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Network slicing has emerged as a promising technical solution to ensure the coexistence of various 5G services. While the 5G architecture evolution for supporting slicing has been exhaustively studied, the architectural option impacts on RAN resource allocation efficiency remain unclear. This article fills a gap in this area by evaluating the impact of architecture choices on the quality of service of different services in the new 5G ecosystem, focusing on ultra-reliable low-latency communication applications. We propose architectural options based on the placement of the entities responsible for implementing these functions. We then assess their impact on the radio resource allocation flexibility when slices span two radio access technologies with redundant coverage. Our numerical experiments showed that the slice management function placement plays a pivotal role in choosing an adequate radio resource allocation scheme for URLLC slices.

This article studies cooperative vehicle platooning under different communications approaches and introduces a new dynamic control scheme based on the Predicted Cooperative Adaptive Cruise Control (PCACC). We start by a performance comparison of different communication technologies including VLC (Visible Light Communication) and V2V (Vehicle-to-Vehicle), with or without relaying via RSU (Road Side Unit), and assess their suitability to fully cooperative and semi-autonomous control schemes. Different from the state of the art, our main design goal is the robustness in terms of an extremely low probability of emergency braking under varying communication conditions and bursts of packet losses. In the light of the performance results, we propose an adaptive control mechanism that tunes the control gains as a function of the observed radio link quality and demonstrate, via extensive simulations, a significantly better performance compared to static control strategies.

International audience; In this paper, we exploit the use of unlicensed spectrum in industrial scenarios for UltraReliable Low-Latency Communication (URLLC). We consider a set of automated machines communicating with a central base station and competing to the radio resources among themselves and with enhanced Mobile Broadband (eMBB) traffic. Observing the impact of Listen-Before-Talk (LBT) on the stringent reliability and delay requirements, we propose a progressive bilevel power transmission policy for URLLC, where a high power transmission can be regarded as a preemption of eMBB packets with lower power. We formulate the objective as a stochastic optimization problem under constraints and solve it in the simple Aloha-like case, and in the more complex LBT case. We then use this model to build an online (re-)transmission algorithm which enables the URLLC stations to determine in a distributed manner the optimal policy using observations of the environment parameters.

International audience; We focus in this paper on the transport of critical services in unlicensed spectrum, where stringent constraints on latency and reliability are to be met, in the context of Ultra-Reliable Low Latency Communication (URLLC). Since contention-based medium access performs poorly in the case of high traffic load, we propose a new transmission scheme where the transmitter can increase its transmission power when the delay of the packet approaches the delay constraint, increasing by that its chance of being decoded even in case of collision with other lower-power packets. We are however interested in minimizing the usage of high power transmissions, mainly to conserve energy for battery-powered devices and to limit the range of interference. Therefore, we define a transmission policy that makes use of a delay threshold after which the high-power transmission starts, and propose a new online-learning approach based on Multi-Armed Bandit (MAB) in order to identify the policy which achieves minimum energy consumption while guaranteeing reliability. However, we observe that the MAB converges slowly to the optimal policy because the loss event is rare in the load regime of interest. We then propose a model-aided learning approach where a simple analytical model helps estimating the longterm reliability resulting from an action and thus its reward. Our results show a significant enhancement of the convergence towards the optimal policy.

International audience; Network slicing has emerged as a promising technical solution to ensure the coexistence of the various 5G services. While the evolution of the 5G architecture for supporting slicing has been thoroughly studied, the impact of the architectural options on RAN resource allocation efficiency is still unclear. This article fills a gap in this area by assessing the impact of architecture choices on the quality of service of different services, with a focus on ultra-reliable low-latency communication applications. We propose architectural options based on the placement of the entities responsible for implementing these functions. We then assess their impact on the radio resource allocation flexibility when slices span two radio access technologies with redundant coverage. Our numerical experiments show that the placement of the slice management functions plays a crucial role in the choice of the radio resource allocation scheme that best fits URLLC slices. Index Terms-5G, network slicing, quality of service, ultra-reliable low-latency communication (URLLC), resource allocation , redundancy, join the shortest queue.

In this paper, we study the performance of packet scheduling schemes for Ultra-Reliable Low-Latency Communications (URLLC) services. In order to ensure a low queuing time, we exploit the redundant coverage in many 5G Radio Access Networks (RAN) scenarios, where two frequency layers or Radio Access Technologies (RAT) are integrated. We consider three packet scheduling and redundancy schemes, namely Jointhe- Shortest-Queue (JSQ), systematic Redundancy (RED), and redundancy with Cancellation upon completion (CAN). On the basis of queuing theory results, we develop expressions for the reliability, defined as the probability that the packet is transmitted before some given target delay. We show that RED has a good performance at low load, while JSQ is better when the load increases; CAN outperforms all other schemes. We then show how the obtained results can be used for the dimensioning of needed 5G radio resources and discuss the trade-off between performance and implementation complexity.

