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We design a multi-connectivity scheme based on the cooperation between the networks of the fourth generation (4G) and the fifth generation (5G) of mobile technologies, to improve the reliability of Ultra-Reliable Low-Latency Communication (URLLC) services. While 5G system is characterized by a short Transmission Time Interval (TTI) and fast retransmissions within the delay budget, 4G system has a large TTI so that only blind retransmissions are possible. We develop an optimization problem that couples this multi-connectivity with an adapted number of replications, scheduled by exploiting Power Domain Non-Orthogonal Multiple Access. The resulting optimal scheme is evaluated in an outdoor urban macro scenario for different reliability targets and user locations in the cell. Results show that the scheme minimizes the number of replicas while achieving the performance targets for both URLLC and eMBB users.

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.

We study in this paper the transport of Ultra-Reliable Low-Latency Communications (URLLC) in the presence of multiple tenants in a system composed of unlicensed and licensed spectrum, the former being shared by the tenants. Due to the stringent reliability and latency constraints of URLLC, the more expensive 5G licensed spectrum is used to serve the traffic that is not served by the unlicensed spectrum within a certain time budget. In a competitive scenario, where each tenant tries egoistically to minimize its share of the licensed spectrum, this 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 the combined unlicensed and licensed system to quantify the performance of the system, in terms of the overall probability of failure, and validate the model against simulations. We then derive the strategies that minimize individual cost functions. Our work gives insights about the existence of Nash equilibria 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; 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.

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.

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 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.

URLLC services are very demanding in terms of quality of service (QoS). We study in this paper dual-connectivity as an enabler for ultra reliability and specifically consider combining 4G and 5G spectrum for delivering URLLC packets. We compare different dual connectivity schemes, including a best link selection scheme and a maximum ratio combining scheme. We consider first an outdoor scenario with users served by macro base stations, where 4G and 5G transmitters are co-localized, and show that ultra-reliability is difficult to achieve everywhere unless the network is densified, or packets are replicated. We then study an industry 4.0 scenario where UEs are localized within a factory and served by indoor 5G small cells, in addition to coverage from outdoor 4G base stations, and show that URLLC requirements are achievable in this scenario.

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.

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.

In this work, we develop tractable flow level performance models for data traffic in cellular networks when users are moving inside the cell and among cells. Due to mobility radio conditions may change during transfer and classical flow level models can no more be used. We first consider an exact Markovian model that models explicitly the mobility between zones of different radio conditions during the data transfer and derive performance metrics such as sojourn and downloading times. However, as this Markovian model does not scale with the number of radio conditions and the number of admissible users, we propose a closed-form approximation model, based on a multi-class Processor Sharing. Numerical results show that the proposed model provides a very tight approximation. We then use this model in order to study the impact of mobility on different performance metrics.

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.

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

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.

Radio capacity simulation tools are gaining a large importance with the development of mobile networks. System radio simulators that are currently used in standardization bodies are becoming increasingly complex as they have to work on two time scales: the scale of “milliseconds” for modeling the behavior of schedulers and the scale of “tens of seconds” for modeling the dynamic behavior of arrivals and departures of users. In this paper, we propose a hybrid system simulation methodology that combines the advantages of system simulators in accurately modeling the physical/MAC interfaces, with the robustness of queuing theory analysis that catches the flow dynamics. We validate our simulation methodology versus complete system level simulators in representative scenarios and show an excellent match between both methodologies. We then show how to extend our simulation methodology for including a mix of services and how to incorporate network measurement results within the proposed methodology.

