Cellular Radio Access Networks Research Articles

Coverage and Data Rate Analysis for a Novel Cell-Sweeping-Based RAN Deployment

Adequate and uniform network coverage provision is one of the main objectives of cellular service providers. Additionally, the densification of cells exacerbates coverage and service provision challenges, particularly at the cell-edges. In this paper, we present a new approach of cell-sweeping-based Base Stations (BSs) deployments in cellular Radio Access Networks (RANs) where the coverage is improved by enhancing the cell-edge performance. In essence, the concept of cell-sweeping rotates/sweeps the sectors of a site in azimuth continuously/discretely resulting in near-uniform distribution of the signal-to-interference-plus-noise ratio (SINR) around the sweeping site. This paper investigates the proposed concept analytically by deriving expressions for the PDF/CDF of SINR and achievable rate; and with the help of system-level simulations, it shows that the proposed concept can provide throughput gains of up to 125% at the cell-edge. Then, using a link-budget analysis, it is shown that the maximum allowable path loss (MAPL) increases by 2.1 dB to 4.1 dB corresponding to the gains in wideband SINR and post-equalized SINR, respectively. This increase in MAPL can be translated to cell-radius/area with the help of the Okumura-Hata propagation model and results in cell-coverage area enhancement by 30% to 66% in a Typical Urban cell deployment scenario.

Crowd‐sourced and incentive driven UAV system to assist with network slices

AbstractOwing to their flexibility, fast deployment, increasing affordability, and numerous application opportunities, unmanned aerial vehicles (UAVs) became an undisputed target of studies and research to discover and exploit the immense opportunities they provide. Moreover, network slicing is a critical enabler for 5G and beyond. Network slices guarantee certain network user expectations such as data rate and latency thresh‐holds. There is no doubt that crowd‐sourced and incentive driven solutions are on the rise. Crowd‐sourcing allowed companies and organizations both small and large to gather data and perform other large‐scale tasks with minimum expenses and maintenance. Indeed, the major concerns for 5G and network slicing are guaranteeing high throughput, reliability, and latency. With data rates being the most important attribute for common regular users, that is, mobile devices, video streaming, navigation, and content consumption. As a result, the focus of this work is to utilize crowd‐sourced UAVs in an incentive driven network slice assistance system to extend coverage and provide mobile users with the high throughput they require. This work presents some basic 5G cellular radio access technologies and network slicing background and proposes a novel system, namely UAV slice assistance (UAVSA), and its hybrid alternative version: UAV hybrid slice assistance (UAVHSA). The hybrid mode combines benefits from the proposed UAVSA system and the traditional base station (BS) system. The proposed algorithms address the issue of coverage and guaranteeing high data rate slices for users. The proposed systems maximize satisfaction rate of network slice users. Moreover, all systems are extensively tested and compared in various scenarios to determine their performance and provide a coherent study. Finally, future works and opportunities are highlighted in conclusion.

Optimization of Channel Segregation-Based Fractional Frequency Reuse for Inter-Cell Interference Coordination in Cellular Ultra-Dense RAN

To cope with ever growing mobile data traffic, we recently proposed a concept of cellular ultra-dense radio access network (RAN). In the cellular ultra-dense RAN, a number of distributed antennas are deployed in the base station (BS) coverage area (cell) and user-clusters are formed to perform small-scale distributed multiuser multi-input multi-output (MU-MIMO) transmission and reception in each user-cluster in parallel using the same frequency resource. We also proposed a decentralized interference coordination (IC) framework to effectively mitigate both intra-cell and inter-cell interferences caused in the cellular ultra-dense RAN. The inter-cell IC adopted in this framework is the fractional frequency reuse (FFR), realized by applying the channel segregation (CS) algorithm, and is called CS-FFR in this paper. CS-FFR divides the available bandwidth into several sub-bands and allocates multiple sub-bands to different cells. In this paper, focusing on the optimization of the CS-FFR, we find by computer simulation the optimum bandwidth division number and the sub-band allocation ratio to maximize the link capacity. We also discuss the convergence speed of CS-FFR in a cellular ultra-dense RAN.

