A New Downlink Admission Control Algorithm Based on the Virtual Observation Point

In the context of 5G systems, the emergence of various use cases with diverse requirements has attracted great attention to network slicing. In a single physical network, several instances of logical end-to-end networks, i.e. slices, will be instantiated to fulfill these requirements. To this end, slices should share the resources of the physical network, which consist of Core Network (CN) and Radio Access Network (RAN) resources. Herein, we focus on the Radio Resource Management (RRM) in the context of network slicing. To maximize the pooling gains, dynamic resource sharing is preferred over static sharing. However, dynamic resource sharing can lead to undesirable inter-slice influences, in particular, the contention on radio resources. In this article, we show that, although the radio resources are dynamically shared among the users of different slices, proper slice management can realize slice protection. This is achieved by adjusting the fraction of radio resources allocated to the different slices by the Packet Scheduler (PS) and by limiting the number of users admitted to the network via Admission Control (AC). We propose an iterative algorithm to optimize the parameters of PS and AC in order to ensure that the service level agreements are satisfied. Extensive system-level simulations have shown that a central entity that tunes these control parameters can greatly increase the network's performance.

Video is expected to be the dominant application by traffic volume over mobile networks in the near future. Mobile network operators are deploying video optimization techniques to enhance the user experience and network utilization for video delivery. Video optimization is typically “out-of-network” and includes techniques such as transcoding, transrating, time shifting and pacing that are implemented outside of mobile radio access and core networks. However, such techniques cannot easily exploit information about real time cell congestion and radio conditions for the video terminals because it is difficult to obtain such information from the radio access network. We propose a novel “in-network” video optimization technique, named Adaptive Guaranteed Bit Rate (AGBR), for HTTP-based Adaptive Streaming (HAS) video. This optimization technique is implemented at the base station and can thus exploit knowledge of the radio and congestion conditions. With only limited knowledge of the video stream properties or content, AGBR works by adjusting the throughput delivered to the different HAS clients that in turn adjust the video quality they request. The optimization algorithm maximizes aggregate quality across multiple video flows served by the base station without starving data clients, thereby improving the overall quality of experience. We demonstrate through extensive analytical modeling and simulations that AGBR can adapt to changing network conditions to support more video sessions at an acceptable quality than alternative algorithms, while enforcing fairness among all users competing for resources within a sector.

Multiple access methods in a wireless network allow multiple nodes to share a set of available channels for data transmission. The nodes can either compete or cooperate with each other to access the channel(s) so that either an individual or a group objective can be achieved. Game theory, which is a mathematical tool developed to understand the interaction among rational entities, can be applied to model and to analyze individual or group behaviour of nodes for multiple access in wireless networks. Game theory also enables us to model the selfish/malicious behaviour of nodes, and subsequently design the punishment or defense mechanisms for robust multiple access in wireless networks. In addition, game models can provide distributed solutions to the multiple access problems, which are based on solid theoretical foundations. In this survey, we provide a comprehensive review of the game models (e.g., noncooperative/cooperative, static/dynamic, and complete/incomplete information) developed for different multiple access schemes (i.e., contention-free and contention-based random channel access) in wireless networks. We consider time-division multiple access (TDMA), frequency-division multiple access (FDMA), and code-division multiple access (CDMA), ALOHA, and carrier sense multiple access (CSMA)-based wireless networks. In addition, game models for multiple access in dynamic spectrum access-based cognitive radio networks are reviewed. The major findings from the game models used for these different access schemes are highlighted. To this end, several of the key open research directions are outlined.