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; 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

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, 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

Distributing Radio Resource Management (RRM) in heterogeneous wireless networks is an important research and development axis that aims at reducing network complexity. In this context, RRM decision making can be delegated to mobiles by incorporating cognitive capabilities into mobile handsets, resulting in the reduction of signalling and processing burden. This may however result in inefficiencies (such as those known as the "tragedy of commons") that are inherent to equilibria in non-cooperative games. Due to the concern for efficiency, centralized network architectures and protocols keep being considered and being compared to decentralized ones. From the point of view of the network architecture, this implies the co-existence of network-centric and terminal-centric RRM schemes. Instead of taking part within the debate among the supporters of each solution, we propose in this paper hybrid schemes where the wireless users are assisted in their decisions by the network that broadcasts aggregated load information. At some system's states, the network manager may impose his decisions on the network users. In other states the mobiles may take autonomous actions in reaction to information sent by the network. In order to improve the performance of the non-cooperative scenario, we investigate the properties of an alternative solution concept named Stackelberg game, in which the network tries to control the users' behavior by broadcasting appropriate information, expected to maximize its utility, while individual users maximize their own utility. We derive analytically the utilities related to the Quality of Service (QoS) perceived by mobile users and develop a Bayesian framework to obtain the equilibria. Numerical results illustrate the advantages of using our hybrid game framework in an association problem in a network composed of HSDPA and 3G LTE system that serve streaming and elastic flows.

In this paper, the capacity of orthogonal frequency-division multiple-access (OFDMA) networks is evaluated when serving mobile TV traffic. To introduce the service within the network, we develop analytical cross-layer models to assess the performance of the system when carrying TV calls over unicast connections. The presented cross-layer analysis is general and can be adapted to all types of multimedia services. We then focus on a TV-specific capacity analysis, exploiting the possibility of broadcasting TV channels over point-to-multipoint (PtM) connections. This includes investigating an enhanced broadcast solution where the modulation is dynamically adapted to the radio conditions of connected TV users. The more complete broadcast solution over single-frequency networks (SFNs) is then evaluated, based on a novel physical-layer model integrating the combined signal gain from neighboring cells. We finally show how to maximize the system capacity through a secondary usage of the SFN resources by elastic traffic. The presented models are evaluated using numerical applications and further validated through network simulations.

In this paper, we study the performance of multi-cell OFDMA WiMAX systems, in both downlink and uplink. We calculate analytically the number of collisions when the number of users in each cell is known. We then calculate the QoS indicators (e.g., blocking rates, download time and bit error rates) taking into account the physical layer conditions (modulation, propagation and MIMO), the MAC layer techniques (HARQ and radio resource management algorithms) and the traffic characteristics, in a cross-layer approach. We finally evaluate the impact of using adaptive modulation and coding on the overall performance of the system. This analysis allows us to calculate the Erlang capacity of a WiMAX system. Our numerical applications then show how to choose the best admission control and modulation schemes that extend the Erlang capacity region.

The rapid growth in demand for video streaming applications is stressing the performance of wireless access networks. To alleviate congestion, vendors currently propose devices to be placed in the operator's network that transcode videos to a lower rate in order to reduce traffic volume in case of congestion. The devices are also able to cache popular videos, both to reduce the burden of transcoding and to alleviate backhaul load. The paper proposes a model of this augmented radio access network enabling an evaluation of the performance benefits for given transcoding and caching capacities. Our results show that a gain in cell capacity of 15% can be realized with moderate transcoding and cache capacities.

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; We consider in this paper an important Quality of Experience (QoE) indicator in mobile networks that is reneging of users due to impatience. We specifically consider a cell under heavy load conditions and compute the reneging probability by using a fluid limit analysis. By solving the fixed point equation, we obtain a new QoE perturbation metric quantifying the impact of reneging on the performance of the system. This metric is then used to devise a new pricing scheme accounting of reneging. We specifically propose several flavors of this pricing around the idea of having a flat rate for accessing the network and an elastic price related to the level of QoE perturbation induced by communications.

During the last years, energy efficiency of wireless networks arises as a dominating concept to answer the huge energy demand due to the increase of mobile traffic. Currently, a new direction appears with powering mobile base stations by renewable energy sources. While most of the studies in this direction are based on simulation or theory, this paper analyzes the usage of renewable energy in a realistic environment. Our study is based on a live scenario, where real traffic measurements of a major European mobile network operator are used. The effects of renewable energy allocation and base stations switching- off are evaluated in terms of on-grid energy saving and electric bill reduction. Moreover, a new algorithm that combines an in- telligent renewable energy allocation and a switch-off mechanism based on renewable energy generation, storage state and price of on-grid energy is proposed. Our results show that switching-off bases stations can achieve about 19 % energy demand reduction. Moreover, equipping base stations with renewable energy sources that generate 20 % of the total network energy demand can lead to 51 % reduction in the electric bill.