NOMA-Enabled Cellular Radio Access Networks Relying on Control- and User-Plane Separation

In a cellular radio access network relying on control- and user-plane separation (RAN-CUPS), control base stations (CBSs) make up the control plane (CP) taking charge of coverage, and traffic base stations (TBSs) in the user plane (UP) are responsible for transmitting high-speed data under the umbrella of CP. In order to increase the coverage probability of CP, non-orthogonal multiple access (NOMA) is introduced into CP while UP adopts orthogonal frequency division multiple access (OFDMA). Then, we develop a tractable analytical model for NOMA-enabled RAN-CUPS based on stochastic geometry. Simulation results show that compared with OFDMA, NOMA could improve coverage probability, spectral efficiency, and energy efficiency of CP, which can further improve the spectral efficiency of UP.

Hyperbolic K-means for traffic-aware clustering in cloud and virtualized RANs

As the internet and connected objects gain more and more in popularity, serving the ever-increasing data traffic becomes a challenge for the mobile operators. The traditional cellular radio access network (RAN), where each base station is co-located with its own processing unit and is responsible for a specific geographic area, has evolved first with the so-called Cloud RAN (C-RAN), and is currently undergoing further architectural evolution under the virtualized RAN (vRAN), Software-Defined RAN (SD-RAN), and Open RAN (O-RAN) architectures. In all these versions, the data processing units can be dynamically centralized into a pool and shared between several base stations, enlarging the geographical view for scheduling and resource allocation algorithms. For instance, resource utilization is improved by avoiding resource idling during off-peak hours. C-RAN and vRAN gains depend strongly on the clustering scheme of radio units (RRHs and RUs). In this paper, we propose a novel radio clustering algorithm that takes into account both the traffic demand and the position of stations, by using the hyperbolic distance in 3-dimensions. We introduce a modified K-means clustering algorithm, called Hyperbolic K-means, and show that this generates geographically compact RU clusters with traffic charge equally shared among them. Application of our algorithm on real-world mobile data traffic, collected from the cities of Nantes and Lille in France, shows an increase in resource utilization by 25%, and a reduction in deployment cost by 15%, compared to the standard RAN. Furthermore, the performance of our Hyperbolic K-means algorithm is compared extensively against alternative C-RAN clustering proposals from the literature and is shown to outperform them, in resource utilization as well as in cost reduction.

Encrypted Traffic Classification Based on Unsupervised Learning in Cellular Radio Access Networks

Traffic classification will be a key aspect in the operation of future 5G cellular networks, where services of very different nature will coexist. Unfortunately, data encryption makes this task very difficult. To overcome this issue, flow-based schemes have been proposed based on payload-independent features extracted from the Internet Protocol (IP) traffic flow. However, such an approach relies on the use of expensive traffic probes in the core network. Alternatively, in this paper, an offline method for encrypted traffic classification in the radio interface is presented. The method divides connections per service class by analyzing only features in radio connection traces collected by base stations. For this purpose, it relies on unsupervised learning, namely agglomerative hierarchical clustering. Thus, it can be applied in the absence of labeled data (seldom available in operational cellular networks). Likewise, it can also identify new services launched in the network. Method assessment is performed over a real trace dataset taken from a live Long Term Evolution (LTE) network. Results show that traffic shares per application class estimated by the proposed method are similar to those provided by a vendor report.

Performance Analysis of Cellular Radio Access Networks Relying on Control- and User-Plane Separation

In a cellular radio access network relying on control- and user-plane separation, control base stations (CBSs) form the control plane (CP) and take care of control coverage as well as low-speed data delivery. In contrast, traffic base stations (TBSs) in the user plane (UP) are used for transmitting high-speed data. Based on queuing theory and stochastic geometry, we derive the coverage probability of the CP under non-line-of-sight (NLoS) transmissions, and derive the energy efficiency of the UP under coexisting line-of-sight and NLoS propagation modes. Numerical results show that when the traffic load is high, the coverage probability of the CP increases with the increasing CBSs' data rate or the density of CBSs. We also found that the maximum energy efficiency of the UP can be achieved by optimizing the TBS density while achieving a high area spectral efficiency.

NetSliC: Base Station Agnostic Framework for Network SliCing

In this paper, we propose the base station (BS) agnostic framework for network slicing, NetSliC, that creates network slices for the radio access network (RAN) based on the service requirements. The current cellular RAN is a heterogeneous complex architecture, comprising legacy distributed small cells, radio remote radio heads connected to a centralized base band unit, and future fifth generation NodeBs leveraging virtualization with different functional splits, serving distinct traffic profiles. Thus, NetSliC is a common language that manages and controls this heterogeneous infrastructure. We consider several criteria for creating network slices in this particularly interesting future scenario, which are applicable to all different types of access and transport interfaces of the distinct BSs. The goal of our work is to propose NetSliC, a framework that creates wireless slices in a cellular RAN independently of the type of the BS (i.e., BS agnostic) and on the same time achieves desirable service capability across the various traffic profiles.