In this paper, we study DownLink Preemption (DLP), a feature enabling dynamic scheduling for Ultra Reliable Low Latency Communications (URLLC) in the presence of ongoing enhanced Mobile Broad Band (eMBB) flows. We design a DLP technique with the objective of maximizing the admission of URLLC packets while minimizing the impact of preemption on the eMBB throughput. We propose two different approaches to solve the DLP problem. A first, the Offline Preemption Approach (OPA), is formulated as a multi-objective Integer Linear Program (ILP) and considers a perfect knowledge of traffic dynamics. We further propose the Impact-Aware Preemption Approach (IAPA), an algorithm solving the DLP problem and performing joint admission and preemption decisions on the fly. We conduct extensive simulations using a system level simulator in realistic 5G Network settings. Our numerical results demonstrate the efficiency of IAPA in guaranteeing a close-to-optimum performance.

Many Industrial Internet of Things (IIoT) use cases are characterized by a large number of users transmitting sporadically packets to a central controller. The transmitted packets have to be conveyed within a very short time so that it is not possible to make per-packet resource reservation, and contention-based access is needed, which is conflicting with the very stringent reliability constraints. In order to achieve both reliability and latency constraints, we consider in this paper the combination of contention-based access with blind replication of packets. Knowing the limited, but large, number of potential users in the system, we propose a semi-centralized channel access scheme where each user is pre-allocated positions for its replicas in case he has a packet to convey. We show, using coding theory, how to design sequences for users so that the number of collisions is minimized. We further exploit our pre-allocation scheme to develop a successive interference cancellation method where the base station tries to decode a packet based on the knowledge of the already decoded colliding packet. We show that the proposed schemes succeed to attain very low loss rates with low resource reservation.

International audience; This article addresses communication and control aspects of platooning systems with the related challenges introduced by the overlap of both areas. The main objective is to provide a dynamic control mechanism where the parameters of the well-known Predicted Cooperative Adaptive Cruise Control (PCACC) are adapted based on the observed quality of the V2V (Vehicle-to-Vehicle) communication links. Different from the state of the art, our main design goal is the minimization of inter-vehicular distances while being robust in terms of an extremely low probability of emergency braking. A new adaptive control scheme based on the offline optimization of the control gains is proposed. We evaluate the new approach in a highway scenario and show the improvements obtained by the dynamic adaptation of the control parameters over static control strategies. Index Terms-Vehicle platoons, cooperative adaptive cruise control (CACC), wireless communication.

We evaluate the throughput performance of a mobile network cell where device to device (D2D) communication, using part of the resource blocks of the considered cell, is used to offload the base station (BS) of part of its content delivery traffic. We suppose download requests occur according to a Poisson process from uniformly distributed user locations and are preferentially satisfied by one or more helpers whose number and positions are described by a Poisson process in the plane. We characterize optimal content placement for both regular caching, where sets of entire objects are cached by the helper devices, and coded caching, where each helper caches random coded chunks of certain objects such that a download may successively require several helpers and the BS. A multi-class processor sharing model is developed to determine the optimal resource partition between D2D and BS subsystems and evaluate the resulting throughput performance. Numerical results demonstrate significant capacity gains, notably for coded caching, that may well justify the added complexity of D2D communication.

We investigate in this paper uplink transmission schemes for 5G Ultra-Reliable Low Latency Communications (URLLC) traffic. The URLLC class of services has been defined for applications requiring extremely stringent latency and reliability. We show that, in systems with episodic traffic and many users compared with the number of transmission resources, randomly transmitting multiple copies of a packet allows to meet the URLLC requirements. We first develop an analytical model for the packet loss rate for a contention based multiple transmission scheme where replica positions are assigned randomly and show that it allows to meet the performance requirements of URLLC for small enough user activity rate. We then propose an advanced replication scheme where positions for the different replicas are pre-allocated to users so that users have pairwise-distinct positions. We show that this advanced scheme achieves very high reliability with low resource consumption.

We propose a novel resource allocation scheme for Ultra- Reliable and Low Latency communication (URLLC) traffic in the uplink of 5G systems. We consider industrial scenarios where a set of machines transmit packets intermittently to a central controller via a base station. We consider contention-based access in realistic scenarios where the delay budget and the 5G New Radio (NR) design allows the reception of few Acknowledgements (ACK), but always waiting for ACKs before retransmission is insufficient to ensure high reliability. This may be seen as a problem of Automatic Repeat Request (ARQ) with delayed feedback. The goal is to minimize the expected number of retransmissions subject to a reliability constraint within a delay budget. We derive the optimal policy that exploits the tradeoff between waiting for the ACK and achieving the target reliability.

