, propagation graph construction and random walk diagnosis. Using the KPI data collected from China Mobile's RAN, DAG-RCA achieves 83.75 % $83.75\%$ top-1 precision on the RCA task.

A User Subscription Model in Mobile Radio Access Networks with Network Slicing

A User Subscription Model in Mobile Radio Access Networks with Network Slicing

Open RAN—Radio Access Network Evolution, Benefits and Market Trends

Open RAN (radio access network) movement is perceived as a game changer, having robust potential to introduce shifts in mobile radio access networks towards tailor-made solutions based on the architecture decomposition. It is widely assumed that those changes will affect the approach to network deployments and supply chains of network elements and their further integration and maintenance. First deployments of O-RAN-based networks have already delivered broadband services to end users. In parallel, many proof-of-concept feature evaluations and theoretical studies are being conducted by academia and the industry. In this review, the authors describe the RAN evolution towards open models and make an attempt to indicate potential open RAN benefits and market trends.

3 × 3 MIMO Fiber–Wireless System in W-Band With WDM/PDM RoF Transmission Capability

We propose and demonstrate a 3 × 3 full multiple-input multiple-output (MIMO) fiber–wireless system in the W-band with wavelength-division multiplexing (WDM) and polarization-division multiplexing (PDM) radio-over-fiber (RoF) transmission capability. The system is realized using two highly stable RoF links based on the optical self-heterodyne method and PDM transmission in one of the RoF links. We experimentally demonstrate and confirm satisfactory performances for a 3 × 3 MIMO offset quadrature amplitude modulation-based filter-bank multicarrier signal. Total capacities of approximately 110 and 132 Gb/s, corresponding to spectral efficiencies of approximately 8.5 and 10.2 bits/s/Hz, respectively, are achieved for the system using antennas placed in the same and alternately different polarizations, respectively. The system is applicable to WDM and combined WDM/PDM RoF transmissions. It provides a scalable solution for facilitating large-scale MIMO signal transportation and can be a promising solution for future mobile transport and radio access networks in high-frequency bands.

Modeling multi-beam radio channel

In this work, a simulation model of a radio channel with fading is implemented for use 
 in research of the multipath channel, as well as for assessing the noise immunity of transmission, recep-tion and processing systems in modern and future mobile communication and radio access networks. Formalization of mathematical models of a radio channel with fading, including the Rayleigh amplitude distribution, uniform phase distribution and a given Doppler spectrum, made it possible to visualize 
 the time-frequency and probabilistic characteristics of a radio channel with fading. The implementation 
 of the procedures for delaying and attenuating copies of signals in a multipath radio channel made it pos-sible to reproduce scenarios of flat and frequency selective fading, which are widely used in practice in assessing the noise immunity of signals with given frequency and time characteristics.

An integrated satellite–terrestrial 5G network and its use to demonstrate 5G use cases

SummaryIn this paper, we present a satellite‐integrated 5G testbed that was produced for the EU‐commissioned Satellite and Terrestrial Networks for 5G (SaT5G) project. We first describe the testbed's 3GPP Rel. 15/6‐compliant mobile core and radio access network (RAN) that have been established at the University of Surrey. We then detail how satellite NTN UE and gateway components were integrated into the testbed using virtualization and software‐defined orchestration. The satellite element provides 5G backhaul, which in concert with the terrestrial/mobile segment of the testbed forms a fully integrated end‐to‐end (E2E) 5G network. This hybrid 5G network exercised and validated the four major use cases defined within the SaT5G project: cell backhaul, edge delivery of multimedia content, multicast and caching for media delivery and multilinking using satellite and terrestrial. In this document, we describe the MEC implementations developed to address each of the aforementioned use cases and explore how each MEC system integrates into the 5G network. We also provide measurements from trials of the use cases over a live GEO satellite system and indicate in each case the improvements that result from the use of satellite in the 5G network.

Analysis and Optimization of 5G Coverage Predictions Using a Beamforming Antenna Model and Real Drive Test Measurements

The ability to estimate radio coverage accurately is fundamental for planning and optimizing any wireless network, notably when a new generation, as the 5 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> Generation (5G), is in an early deployment phase. The knowledge acquired from radio planning of previous generations must be revisited, particularly the used path loss and antennas models, as the 5G propagation is intrinsically distinct. This paper analyses a new beamforming antenna model and distinct path loss models - 3 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rd</sup> Generation Partnership Project (3GPP) and Millimetre-Wave Based Mobile Radio Access Network for Fifth Generation Integrated Communications (mmMAGIC) - applying them to evaluate 5G coverage in 3-Dimensional (3D) synthetic and real scenarios, for outdoor and indoor environments. Further, real 5G Drive Tests (DTs) were used to evaluate the 3GPP path loss model accuracy in Urban Macro (UMa) scenarios. For the new antenna model, it is shown that the use of beamforming with multiple vertical beams is advantageous when the Base Station (BS) is placed below the surrounding buildings; in regular UMa surroundings, one vertical beam provides adequate indoor coverage and a maximized outdoor coverage after antenna tilt optimization. The 3GPP path loss model exhibited a Mean Absolute Error (MAE) of 21.05 dB for Line-of-Sight (LoS) and 14.48 dB for Non-Line-of-Sight (NLoS), compared with real measurements. After calibration, the MAE for LoS and NLoS decreased to 5.45 dB and 7.51 dB, respectively. Moreover, the non-calibrated 3GPP path loss model led to overestimations of the 5G coverage and user throughput up to 25% and 163%, respectively, when compared to the calibrated model predictions. The use of Machine Learning (ML) algorithms resulted in path loss MAEs within the range of 4.58 dB to 5.38 dB, for LoS, and within the range of 3.70 dB to 5.96 dB, for NLoS, with the Random Forest (RF) algorithm attaining the lowest error.