Virtual radio access networks (RANs) is the candidate solution for 5G access networks, the concept of virtualised radio resources completing the virtual RAN paradigm. This paper proposes a new analytical model for the management of virtual radio resources in full heterogeneous networks. The estimation of network capacity and data rate allocation are the model’s two main components. Based on the probability distribution of the signal-to-interference-plus-noise-ratio observed at the user terminal, the model leads to the probability distribution for the total network data rate. It considers different approaches for the estimation of the total network data rate, based on different channel qualities, i.e., optimistic, realistic and pessimistic. The second component uses the outcome of the first one in order to maximise the weighted data rate subject to the total network capacity, the SLAs (service level agreements) of Virtual Network Operators (VNOs), and fairness. The weights for services in the objective function of the resource allocation component enable the model to have prioritisation among services. The performance of the proposed model is evaluated in a practical heterogeneous access network. Results show an increase of 2.5 times in network capacity by implementing an access point at the centre of each cell of a cellular network. It is shown that the cellular network capacity itself can vary from 0.9 Gbps in the pessimistic approach up to 5.5 Gbps in the optimistic one. Finally, the isolation of service classes and VNOs by means of virtualisation of radio resources is clearly demonstrated.

IEEE 802.16/WiMAX-based broadband and mobile wireless access is expected to be a significant component in the next generation (e.g., beyond 3G, 4G) wireless systems. IEEE 802.16/WiMAX standard, which incorporates several advanced radio transmission technologies such as orthogonal-frequency division multiplexing (OFDM), adaptive modulation and coding, and adaptive forward error correction (FEC), is designed to provide broadband wireless capability using a well-defined quality-of-service (QoS) framework. Therefore, this is a promising technology for wireless services requiring high- rate transmission (in the range of tens of Mbps) and strict QoS requirements in both indoor and outdoor environments. This technology is currently of big interest to researchers and practitioners involved in the design, analysis, installation, and management of mobile broadband wireless access systems and networks. The objective of this tutorial is to provide a complete overview on the IEEE 802.16/WiMAX standard and the current state-of-the-art research on the design, analysis, and optimization of IEEE802.16/WiMAX-based networks. The key technical challenges related to protocol engineering in these networks are described. The aim is to provide a survey on the emerging IEEE 802.16/WiMAX technology rather than an in-depth study on a specific protocol engineering problem. An overview of the different evolutions of the IEEE 802.16/WiMAX standard broadband wireless access (BWA) is presented and the open research issues in protocol engineering (e.g., for radio resource management, mobility support, security) are identified. A comprehensive survey on radio resource management, traffic scheduling, admission control, mobility management, and security mechanisms for IEEE 802.16/WiMAX are provided. A comparative performance study among the third-generation (3G) and the IEEE 802.16-based systems is provided. Several applications (e.g., wireless telemedicine and e-health services), services and deployment scenarios are described and the necessary protocol design and engineering issues are outlined.

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.

Over the past decade, wireless communications has experienced tremendous growth, and this growth is likely to multiply in the near future. The proliferation of mobile users and an ever increasing demand for multimedia services has resulted in greater capacity requirements. Radio frequency spectrum is scarce and cannot meet this ever increasing demand and the required Quality of Service (QoS) will no longer be achieved if efficient Radio Resource Management (RRM) solutions are not found. Conventional Radio Access Networks (RAN) have standalone Base Stations (BS) with capacity preconfigured for peak loads. These RANs have high call blocking and dropping rates since BSs resources cannot be shared. Cloud based RANs (C-RAN) have been proposed as a cost and energy efficient way of meeting high capacity demand of future wireless access networks by consolidating BSs to the cloud. Instead of relying on rejection of new call requests due to limited BS resources, C-RAN takes benefit of the cloud elasticity, which allows dynamic provisioning of cloud BS resources. This paper presents a novel C-RAN Call Admission Control (C-RAN CAC) to ensure Grade of Service (GoS) by improving blocking probability and improvement of call waiting times. Call blocking probability, call average waiting time and system utilization are used to evaluate the performance of the proposed CAC algorithm.

This article provides an overview of radio resource management (RRM) in the context of network slicing considering a range of different deployment options and practicalities. Initially, it elaborates the 3GPP radio access network (RAN) sharing in terms of business and architecture. Slice‐tailored RRM solutions are then considered for various base station deployments focusing on RRM principles and customization, which result in different paradigms of resource sharing including full isolation, sharing, and hybrid approaches. The concept of slice broker is also elaborated, which aims to allocate radio resources related to slice requests considering the desired service performance, highlighting the need of traffic and mobility forecasting. The notion of resource sharing is further analyzed, considering various RRM and scheduling schemes including multi‐objective and hierarchical RRM, slice‐aware flexible function split, TDD service‐oriented solutions, and joint radio and backhaul optimization and licensed assisted configurations.