International audience; We provide a flow level analysis of the offloading capability of D2D technology when devices endowed by caches are moving in the network, within the cell and among cells. We introduce the mobility with respect to the receiving user when we consider D2D communication and with respect to the base station when we consider the classical cellular communication. Due to mobility, the quality of both D2D and cellular communication may change over time which makes the analysis challenging. We describe the system through an exact Markovian model, however, since it does not scale with the number of admissible users we provide a closed form approximation model based on multi-class Processor Sharing queue. Numerical results validate the accuracy of our approximation and show a large offloading potential of D2D when devices are equipped with caches. We also observe that mobility increases offloading capability of D2D communications with respect to the static case.

International audience; We study in this paper the transport of Ultra-Reliable Low-Latency Communication (URLLC) in a scenario of Industry 4.0 where transmission in uplink is possible in both licensed and unlicensed spectrum. We propose a transmission policy where the packet first attempts transmission in unlicensed spectrum during a time budget smaller than the delay constraint, if the transmission fails then the packet uses the remaining time budget to attempt transmission in licensed spectrum. The goal of using this policy is to minimize the cost of licensed bandwidth required for URLLC. We first consider the case of one tenant managing the industrial area and quantify the needed licensed bandwidth to attain reliability target within the target delay. We optimize the system by choosing the transmission policy which minimizes this cost. We then study the case of multiple tenants present in the same area and sharing unlicensed spectrum. Each tenant tries to minimize its cost of licensed bandwidth by utilizing unlicensed resources, which may result in the tragedy of the commons like situation. We formulate the problem using a game-theoretic approach to model the non-cooperative multi-tenant scenario. We model the medium access of unlicensed system for this case and derive the strategies that minimize individual cost functions. We then prove the existence of pure Nash equilibria analytically and identify them numerically. Finally, we quantify the so-called price of anarchy, i.e., ratio of the utility yielded by the competitive setting to the outcome of a cooperative scenario.

International audience; This article investigates the slicing concept in the 5G Radio Access Network (RAN) with the related challenges and research problems. The objective is to identify the plausible options for implementing the slicing concept at the RAN level by the Mobile Network Operator (MNO) to respond to the needs of verticals. We start by identifying the different slice granularity options, i.e., how to define slices by combining customer and service needs. We then present how the 5G New Radio (NR) features can be used for facilitating slice implementation and provide typical configurations for different slice types from technology and RAN architecture perspectives. The main challenges for RAN slicing are then discussed, with a special attention to the resource allocation problem between slices sharing the same spectrum band. We also investigate the multi-tenant slicing implementation in terms of the openness of the network to third parties which is regarded as a key issue that may encourage vertical players to use operators' networks rather than deploying their own infrastructure.

International audience; We focus in this paper on energy management strategies for a mobile network equipped with battery storage capacity as well as local energy production capability, and powered by a smart grid. At each time instant, the mobile network operator has to decide whether to operate its network based on its own energy resources or the smart grid ones, with a possibility to sell energy to the smart grid as well. We formulate our problem using Markov Decision Process (MDP) and derive an optimal, offline policy which minimizes the operator energy bill, using dynamic programming algorithm. We show the optimality of our solution by numerical comparison with the solution obtained through linear programming. Our numerical applications allow to further understand when the operator has an incentive to buy energy, whether it is beneficial for it to act as an energy seller, the size of the battery to deploy, as well as the robustness of our offline deterministic policy to estimation errors

We focus in this paper on energy management strategies for mobile networks equipped with battery storage capacity and powered by a smart grid. We consider the case where the network operator signs an incentive based demand response contract with the energy provider, in which case the former should stop using the grid if the latter tells it to do so, typically in periods of high energy consumption. The operator gets in this case a premium, e.g. in the form of a discount on its energy bill. However, if the operator fails to comply with the energy reduction requests, it would pay a penalty. We formulate the problem using Markov Decision Process (MDP) and apply dynamic programming algorithm to devise an optimal offline policy which minimizes the network operator energy expenditure, by indicating to it when to buy energy and when to operate its network on the smart grid or on its own energy storage. We also show how the operator should manage its battery in order to respond to the energy provider requests to stop consuming from the grid at high electricity load.

The 5-th Generation (5G) of wireless networks is expected to support a wide set of use cases with ultra-reliable and very-low latency requirements. New Radio (NR) system design and different numerologies (subcarrier spacings) are adopted in the 3rd Generation Partnership Project (3GPP) standards in order to satisfy these stringent requirements. In this paper we study i) the user-plane latency performance of Ultra-Reliable and Low-Latency Communications (URLLC) for 15, 30, 60 and 120 kHz numerologies; ii) the service availability that is considered as essential metric for measuring the performance of the 5G networks; iii) the impact of allocating a dedicated bandwidth to URLLC services on the latency targets of URLLC packets and on the throughput of the coexisting evolved Mobile Broadband (eMBB) services.