Combined time bound optimization of control, communication, and data processing for FSO‐based 6G UAV aerial networks

Because of the rapid increase of mobile traffic, flexible broadband supportive unmanned aerial vehicle (UAV)-based 6G mobile networks using free space optical (FSO) links have been recently proposed. Considering the advancements made in UAVs, big data processing, and artificial intelligence precision control technologies, the formation of an additional wireless network based on UAV aerial platforms to assist the existing fixed base stations of the mobile radio access network is considered a highly viable option in the near future. In this paper, a combined time bound optimization scheme is proposed that can adaptively satisfy the control and communication time constraints as well as the processing time constraints in FSO-based 6G UAV aerial networks. The proposed scheme controls the relation between the number of data flows, input data rate, number of worker nodes considering the time bounds, and the errors that occur during communication and data processing. The simulation results show that the proposed scheme is very effective in satisfying the time constraints for UAV control and radio access network services, even when errors in communication and data processing may occur.

Reliability and Mobility Load Balancing in Next Generation Self-organized Networks: Using Stochastic Learning Automata

Self-organizing networking (SON) is an automation technology designed to make the planning, configuration, management, optimization and healing of mobile radio access networks simpler and faster. Most current self-organization networking functions apply rule-based recommended systems to control network resources which seem too complicated and time-consuming to design in practical conditions. This research proposes a cognitive cellular network empowered by an efficient self-organization networking approach which enables SON functions to separately learn and find the best configuration setting. An effective learning approach is proposed for the functions of the cognitive cellular network, which exhibits how the framework is mapped to SON functions. One of the main functions applied in this framework is mobility load balancing. In this paper, a novel Stochastic Learning Automata has been suggested as the load balancing function in which approximately the same quality level is provided for each subscriber. This framework can also be effectively extended to cloud-based systems, where adaptive approaches are needed due to unpredictability of total accessible resources, considering cooperative nature of cloud environments. The results demonstrate that the function of mobility robustness optimization not only learns to optimize HO performance, but also it learns how to distribute excess load throughout the network. The experimental results demonstrate that the proposed scheme minimizes the number of unsatisfied subscribers (Nus) by moving some of the edge users served by overloaded cells towards one or more adjacent target cells. This solution can also guarantee a more balanced network using cell load sharing approach in addition to increase cell throughput outperform the current schemes.

Long Term Evolution -Self Organizing Network for Minimization of Sudden Call Termination in Mobile Radio Access Networks

Nowadays the mobile devices have become a more vital requisite and very crucial portion of our lives daily routine. The sudden call termination that happens unexpectedly (call drops) is a circumstance were the enduring calls get cut without any prior indication. The evolution of the services associated with the 3G and the 4G based on the voice and the data has ended up in high conflicts between the companies of the telecommunication to increase the consumer rate leading to major occurrence of the termination in the calls. Such abrupt un-notified call cessation still remains as an unanswered question in the telecommunication industry all over the world. Manifold measures and the researches put forth to devise the solution to the issue of un-notified call cessation for the mobile radio access networks were not successful as every methodology had its own advantages and as well as disadvantages. The laid out research made efforts to discover the reasons that for this un-notified sudden termination of calls, and examines the problem related with the termination of calls in each phase of the radio technology and puts forth the Self Organizing Network in the LTE for minimizing the factors that are related to the call termination and enhances the quality of the voice calls. Further brings down the expenses on the capital and the operations on terms of structural and the configuration attributes.

First 20 Years of Green Radios

Green radios jointly consider the spectrum efficiency and the energy efficiency in wireless networks in order to provide sustainable development. In the past two decades, various green radio solutions for different types of terminals and radio access networks have been developed, some of which have been used in the designs of wireless products. In this paper, we provide a historical view on some fundamental works and practical issues. In addition to providing a comprehensive overview on theoretical achievements, we also discuss several important power saving solutions with notable engineering impacts, such as Doherty power amplifier and separated baseband unit - remote radio unit architecture, which might be overlooked in previous publications. Moreover, with the huge growth of wireless traffic in the near future, green radio design for future wireless networks shall involve an end-to-end energy efficiency investigation of mobile terminals, radio access and core networks, and different applications. By introducing green radio schemes for advanced terminals and future wireless networks, this article will not only be beneficial for readers with only preliminary background in communications and signal processing but also have reference and historical values for researchers and practical engineers in the area.