Small-Cell Assisted Secure Traffic Offloading for Narrowband Internet of Thing (NB-IoT) Systems

As cellular networks are evolving toward the fifth generation/long-term evolution systems, cellular radio access networks are expected to provide high throughput and reliable connectivity for massive number of smart devices (SDs), which leads to the emerging narrowband Internet of Things (NB-IoT), a cellular-assisted low-power wide area IoT system. Driven by the potential critical missions, such as transportation safety and video surveillance that require high throughput and low-power consumption, we investigate the small-cell assisted traffic offloading for NB-IoT systems. Taking into account the offloading through small cells operating on unlicensed bands, we account for the secrecy-outage issue in which some malicious eavesdroppers might intentionally overhead the offloaded data delivered to small cells. We first formulate a joint traffic scheduling and power allocation problem to minimize the total power consumption of SDs, while satisfying both the traffic throughput requirement and secrecy-requirement. Despite the nonconvexity of the problem, we propose an efficient algorithm to compute the optimal offloading solution. With the per-SD’s optimal offloading solution, we further investigate a multi-SDs multi access-points (APs) scenario, in which different SDs select different APs for providing offloading service to minimize the overall offloading-cost for all SDs. Specifically, we formulate an optimal SD-AP pairing problem to find the optimal pairing between the SDs and APs. Numerical results have been provided to validate our proposed algorithm and show the performance gain of our proposed traffic offloading for the NB-IoT systems.

Time- Versus Size-Based CPRI in Ethernet Encapsulation for Next Generation Reconfigurable Fronthaul

The utilization of Ethernet in the cellular terrestrial cloud radio access network (C-RAN) fronthaul will potentially improve C-RAN reconfigurability and cost efficiency in terms of both capital and operational expenditures. Moreover, Common Public Radio Interface (CPRI) line bit rate dynamic reconfiguration may spare further capital expenditures by avoiding peak traffic capacity allocation. A possible solution for introducing Ethernet in the fronthaul is the encapsulation of CPRI in Ethernet. This solution is now part of the radio over Ethernet interface specified by the IEEE P1914 working group. However, it must be assured that fronthaul strict requirements on delay and jitter are still met. In this study, the combined impact of encapsulating CPRI in Ethernet and of the dynamic CPRI line bit rate reconfiguration on delay and jitter of the communication between radio equipment and a radio equipment controller is evaluated. The evaluation is both analytical and based on the presynthesis emulation of dynamic CPRI line bit rate reconfiguration. Both a size-based and a time-based encapsulation are considered. Results show that dynamic CPRI line bit rate reconfiguration can be achieved within about 1 ms. However, if a size-based encapsulation of CPRI in Ethernet is utilized, dynamic CPRI line bit rate reconfiguration might cause delay variations (i.e., jitter) up to few microseconds. Thus, to avoid jitter upon CPRI line bit rate reconfiguration, time-based encapsulation is preferable.

Energy-efficient inter-RAN cooperation for non-collocated cell sites with base station selection and user association policies

Conventional planning and optimization of cellular mobile networks for supporting the peak-time user demand leads to substantial wastage of electrical energy. Infrastructure sharing among geographically collocated networks is considered promising for energy efficient operation of future cellular systems. Therefore, this paper proposes a generalized energy-efficient cooperation framework for sharing BSs between two cellular radio-access networks (RANs) serving the same geographical area. Previous works have the constraint of cooperation only among the collocated BSs belonging to different RANs, while the proposed framework is free from such limitation. To the best of our knowledge, this paper is the first for developing cooperation mechanisms among the non-collated BSs. Independent Poisson point process is used for modeling the near realistic random locations of both BSs and user equipment (UEs). Under the proposed framework, BSs belonging to different RANs dynamically share each others traffic and thus allow some BSs to switch into low power sleep mode for saving energy. During this BS switching through traffic-sharing, connection continuity (no drop of the existing calls) is maintained throughout the network. A generalized optimization problem for maximizing energy savings is formulated. Due to the high complexity of the optimization problem, heuristically guided algorithms differing in BS selection and UE association policies are proposed. More specifically, two different BSs selection schemes and three separate UE association policies are integrated in the algorithms. Performance of the proposed inter-RAN cooperation framework is evaluated using extensive simulations demonstrating a substantial energy savings and gain in energy efficiency. Impact of different network parameters, such as BS selection and UE association policies, BS and UE densities, BS power profile and SINR requirements for connection continuity on the system performance is thoroughly investigated and analyzed.