This paper proposes a traffic model for mobile networks carrying adaptive streaming. The proposed model takes into account the flow dynamics and some application-level parameters influencing the performance of adaptive streaming, such as the presence of a playout buffer, chunk duration configuration and the video bit rate configuration. Paper shows based on flow-level queueing model how to compute performance metrics for a streaming user such as average video bit rate, average service time, average deficit rate, defined as the probability of having its instantaneous throughput lower than the chosen video bit rate and average buffer surplus, related to the amount of video accumulated in the buffer. Since heterogeneous radio conditions and the coexistence of elastic traffic and streaming services make the exact solution intractable, we propose a simple yet accurate approximation that reduces the computational complexity and makes system dimensioning easier for mobile network operators. Our numerical results show the performance impacts of video chunk duration and amount of available video bit rate. These performance impacts obtained by our models give an insight for operators to properly dimension their adaptive streaming service by well configuring both HTTP-level and MAC-level parameters.

International audience; Ultra-Reliable and Low Latency Communications (URLLC) is a challenging class of services to be supported by the fifth generation of mobile networks (5G). Among the URLLC services, many use cases, especially those related to factory automation, involve communications with relatively static radio conditions and a periodic generation of control or data packets. The transmission of these packets requires extremely low latency and ultra-reliable communication to enable real-time control of automation processes. In this paper, we discuss a mechanism of deterministic resource allocation to meet the URLLC requirement in terms of reliability and latency, including initial transmissions and controlled retransmissions. A joint resource allocation and modulation and coding schemes selection is performed so that the resource consumption is minimized, subject to latency and reliability constraints. We show that when applying the proposed resource allocation technique it is possible to achieve very low error rates.

In this work, we combine base station sleep mode strategies and device to device (D2D) communications to design solutions for 5G green mobile networks. The basic idea is that switching-off base stations allows to save energy while D2D technology guarantees coverage. We consider the realistic case of multi-layer cellular network and explore two sleep mode mechanisms: partial sleep mode (PSM) where only the frequency layer guaranteeing coverage at cell-edge is turned off, and deep sleep mode (DSM) where the base station is switched-off completely. Once a base station is switched-off multi-hop D2D communications are enabled to provide coverage. Cellular and D2D communications are modeled using queuing theory and sharing radio resources among them in an optimal way guaranteeing the stability of the system. We evaluate the time period of sleeping base stations in function of device battery discharging and hence the corresponding network energy savings. Results show that the combination of sleep mode strategies and D2D communications provides energy savings using an acceptable device battery discharge.

International audience; We consider in this paper a heterogeneous wireless network where the cell sites, known as Remote Radio Heads, are connected to a central processing unit composed of a pool of Base Band Units, so-called Virtual-Radio Access Network (V-RAN). We evaluate its performance, in terms of user flow throughput, system stability and fairness under two resource allocation strategies: Dominant Resource Fairness (DRF) and a heuristic based on Proportional Fairness (PF), which we apply locally on each access network; both allocations being applied jointly on radio and processing resources. We consider the case when the V-RAN is restrictive in terms of processing resources as compared to the radio ones, and compare it to the case when the V-RAN is not restrictive. Our results show that locally-applied PF achieves higher throughput and system stability than DRF, which achieves better fairness

HCERES C, ABS 1; International audience; This work presents a strategic investment framework for mobile TV infrastructure. We address the question of whether an operator should enter the mobile TV market and, if yes, how and when to do so. We perform a capacity and QoS analysis that shows that Mobile TV is not a simple added-on service but requires new planning strategies that need heavy investments. We consider two possible settings: a competitive mobile TV network where a digital video broadcasting (DVB) operator and a cellular network operator build their independent networks and a cooperative setting where the TV network is mainly relying on a DVB infrastructure whose coverage can be complemented by a cellular network. Two main issues alter the investment decision of the stakeholders, namely, the market uncertainty and the competition or the willingness of cooperation between the main technological players. We define a game theoretical real options framework and propose a novel bi-level dynamic programming algorithm that solves the underlying profit maximization problem. Our numerical results illustrate the optimal investment decisions of both actors and the impact of the system parameters as well as the degree of uncertainty on the investment dates

International audience; We focus in this paper on energy management strategies for mobile network, equipped with battery storage capacity as well as local energy production capability, and powered by a smart grid. At each time instant, the mobile network operator has to decide whether to operate its network based on its own energy resources or the smart grid ones, with a possibility to sell energy to the smart grid as well. We formulate our problem using Markov Decision Process (MDP) and derive an optimal policy, which minimizes the telecommunication operator energy bill, using dynamic programming algorithm. We show the optimality of our solution by numerical comparison with the case of being exclusively powered by the grid. Our numerical applications allow to further understand when the operator has an incentive to buy energy, whether it is beneficial for him to act as aggregator (energy seller) as well as the size of the battery to deploy

International audience; Today, mobile networks are witnessing an exponential growth of traffic volumes, linked to new services, especially for smart cities and smart-grid. The European Celtic-Plus SooGREEN project, started mid 2015, is targeting to reduce the energy consumption of the services in different mobile architectures in interaction with smart-grid. SooGREEN is focused on the services energy consumption modelling and measurement, the dynamic optimization of the mobile access network and of the content delivery, the design of an Energy Efficient Virtualized and Centralized Radio Access Network (RAN), and the bi-directional interaction of the mobile network with the smart-grid. This paper presents insight into the project after its first year, and discusses research trends in green communication networks for the future.