It has for long been recognized that in multi-cell wide-band code division multiple access (WCDMA) networks the admission of a new session into the system can have undesirable impacts on the neighboring cells. Although admission control algorithms that take into account such multi-cell impacts have been studied in the past, little attention has been paid to multi-cell admission and rate control algorithms when traffic is elastic. In this work, we propose a model for multi-cell WCDMA networks to study the impact of admission and rate control algorithms on key performance measures such as the class-wise blocking and dropping probabilities, block error rates and the overall throughput. By means of simulation we compare the performance of multi-cell algorithms with that of a single cell algorithm. For voice traffic, we find that multi-cell algorithms improve the session drop and block error probabilities in both of the examined heterogenous (termed "Hotspot" and "Hotround") scenarios. When traffic is elastic, the multicell algorithms perform better in the examined homogeneous case.

Featuring edge caching and computing, fog radio access networks have been seen as promising architectures. However, the joint optimization of cache and radio resource can put heavy burden on the resource manager in the cloud. To overcome this issue, hierarchical radio and cache resource management is studied in this paper. The core idea is to fully utilize the resource management capabilities of fog access points (FAPs) to divide time-domain resource on a small timescale by participating a coalitional game while make the resource manager allocate cache resource on a large timescale to maximize a long-term utility. Based on defined FAP preference, a low-complexity and distributed coalition formation algorithm is first developed under per-FAP fronthaul capacity constraints. Then, facing the challenges incurred by no closed form, discrete variables and the curse of dimensionality, multi-agent reinforcement learning (MARL) based caching is proposed for the resource manager. In the proposal, multiple agents are created, one for each content-FAP pair, who jointly learn a caching strategy via the interaction with a history network environment. By simulation, the effectiveness of the MARL based caching is demonstrated.

The interface management and resource allocation in backhaul (BH)/access networks for the cloud/centralized radio access networks (C-RAN) are two of the largest challenges to enable the C-RAN architecture deployment successfully in cellular wireless systems. From the PHY perspectives, one major advantage of C-RAN is the ease of implementation of multicell coordination mechanisms to manage the interference and improve the system spectral efficiency (SE). Theoretically, a large number of cooperative cells leads to a higher SE; however, it may also cause significant delay due to extra channel state information feedback and joint processing computational needs at the cloud data center, which is likely to result in performance degradation. In order to investigate the delay impact on the throughput gains, we divide the network into multiple clusters of cooperative small cells and formulate a throughput optimization problem. We model various delay factors and the sum-rate of the network as a function of cluster size, treating it as the main optimization variable. For our analysis, we consider both base stations' as well as users' geometric locations as random variables for both linear and planar network deployments. The output signal-to-interference-plus-noise ratio and ergodic sum-rate are derived based on the homogenous Poisson-point-processing model. The sum-rate optimization problem in terms of the cluster size is formulated and solved. From the radio resource management (RRM) perspective, we consider the problem of joint BH and access links optimization in dense small-cell networks with special focus on time division duplexing mode of operation in BH and access links transmission. Here, we propose a framework for joint RRM where we systematically decompose the problem in BH and access links. To simplify the analysis, the procedure is tackled in two stages. At the first stage, the joint optimization problem is formulated for a point-to-point scenario where each small cell is simply associated to a single user. In the second stage, the problem is generalized for multiaccess small cells. In addition, the chapter addressed thejoint routing and BH scheduling in a dense small-cell networks using 60 GHz multihop BH, coordinated by a local C-RAN central unit. The problem is formulated as a generalized vehicle routing problem and decoupled into two subproblems, channel-aware path selection and queue-aware link scheduling.