This paper presents statistical methods to enhance dynamic simulations in mobile networks. The aim is to perform reliable (unbiased) and fast evaluation of QoS indicators such as blocking and dropping rates. To do so, we adopt a trajectory splitting (TS) method that splits the path of the simulated stochastic process into multiple copies for determined configurations, thus focusing on configurations for which communication problems are likely to occur. We show that this method significantly reduces the variance of the estimators of both blocking and dropping probabilities, and hence reduces simulation times for the same precision. In a real network dynamic simulation, we propose an algorithm that automatically checks that the network has reached its steady state distribution and eliminates the bias due to the initial stabilization samples. We then isolate stations of interest with their most interfering neighbors and show that applying TS to these regions of interest leads to a very significant reduction of the simulation times.

In this paper, we determine the optimal CAC strategy in UMTS systems based on pricing. We investigate comparatively three connection admission control schemes, which are: (i) a measurement-based approach wherein a predictive mechanism is used to anticipate users' arrivals, (ii) a squeezing-based approach where lesser sensitive data flows see their SIR reduced to minimal predetermined values so as to accommodate higher priority flows and (iii) a plain CAC that accepts users simply upon resource availability and no priorities are implemented. This comparison is carried out using two pricing schemes, flat pricing and a service-based one where the user pays for what he gets. Our results show that the squeezing approach outperforms the other two with respect to both pricing schemes. As of the latter, service-based pricing yields higher revenue at the possible cost of increasing complexity.

International audience; —The major motivation behind this work is to optimize the sleep mode and transmit power level strategies in a small cell cluster in order to maximize the proposed energy efficiency metric. We study the virtual multiple input multiple output (MIMO) established with each base station in the cluster equipped with one transmit antenna and every user equipped with one receive antennas each. The downlink energy efficiency is analyzed taking into account the transmit power level as well as the implementation of sleep mode schemes. In our extensive simulations, we analyze and evaluate the performance of the virtual MIMO through zero-forcing schemes and the benefits of sleep mode schemes in small cell clusters. Our results show that for certain configurations of the system, implementing a virtual MIMO with several transmit antennas can be less energy efficient than a system with sleep mode using OFDMA with a single transmitting antenna for serving multiple users.

International audience; We study in this work user impatience and quantify its impact on the performance of mobile networks, notably LTE networks, in the presence of data flows experiencing heterogeneous radio conditions. We consider a dynamic user setting where users come to the system at different time instants and leave it after a finite duration, either after completion of their data transfers or earlier, at the expiry of some patience duration. We derive closed-form analytical expressions for the system stationary probability distribution, in general and for some particular distributions for the impatience duration and file size, and obtain several performance metrics such as system load and mean transfer times, taking into account the heterogeneity of users locations in the cell. Our numerical results quantify these metrics, as a function of the impatience rate, as well as the traffic region where the impatience impact becomes preponderant