Cloud radio access network (CRAN) has been proposed as a promising evolution of mobile network architecture where baseband processing functions of a base station are split/decoupled from the radio unit (RU) and centralized. However, rigid bandwidth and latency requirements are incurred by fronthaul, i.e., transport link, which connects RU to the central cloud. Therefore, new functional splits are discussed for CRAN with dual-site processing, which we call Hybrid-RAN (H-RAN), where some functions remain distributed while others are centralized. In this work, from a perspective of minimizing the total cost of ownership (TCO) for H-RAN, we present a techno-economic study to find the optimal functional splits for a base station (BS), with a given configuration. A configuration of a BS represents frequency layers, carrier bandwidths, and MIMO schemes, associated with different frequency bands. For each functional split, we present a model to calculate the requirement of computational resources and fronthaul bandwidth. We formulate a TCO minimization model using constraint programming. Numerical results show that the optimal functional split depends on BS configuration, fiber ownership, and data transmission direction. H-RAN with optimal functional split can achieve lower TCO than both classical Distributed RAN and CRAN.

As video accounts for larger wireless traffic, improving users' quality of experience becomes important for network service providers. In this paper, we apply supervised machine learning technique to predict one objective QoE metric, video starvation, with the users' features, recorded at the beginning of each video session. We show that static users and adaptive streaming users have less starvation events and that mobile users are more difficult to predict their video starvation. In terms of users' features, we show that system parameters such as channel conditions and number of active users are two important features which contribute to better prediction performance. Prediction with the two features can provide sufficient accuracy for static users but not sufficient for mobile users. We also demonstrate that the two information, number of users served in a cell and the number of users experiencing video starvation, provide similar prediction accuracy.

International audience; Our aim in this work is to develop profit sharing strategies for coooperative 4G Long Term Evolution (LTE) and Digital Video Broadcasting - Next Generation Handheld (DVB-NGH) systems offering mobile TV service. We first study the capacity of the hybrid system for offering such a service and derive the associated cost for each network. We then focus on the sharing of profit between LTE and DVB operators as well as TV channels providers, taking into account the subscription revenues as well as the infrastructure and operation costs. We consider two cases: one in which both LTE and DVB networks are managed by a single operator and one in which the operators are separate. In both cases, we derive closed-form expressions for each player profit share using coalition game concept Shapley value. We further obtain the players optimal strategies, at the Nash equilibrium, where each player tries to maximize its own profit.

International audience; The purpose of this paper is to identify, through empirical validation, the best analytical model for QoS and capacity estimation in mobile data networks. We first present two different sets of models that have been proposed in the literature: the infinite source, Erlang-like models and the finite source, Engset-like models. While the former models are widely developed and adapted to mobile networks, the latter are less used in the mobile context. We thus derive novel analytical models to complete the finite source theory before moving to the comparison of the different models. We make use of network measurements originating from an HSPA network and compare the modeled performance with the observed one, for each of the available analytical models. Our results show that a Processor Sharing analysis that takes as cell capacity the harmonic average of the achievable throughputs and as traffic inputs the volumes generated in each CQI, gives results that are close to the field measurements. As of the finite source models, we observed a good match on some cells and a mismatch on other cells. This is due to the difficulty of extracting traffic parameters from the field. However, finite source models have a better predictive power than infinite source models, as their traffic characteristics can more easily be linked to changes in the network such as the introduction of new services or new devices.

International audience; We consider a scenario where an Internet Service Provider (ISP) serves users that choose digital content among M Content Providers (CP). In the status quo, these users pay both access fees to the ISP and content fees to each chosen CP; however, neither the ISP nor the CPs share their profit. We revisit this model by introducing a different business model where the ISP and the CP may have motivation to collaborate in the framework of caching. The key idea is that the ISP deploys a cache for a CP provided that they share both the deployment cost and the additional profit that arises due to caching. Under the prism of coalitional games, our contributions include the application of the Shap-ley value for a fair splitting of the profit, the stability analysis of the coalition and the derivation of closed-form formulas for the optimal caching policy. Our model captures not only the case of non-overlapping contents among the CPs, but also the more challenging case of overlapping contents; for the latter case, a non-cooperative game among the CPs is introduced and analyzed to capture the negative externality on the demand of a particular CP when caches for other CPs are deployed.