Commoditization and virtualization of wireless networks are changing the economics of mobile networks to help network providers, e.g. Mobile Network Operators (MNOs), Mobile Virtual Network Operator (MVNO), move from proprietary and bespoke hardware and software platforms to an open, cost-efficient and flexible cellular ecosystem. In addition, rich and innovation local services can be efficiently materialized through cloudification by leveraging the existing infrastructure. The future communication architecture for mobile cloud services - Mobile Cloud Networking (MCN) is a EU FP7 large-scale integrating project (IP) funded by the European Commission that is focusing on how cloud computing and network function virtualization concepts are applied to achieve virtualization of cellular networks. It aims at the development of a fully cloud-based mobile communication and application platform, or more specifically, it aims to investigate, implement and evaluate the technological foundations for the mobile communication system of long-term evolution (LTE), based on mobile network with decentralized computing and smart storage offered as one atomic service: on-demand, elastic and pay-as-you-go. MCN will investigate, implement and evaluate the technological foundations for that system to meet real-time performance and support efficient and elastic use and sharing of radio access and mobile core network resources between operators. Mobile network functionalities-such as baseband unit processing, mobility management and quality of service (QoS) control-will run on the enhanced mobile cloud platform leveraging commodity hardware, which requires extensions toward higher decentralization and enhancing them to elastically scale up and down based on load. The end-to-end control and management orchestrates infrastructure and services across several technological domains: wireless, mobile core and data centres, providing guaranteed multiple end-to-end service, mobility through the Follow-Me Cloud concept. In this chapter, we present three enabling components of such a future MCN architecture: Radio Access Network as a Service (RANaaS), Information-Centric Networking as a Service (ICNaaS) and Mobility Prediction as a Service (MOBaaS).

In spite of promising outcomes in optimizing energy usage for Radio Access Network (RAN) Base Station (BS) hardware, deployment, and resource management, existing methods frequently lack flexibility for scenarios involving multiple frequencies and technologies of BSs. This investigation presents a comprehensive BS switching strategy based on a threshold, tailored for real-world multi-frequency and multi-technology BSs within the RAN. The proposed approach strategically deactivates BSs using a threshold parameter that determines the maximum allowable growth in transmission power for active BSs, ensuring both coverage for users affected by BS deactivation and energy saving. Simulations conducted on a realistic multi-technology 5G New Radio (NR) RAN in an urban environment validate the efficacy of the proposed strategy, achieving up to 73% of energy saving. The study assesses the influence of the frequency order of BS deactivation and examines user re-association strategies aimed at minimizing either path loss or transmission power.

This paper presents an experimental wireless platform allowing the seamless handoff of mobile terminals with on-going video sessions across heterogeneous radio access technology networks. The handover decision is taken by considering parameters from the physical and network layers from both the mobile terminal and radio access networks using Media Independent Handover (MIH) concept. It is demonstrated that when the network is congested, triggering handover from MIH improves and maintains the perceived video quality of service.

The virtualisation of Radio Access Networks (RANs) is one of the goals in designing 5G mobile networks. This paper aims at presenting a proof of concept for the virtualisation of radio resources using Open Air Interface (OAI), a software-based Long-Term Evolution (LTE) eNodeB physical emulator. OAI was extended to support multi-tenancy, representing diverse Virtual mobile Network Operators (VNOs) with different Service Level Agreements (SLAs). A comprehensive analytical model for managing the virtual radio resources has been proposed, with two key parts: estimation of available radio resources and their allocation to different VNOs. The estimation is performed by the model, and the allocation is managed by OAI scheduling. Various scenarios and use cases are studied in this virtual RAN environment, network performance being evaluated for different situations, by varying guaranteed levels, serving weights, and used services. Results show that the proposed approach offers almost the same capacity to guaranteed VNOs regardless of other existing VNOs, experiencing at worst a degradation of 32% of its initial allocated data rate, without violation of the guaranteed data rate. The data rate allocated to best effort VNOs may decrease up to 7% of its initial value, which is acceptable, to guarantee other more demanding SLAs.