Distributing Radio Resource Management (RRM) in heterogeneous wireless networks is an important research and development axis that aims at reducing network complexity, signaling, and processing load in heterogeneous environments. Performing decision-making involves incorporating cognitive capabilities into the mobiles such as sensing the environment and learning capabilities. This falls within the larger framework of cognitive radio (Mitola, 2000) and self-organizing networks (3GPP, 2008). In this context, RRM decision making can be delegated to mobiles by incorporating cognitive capabilities into mobile handsets, resulting in the reduction of signaling and processing burden. This may however result in inefficiencies such as those known as the “Tragedy of commons” (Hardin, 1968) that are inherent to equilibria in non-cooperative games. Due to the concern for efficiency, centralized network architectures and protocols keep being considered and being compared to decentralized ones. From the point of view of the network architecture, this implies the co-existence of network-centric and terminal-centric RRM schemes. Instead of taking part within the debate among the supporters of each solution, the authors propose a hybrid scheme where the wireless users are assisted in their decisions by the network that broadcasts aggregated load information (Elayoubi, 2010). At some system’s states, the network manager may impose his decisions on the network users. In other states, the mobiles may take autonomous actions in reaction to information sent by the network. Specifically, the authors derive analytically the utilities related to the Quality of Service (QoS) perceived by mobile users and develop a Bayesian framework to obtain the equilibria. They then analyze the performance of the proposed scheme in terms of achievable throughput (for both mobile terminals and the network) and evaluate the price of anarchy which measures how good the system performance is when users play selfishly instead of playing to achieve the social optimum (Johari, 2004). Numerical results illustrate the advantages of using the hybrid game framework in a network composed of HSDPA and 3G LTE system that serve streaming and elastic flows. Finally, this chapter addresses current questions regarding the integration of the proposed hybrid Stackelberg scheme in practical wireless systems, leading to a better understanding of actual cognitive radio gains.

This paper presents an extensive overview on an energy saving feature referred to as ‘site sleep mode’, designed for existing and future mobile broadband networks. In addition to providing a detailed understanding of the main concept, the paper also provides various studies and results to highlight potential savings, and emphasize some of the expected limitations. Since site measurements show that the energy consumption of base station sites is largely load-independent, this makes such a feature highly effective for reducing the energy consumption of mobile networks during hours of low traffic. After going through a number of different alternatives of the feature, this is applied to different network topologies, macro-only based networks, and a set of heterogeneous networks that employ the use of small cells in traffic hotspots. Results obtained through detailed case studies show that sleep mode can reduce the average daily energy consumption of a network by around 30%. This can be achieved while maintaining a predefined level of performance, used as a measure of comparing different scenarios.

A central objective in designing LTE networks was to provide a better quality of experience for the end user. One of the implemented enhancements is a direct connection between neighbouring eNodeBs through the X 2 interface. This interface enables mobility management and the transfer of the user's data in case of a handover. The aim of this paper is to provide an analytical model to dimension the X 2 link bandwidth under certain performance objectives. We take into account radio interface conditions in order to establish handover rates and we use the Kaufman-Roberts formula to compute the needed X 2 bandwidth. We also study the impact of traffic management schemes (admission control and QoS differentiation) and of transport protocols on X 2 dimensioning.

International audience; Our purpose in this paper is to obtain the \emph{exact distribution} of the number of buffer starvations within a sequence of $N$ consecutive packet arrivals. The buffer is modeled as an M/M/1 queue. When the buffer is empty, the service restarts after a certain amount of packets are \emph{prefetched}. With this goal, we propose two approaches, one of which is based on \emph{Ballot theorem}, and the other uses recursive equations. The Ballot theorem approach gives an explicit solution, but at the cost of the high complexity order in certain circumstances. The recursive approach, though not offering an explicit result, needs fewer computations. We further propose a fluid analysis of starvation probability on the file level, given the distribution of file size and the traffic intensity. The starvation probabilities of this paper have many potential applications. We apply them to optimize the quality of experience (QoE) of media streaming service, by exploiting the tradeoff between the start-up delay and the starvation.

This paper proposes two novel contributions: a fast statistical method for scheduling gain calculation is introduced, and we show how it can be combined with queuing theory and real network measurements in order to calculate the flow-level performance of a cellular network that uses Proportional Fair (PF) scheduling. A statistical method to evaluate the scheduling gain is proposed and a proof of its convergence is given. This method is three orders of magnitude faster than full system simulation. Based on these results, a queuing theory analysis is performed and is applied to the pedestrian A 3km/h channel model and LMMSE receiver. The evaluation uses drive tests measurements to reflect the realistic distribution of radio conditions. The derived flow-level performance of PF scheduling, including blocking rate, outage rate and flow throughput, is of major interest for network operators.