The paper elaborates on the technological and architectural innovations researched and developed by 5G-PPP Phase 1 projects and covering innovation areas such as 5G system design and evaluation, novel air interfaces, network management and security as well as virtualization and service deployment aspects., © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Mobile networks will support increasing numbers of connected vehicles. Successive generations of mobile networks have reduced the cost of data rate, in terms of spectrum usage and power consumption at the base station, by increasingly exploiting the concept of channel state information at the transmitter. Unfortunately, beyond a limiting velocity (which depends on the carrier frequency), networks are no longer cost efficient, since such information is not usable. Recently, channel prediction techniques requiring several antennas on the car roof have been introduced to solve this problem. In this paper, for the first time, we determine the most cost efficient configurations, in terms of numbers of antennas on the car roof and carrier frequency, in various scenarios (highway and dense urban). Our studies show that with a simple prediction technique based on predictor antennas, the network can use twice less spectrum and around 20 dB less power, for cars with 3 antennas on their tops than for cars with the same number of antennas and not using prediction.

International audience; We study in this work user impatience by adopting a realistic realization: a user gets impatient when its throughput falls below a certain threshold for a given patience duration. We model such a behavior in a cellular network, transporting elastic flows, for a realistic user configuration with random arrivals, following a Poisson process, and departure after a finite duration, either upon transfer completion or because of impatience. We derive several performance metrics, pertaining to the probability of abandoning the transfer as well as transport efficiency in terms of traffic efficiently transported until service completion versus wasted resources because of abandonment. We further implement a control mechanism using two approaches: a preventive one, based on blocking of users when their number exceeds a certain threshold, and a reactive one, based on dropping of users when the network experiences congestion, and show how the system performance gets enhanced in both cases

We investigate streaming over multiple links. A file is split into small units called chunks that may be requested on the various links according to some policy, and received after some random delay. After a start-up time called pre-buffering time, received chunks are played at a fixed speed. There is starvation if the chunk to be played has not yet arrived. We provide lower bounds (fundamental limits) on the starvation probability of any policy. We further propose simple, order-optimal policies that require no feedback. For general delay distributions, we provide tractable upper bounds for the starvation probability of the proposed policies, allowing to select the pre-buffering time appropriately. We specialize our results to: (i) links that employ CSMA or opportunistic scheduling at the packet level, (ii) links shared with a primary user (iii) links that use fair rate sharing at the flow level. We consider a generic model so that our results give insight into the design and performance of media streaming over (a) wired networks with several paths between the source and destination, (b) wireless networks featuring spectrum aggregation and (c) multi-homed wireless networks., Comment: 24 pages

One of the objectives of METIS-II project is to facilitate discussion on scenarios, use cases, KPIs and requirements for 5G, building upon the comprehensive work conducted in the METIS-I project and taking the work of other European projects as well as other bodies such as ITU-R, NGMN, etc. into account. This paper analyses the landscape of 5G use cases and presents METIS-II 5G use cases that cover the main 5G services, have stringent requirements and whose technical solutions are expected to serve other similar use cases as well. It also links these use cases to the business cases defined by 5G PPP so that requirements of vertical industries can be taken into account when designing the 5G Radio Access Network (RAN).

International audience; This paper presents an analytical performance evaluation framework for 4G/WiFi multihoming techniques. Several multihoming flavors have been compared, with a focus on user centric allocation strategies. In these strategies the user splits his packets between two radio interfaces following a policy that depends on the amount of information he gets. First, the simplest policy is considered in which the user sends an amount of traffic on each interface proportional to the latter's peak rate. Second, the optimal selfish policy is investigated in which the user has complete information about the traffic intensities. This latter policy has been proved to achieves a global optimum. The numerical results show that an optimized user centric policy achieves good gains for both the system capacity and the user throughput compared to a peak maximization strategy. The results also show that multihoming provides large performance gains for multi-homed users while degrading neither the capacity of the system nor the performance of single-homed users

Although adaptive streaming is becoming a preponderant technology for online streaming providers, the design of video chunks has not been well examined in the literature. This issue becomes more important in a mobile context characterized by a large heterogeneity of radio conditions between users. We develop in this paper some flow-level models to assess the impact of different video chunk durations. Our analytical and simulation results show that smaller chunk durations can improve the video smoothness and reduce buffer starvation events. However, this would require to increase HTTP signaling and to manage many headers and URLs of video chunks. To resolve this challenge, we propose to transmit multiple chunks instead of one chunk in an HTTP request. We show that our proposal can achieve better video smoothness as the case of deploying shorter chunk duration while keeping the same number of video chunks.

This paper investigates the network offloading capability of Device to Device (D2D) communication when combined with content caching. We consider a mobile network where a proportion of users are equipped with caches from which other users can retrieve contents using direct D2D communications. In this case, the offloading capacity depends both on the cache performance and the quality of the D2D links. As of the cache performance, we develop an analytical model for the cache hit rate for different content prefetching strategies. We then inject this hit rate in a queuing theory analysis of the network capacity where the macro base station and the D2D links are modeled as coupled Processor Sharing (PS) queues. We develop closed-form solutions for the stability region and the performance gains for both one-hop and two-hop D2D. Our simulation results illustrate the offloading capacity and present optimal cache and network parameters that maximize the benefit of D2D communications.