Control-Data Separation Architecture for Cellular Radio Access Networks: A Survey and Outlook

Conventional cellular systems are designed to ensure ubiquitous coverage with an always present wireless channel irrespective of the spatial and temporal demand of service. This approach raises several problems due to the tight coupling between network and data access points, as well as the paradigm shift towards data-oriented services, heterogeneous deployments and network densification. A logical separation between control and data planes is seen as a promising solution that could overcome these issues, by providing data services under the umbrella of a coverage layer. This article presents a holistic survey of existing literature on the control-data separation architecture (CDSA) for cellular radio access networks. As a starting point, we discuss the fundamentals, concepts, and general structure of the CDSA. Then, we point out limitations of the conventional architecture in futuristic deployment scenarios. In addition, we present and critically discuss the work that has been done to investigate potential benefits of the CDSA, as well as its technical challenges and enabling technologies. Finally, an overview of standardisation proposals related to this research vision is provided.

User Cooperation for 5G Wireless Access Networks

Device-to-device (D2D) connectivity is one of the main enablers for future fifth generation (5G) radio access networks. In this paper, we introduce a new model for user cooperation in 5G radio access networks termed frequency-selective soft forwarding (SF). SF is based on soft-processing by a target user equipment (TUE) of selectively forwarded soft information data by a set of cooperating user equipments acting as mobile relays towards the TUE. SF exploits the inherent frequency selectivity and broadcast nature of the downlink radio access channel for the sake of enabling efficient user cooperation and seamless integration of D2D connectivity into cellular radio access networks. Several variants of SF are investigated, including centralized and distributed approaches, thus offering various tradeoffs of performance versus signaling overhead cost. We also propose a hybrid cooperation mode selection strategy which leverages the performance benefits of SF and the low-overhead cost of decode-and-forward (DF) relaying to enhance the performance of 5G radio access networks. Exhaustive simulation results using a state-of-the-art long-term evolution-compliant link-level simulator show that the proposed user cooperation strategies well outperform baseline cooperation schemes relying on conventional DF and approach the performance of optimal joint reception with significantly lower cost in terms of D2D resource utilization and signaling overhead.

Cellular-Based Real-Time Flow Repair for Broadcast Flows

Watching television on a portable device is possible on broadcast and cellular systems. With broadcast technologies, due to the absence of a feedback channel it is not possible to guarantee an error free reception at the receivers. With cellular technologies, the transmission is based on unicast and the same content is transmitted as many times as the number of people who are watching the same program in the cell. We propose to combine both technologies and consider the concept of repairing a broadcast data flow for dual-mode (cellular and broadcast) smartphones in real time in order to ensure a better quality of service. We propose to use the constrained application protocol (CoAP) and specify a real-time flow repair (RFR) service based on CoAP in the cellular networks. We describe the architecture to provide such a service. We analyze the load generated in the cellular radio access network due to the retransmission of the packets lost on the broadcast system and also develop a model for the evaluation of the residual errors in the RFR operations.

Characterizing Pervasive Vehicular Access to the Cellular RAN Infrastructure: An Urban Case Study

Managing user mobility is historically one of the most critical issues in cellular radio access networks (RANs). That task will become an even greater challenge due to cellular users on board vehicles and networked cars that autonomously access Internet-based services, whose number is expected to grow dramatically in the next few years. There is thus a need to characterize RAN access from/by vehicles in a similar way to what has been done for traditional pedestrian access. In this paper, we propose a study of the macroscopic and microscopic features of pervasive vehicular access in a case-study large-scale urban environment in the presence of realistic data sets of the road traffic and RAN deployment. We find that pervasive vehicular access is characterized by unique temporal and spatial variability in the urban region, such that it may require a dedicated RAN capacity planning: The presence of stable vehicular access load patterns and mobility flows can help to that end. Moreover, we identify the theoretical distributions that best fit key metrics for RAN planning, i.e., the vehicular users' interarrival and residence times at cells, and discuss how their parameters vary over time and space.