Design and Optimization of a Renewable-Energy Fully-Hybrid Power Supply System in Mobile Radio Access Networks

The worldwide continuous growth of mobile subscriptions and broadband data demand is leading to an increase in hardware complexity of the base stations making up the mobile Radio Access Networks (RAN). This technological trend will inevitably result in increasing RAN energy consumption. In addition, the electrical grid accessibility issues encountered in developing countries bring a serious concern for telecom carriers who are constantly looking to reduce their networks operating expenditure (OPEX). Regular periodic maintenance and fuel consumption of on-site Diesel Generators are one of the main contributors to RAN OPEX. In this paper, an exhaustive yet compact model of a radio base station’s running cost is first introduced to provide telecom carriers a mathematical tool to estimate accurately their overall expenditure. Secondly, a generic Design & Optimization MATLAB tool is developed to minimize this cost by introducing, to the existing grid-generator solutions, renewable-energy (RE) sources to form a fully-hybrid power supply system (HPSS). CO2 emission is also integrated into the previous model to form a compound objective function for optimization. Finally, to achieve an optimal power supply system with both minimum annual OPEX and CO2 emissions, the core algorithm of this work computes the target duty-partition configuration among RE sources, on-site Diesel generators and utility grid. The software outputs in addition the required system design parameters for the RE sources to be installed on site.

Information Prediction and Dynamic Programming-Based RAN Slicing for Mobile Edge Computing

In 5G networks, mobile edge computing (MEC) and radio access network (RAN) slicing can support the evolving services and satisfy the diverse service requirements efficiently, thereby, being promising technologies. In this letter, the work is focused on the RAN slicing between MEC services and traditional services. An information prediction and dynamic programming based RAN slicing algorithm is proposed. It guarantees the inter-slice isolation and realizes the intra-slice customization. Furthermore, it can optimize the network utility with high fairness in polynomial time complexity.

Zadoff-Chu sequence-based upstream ranging in OFDMA-PON mobile radio access networks

Orthogonal frequency division multiple access (OFDMA) uplink in a passive optical network (PON) requires the delay alignment for OFDMA symbols from remotely distributed optical network units (ONUs). In this paper, we experimentally demonstrate and analyze the performance of a Zadoff-Chu (ZC) sequence-based upstream ranging scheme in an intensity modulation/direct detection (IM/DD)-based OFDMA-PON. The experimental results show that the proposed scheme can achieve upstream synchronization with only marginal inter-carrier interference (ICI) and requires no additional bandwidths in a typical OFDMA transmission with cyclic prefix (CP).

Advances in Next-Generation Networking Technologies for Smart Healthcare

The seven articles in this special section examine how 5G mobile communications will impact the smart healthcare industry. With the advancement of 5G communications, smart or "connected" healthcare is getting tremendous attention from academia, governments, industry, and the healthcare community. This will include, for example, 5G wireless networks, mobile edge computing (MEC), software-defined networking (SDN), and cloud radio access networks (C-RANs) can play a significant role in smart healthcare by offering better insight of heterogeneous healthcare media content to support aff ordable and high-quality patient care. While researchers have been making advances in the study of next-generation networking and healthcare services individually, very little attention has been given to make cost-effective and aff ordable smart healthcare solutions. Connected or smart healthcare has the potential to revolutionize many aspects of our society.

Green transmission for C-RAN based on SWIPT in 5G: a review

C-RAN is a promising new design for the next generation, an important aspect of it in the energy efficiency consideration. Hence, it is considering an innovative candidate to use it as an alternative cellular network instead of the traditional. Investigation green transmission of mobile cloud radio access networks based on SWIPT for 5G cellular networks. Especially, with considering SWIPT as a future solution for increasing the lifetime of end-user battery’s, that’s mean this technique will improving energy efficiency (EE). Addressing SWIPT into C-RAN is a challenging and it is needed to developing a new algorithm to use it on the cellular network with many trying to ensure the success of the system performance. C-RAN as a network and SWIPT as a promising technique with the suggesting green wireless network are discussed besides the importance of energy efficiency for the next generation. Furthermore, there was a study on fifth enabling technologies that can be used for 5G with emphasis on two of them (C-RAN and energy efficiency). Lastly, research challenges and future direction that require substantial research efforts are summarized.

Amping Up, Saving Power: Digital Predistortion Linearization Strategies for Power Amplifiers Under Wideband 4G\/5G Burst-Like Waveform Operation

Fourth-generation (4G) communication systems based on orthogonal frequency division multiplexing (OFDM) and the proposed backwards compatible fifth-generation (5G) variants, like filter-bank multicarrier (FBMC), are based on modulation techniques that allow significantly increased spectral efficiency and capacity in mobile radio access networks (RANs). However, the use of these modulation techniques impacts the requirements of the radio base stations, which have been traditionally the most energy-consuming element of mobile networks, accounting for up to 80% of the energy consumption of RANs [1]. Non-constant envelope-modulation techniques with high peak-to-average power ratios (PAPRs) require highly linear power amplifier (PA) amplitude and phase responses to fulfill stringent spectral mask and modulation accuracy requirements. This is often achieved with significant PA back-off, which considerably reduces PA efficiency because the PA's maximum efficiency is achieved near the saturation point.