International audience; We study in this work the quality of experience of live mobile TV users in the presence of a playout buffer at the receiver side. We specifically consider an LTE network delivering both unicast and broadcast services, and study two cases: i. lossless channels where interruptions in mobile TV delivery are due to the absence of resources at the base station because they are totally consumed by higher priority real-time voice services, and ii. lossy channels, where we propose to exploit the existence of feedback channels to request, if possible, retransmission of the lost video frame. We derive in both cases several QoS metrics pertaining to mobile TV performance, such as interruption frequency and duration as well as video frame loss probability. Our results show the trends of these metrics as a function of several system parameters and yield design rules for network planning as well as for the playout buffer so as to enhance efficiently the live TV watching experience

International audience; We study, in this work, optimal sleep/wake up schemes for the base stations of network-operated femto cells deployed within macro cells for the purpose of offloading part of its traffic. Our aim is to minimize the energy consumption of the overall heterogeneous network while preserving the Quality of Service (QoS) experienced by users. We model such a system at the flow level, considering a dynamic user configuration, and derive, using Markov Decision Processes (MDPs), optimal sleep/wake up schemes based on the information on traffic load and user localization in the cell, in the cases where this information is complete, partial or delayed. Our results quantify the energy consumption and QoS perceived by the users in each of these cases and identify the tradeoffs between those two quantities. We also illustrate numerically the optimal policies in different traffic scenarios

International audience; The Quality of Experience (QoE) of streaming service is often degraded by frequent play-back interruptions. To mitigate the interruptions, the media player prefetches streaming contents before starting playback, at a cost of initial delay. We study the QoE of streaming from the perspective of flow dynamics. Firstly, a framework is developed for QoE when streaming users join the network randomly and leave after downloading completion. We model the distribution of prefetching delay using partial differential equations (PDEs), and the probability generating function of playout buffer starvations using ordinary differential equations (ODEs) for constant bit-rate (CBR) streaming. The explicit form starvation probabilities and mean start-up delay are obtained by use of a matrix function approach. Secondly, we extend our framework to characterize the throughput variation caused by opportunistic scheduling at the base station, and the playback variation of variable bit-rate (VBR) streaming. Our study reveals that the flow dynamics is the fundamental reason of playback starvation. The QoE of streaming service is dominated by the first moments such as the average throughput of opportunistic scheduling and the mean playback rate. While the variances of throughput and playback rate have very limited impact on starvation behavior in practice.

International audience; In this work, we develop performance evaluation models for some intra-site coordination schemes in cellular networks, with a focus on Multi-flow transmission in HSPA+. We first focus on a static scheme where coordination is always performed for all users in the overlapping region of two cells. Through the analysis of a flow-level model, we show that this scheme indeed improves the cell-edge throughput at low loads but may make the system unstable at high loads, due to the suboptimal allocation of radio resources. We notice also that these results are very sensitive to the coordination threshold. We thus investigate a dynamic scheme which performs coordination according to resource availability in the site and show that this scheme outperforms the static one at all traffic loads independently of the coordination threshold. Additional results demonstrate an efficient load balancing ability across cells. We finally analyze how our models extend to the case of opportunis-tic scheduling schemes, like Proportional Fair, and show the impact of these schemes on the coordination gains.

International audience; The paper considers the use of caching in mobile access networks and seeks to evaluate the optimal memory for band-width tradeoff at base station (BS), packet gateway (PGW) and a possible intermediate mobile cloud node (MCN). Formulas are derived for the hit rate under time varying popularity and for a novel cache insertion policy incorporating a pre-filter. The analytical model is applied first to demonstrate that reactive caching is not efficient for nodes with low demand due to the negative impact of content churn. This means BS or MCN caches must be managed proactively with popular content items pre-fetched under some centralized control. Quantifying the tradeoff at each level leads us to conclude that limited caching at BS and MCN levels brings significant savings while to store the vast majority of the content catalogue at the Internet edge, at the PGW or in some higher level shared facility, is clearly cost effective.

International audience; Cooperation in multi-access wireless networks have become an effective strategy for answering the rising data rate requests. The interworking is performed either by traffic steering, load balancing or yet radio resource aggregation, the so-called multi-homing. While most studies focused mainly on the first two techniques, we focus in this work on multi- homing, and target principally LTE and WiFi access networks. We specifically consider the co-existence of several classes of users in the system: single-homed users and multi- homed users, and study two network-centric, resource allocation strategies: proportional fairness applied to the global network as a whole or to each wireless access network in isolation of the other. We evaluate the system performance and show that both strategies improve the achievable throughput and stability conditions by applying a load balancing between accesses, thus increasing the overall network capacity

International audience; This paper proposes a performance model for mobile networks carrying adaptive streaming traffic. The proposed model takes into account the flow dynamics in addition to the main parameters influencing the performance of adaptive streaming, such as the playout buffer and the video bit rates. We show how to compute several performance metrics like the average video bit rate, the deficit rate, defined as the probability of having an instantaneous throughput lower than the chosen video bit rate, and the average buffer surplus, related to the amount of data accumulated in the buffer. Considering the coexistence of multiple services and heterogeneous radio conditions that make the exact solution intractable, we propose a simple yet accurate approximation that is easy to integrate in the operator's dimensioning tools. Our numerical results investigate the performance trade-offs between the different parameters of the adaptive streaming service.