Software-defined networking in cellular radio access networks: potential and challenges

Software-defined networking has brought both performance and management benefits to wired networks. It is natural to wonder if SDN principles also apply and can deliver similar benefits to RANs. It is this question that we intend to address in this article. We first highlight that the core SDN principle of decoupling control and data planes already exists in RANs in the form of self-organizing networking solutions, which can optimize RAN performance at coarse timescales. In addition to control/data plane separation, we also elaborate how fine timescale optimizations such as coordinated multi-point transmission are made practical with the help of cloud RANs (C-RANS), which offer the notion of processing decoupled from transmission within the data plane. We finally discuss the potential and challenges related to a less explored application of SDN in the RAN, which is programming the fronthaul network in a C-RAN. We argue that this novel notion of software-defined fronthaul, SDF, has the power to orchestrate novel applications and thus should be a key area of focus in RAN optimization.

The prediction analysis of cellular radio access network traffic: From entropy theory to networking practice

Although the research on traffic prediction is an established field, most existing works have been carried out on traditional wired broadband networks and rarely shed light on cellular radio access networks (CRANs). However, with the explosively growing demand for radio access, there is an urgent need to design a traffic-aware energy-efficient network architecture. In order to realize such a design, it becomes increasingly important to model the traffic predictability theoretically and discuss the traffic-aware networking practice technically. In light of that perspective, we first exploit entropy theory to analyze the traffic predictability in CRANs and demonstrate the practical prediction performance with the state-of-the-art methods. We then propose a blueprint for a traffic-based software-defined cellular radio access network (SDCRAN) architecture and address the potential applications of predicted traffic knowledge into this envisioned architecture.

TACT: A Transfer Actor-Critic Learning Framework for Energy Saving in Cellular Radio Access Networks

Recent works have validated the possibility of improving energy efficiency in radio access networks (RANs), achieved by dynamically turning on/off some base stations (BSs). In this paper, we extend the research over BS switching operations, which should match up with traffic load variations. Instead of depending on the dynamic traffic loads which are still quite challenging to precisely forecast, we firstly formulate the traffic variations as a Markov decision process. Afterwards, in order to foresightedly minimize the energy consumption of RANs, we design a reinforcement learning framework based BS switching operation scheme. Furthermore, to avoid the underlying curse of dimensionality in reinforcement learning, a transfer actor-critic algorithm (TACT), which utilizes the transferred learning expertise in historical periods or neighboring regions, is proposed and provably converges. In the end, we evaluate our proposed scheme by extensive simulations under various practical configurations and show that the proposed TACT algorithm contributes to a performance jumpstart and demonstrates the feasibility of significant energy efficiency improvement at the expense of tolerable delay performance.

Generalizing and optimizing fractional frequency reuse in broadband cellular radio access networks

For broadband cellular access based on orthogonal frequency division multiple access (OFDMA), fractional frequency reuse (FFR) is one of the key concepts for mitigating inter-cell interference and optimizing cell-edge performance. In standard FFR, the number of OFDMA sub-bands and the reuse factor are fixed. Whereas this works well for an idealized cell pattern, it is neither directly applicable nor adequate for real-life networks with irregular cell layouts. In this article, we consider a generalized FFR (GFFR) scheme to allow for flexibility in the total number of sub-bands as well as the number of sub-bands in each cell-edge zone, to enable network-adaptive FFR. In addition, the GFFR scheme takes power assignment in consideration. We formalize the complexity of the optimization problem, and develop an optimization algorithm based on local search to maximize the cell-edge throughput. Numerical results using networks with realistic radio propagation conditions demonstrate the applicability of the GFFR scheme in performance engineering of OFDMA networks.

OpenRAN: a new architecture for mobile wireless internet radio access networks

Cellular telephony networks depend on an extensive wired network to provide access to the radio link. The wired network, called a radio access network, provides such functions as power control and, in CDMA networks, combination of soft handoff legs (also known as macrodiversity resolution) that require coordination between multiple radio base stations and multiple mobile terminals. Existing RAN architectures for cellular systems are based on a centralized radio network controller connected by point-to-point links with the radio base transceiver stations. The existing architecture is subject to a single point of failure if the RNC fails, and is difficult to expand because adding an RNC is expensive. Also, although a network operator may have multiple radio link protocols available, most RAN architectures treat each protocol separately and require a separate RAN control protocol for each. We describe a new architecture, the OpenRAN architecture, based on a distributed processing model with a routed IP network as the underlying transport fabric. OpenRAN was developed by the Mobile Wireless Internet Forum IP in the RAN working group. The OpenRAN architecture applies principles to the radio access network that have been successful in reducing cost and increasing reliability in data communications networks. The result is an architecture that can serve as the basis for an integrated next-generation cellular radio access network.