International audience; Carrier aggregation and multi-flow transmission are among the most important features of HSPA+. While the former allows users to be served simultaneously by several carriers in the same sector, the latter enables adjacent sectors to simultaneously schedule different data streams to the same user in their over-lapping region. In this paper, we investigate the inter-operation of these two features. We evaluate the flow-level performance using a method based on network simulation coupled with Markov chain analysis. Results in single-carrier mode show an improvement in throughput at low load and an efficient load balancing across sectors at high load. In multi-carrier mode, we show that coordination is no more recommended since it does not achieve any throughput gain over the classical multi-carrier system. This is due to the actual status of the standard that limits the number of carriers that can be used for the multi-flow transmission to two. However, if this restriction is released in the standard, our results show that multiflow transmission would bring significant gains.

Among the several features that are foreseen for increasing the capacity of cellular systems, Multi-user multiple- input multiple-output (MU-MIMO) is considered as a key en- abling technology. Particularly, MU-beamforming is a powerful means of increasing the system capacity and throughput by creating several spatial signals to different users on the same time/frequency resource. In this paper, we develop an analytical model for MU-beamforming based on queuing theory combined with network simulations. The proposed framework is used for evaluating the potential gains in terms of capacity and throughput in LTE-Advanced system. Several scenarios are studied, with and without beamforming. Results show an important gain of SU-beamforming over the classical system without beamforming and a further gain of MU-beamforming, especially at high loads. Index Terms - Multi-user beamforming, LTE-Advanced, Flow Level Modeling, Queuing Theory, Simulations. I. I NTRODUCTION

In this paper, we study the performance of multicarrier mobile networks. Specifically, we analyze the flow-level performance of two inter-carrier load balancing schemes and the gain engendered by Carrier Aggregation (CA). CA is one of the most important features of HSPA+ and LTE-A networks; it allows devices to be served simultaneously by several carriers. We propose two load balancing schemes, namely Join the Fastest Queue (JFQ) and Volume Balancing (VB), that allow the traffic of CA and non-CA users to be distributed over the aggregated carriers. We then evaluate the performance of these schemes by means of analytical modeling. We show that the proposed schemes achieve quasi-ideal load balancing. We also investigate the impact of mixing traffic of CA and non-CA users in the same cell and show that performance is practically insensitive to the traffic mix., Comment: 8 pages, 6 figures, submitted to WiOpt2014

Our purpose in this paper is to characterize buffer starvations for streaming services. The buffer is modeled as an M/M/1 queue, plus the consideration of bursty arrivals. When the buffer is empty, the service restarts after a certain amount of packets are \emph{prefetched}. With this goal, we propose two approaches to obtain the \emph{exact distribution} of the number of buffer starvations, one of which is based on \emph{Ballot theorem}, and the other uses recursive equations. The Ballot theorem approach gives an explicit result. We extend this approach to the scenario with a constant playback rate using T\`{a}kacs Ballot theorem. The recursive approach, though not offering an explicit result, can obtain the distribution of starvations with non-independent and identically distributed (i.i.d.) arrival process in which an ON/OFF bursty arrival process is considered in this work. We further compute the starvation probability as a function of the amount of prefetched packets for a large number of files via a fluid analysis. Among many potential applications of starvation analysis, we show how to apply it to optimize the objective quality of experience (QoE) of media streaming, by exploiting the tradeoff between startup/rebuffering delay and starvations., Comment: 9 pages, 7 figures; IEEE Infocom 2012

International audience; The power demand of future wireless networks is predicted to dramatically increase. This energy consumption issue, if unaddressed, will restrict the roll-out of many new services. Based on this fact, we try in this paper to study and compare the energy consumption of the most popular mobile TV delivery solutions: LTE eMBMS and DVB-NGH. We study the energy consumption in a region where Mobile TV is delivered by a standalone LTE network and a standalone DVB-NGH transmitter or by a cooperative LTE/DVB network. By cooperation we mean that the mobile TV coverage is ensured by DVB in the region surrounding a broadcasting tower and by LTE otherwise. Our work is a simulation one and can be used as an offline study that enables the operators to configure their networks towards a Green Mobile TV delivery. Results shows that the cooperation will decrease the power consumption of at least one of the cooperative operators (LTE and/or DVB) and thus it will certainly decrease the overall power consumption in the service region for a high level Green Mobile TV solution.