Network densification and millimeter-wave technologies are key enablers to fulfill the capacity and data rate requirements of the fifth generation (5G) of mobile networks. In this context, designing low-complexity policies with local observations, yet able to adapt the user association with respect to the global network state and to the network dynamics is a challenge. In fact, the frameworks proposed in literature require continuous access to global network information and to recompute the association when the radio environment changes. With the complexity associated to such an approach, these solutions are not well suited to dense 5G networks. In this paper, we address this issue by designing a scalable and flexible algorithm for user association based on multi-agent reinforcement learning. In this approach, users act as independent agents that, based on their local observations only, learn to autonomously coordinate their actions in order to optimize the network sum-rate. Since there is no direct information exchange among the agents, we also limit the signaling overhead. Simulation results show that the proposed algorithm is able to adapt to (fast) changes of radio environment, thus providing large sum-rate gain in comparison to state-of-the-art solutions.

Hybridation between ray-based deterministic propagation modelling and statistical components is viewed as a promising solution to assess the performance of outdoor small-cell network designs or allocation techniques. In the solution presented in this paper, the main properties of the propagation channel (i.e. the specular paths, and the blockage by large objects) are simulated from the 3D geographical data and the ray-based model, while the effect of small or dynamic in- street objects, like vehicles and human bodies, can be appropriately reproduced by a stochastic procedure. A new feature of the solution consists in the creation of random clusters of human bodies in the surrounding of the users (the impact of the user body itself was previously introduced in the hybrid model as a stochastic factor). The application and interest of the new feature is illustrated in a radio access 60-GHz small-cell scenario, where small-cells are installed on lampposts and users are distributed in the street. The blockage by the human bodies affects the cell selection and beam orientation; the degradation of the service coverage is evaluated based on the signal-to-noise ratio (SINR) and for various human crowd densities.

Advanced radio channel modeling continues to be of great interest in order to facilitate innovation and pursue performance prediction of wireless networks; in particular, dual-polarized antenna systems for 4.5 and 5G require models that properly capture the complex phenomenon of depolarization. Accordingly, we present and validate a ray-based model for dual-polarized channel characterization. We present the model and describe the measurement campaign used to obtain field data for evaluation. We also compare our approach to the largely used WINNER-based stochastic model, and discuss the impact of antennas and diffuse scattering in the prediction of depolarization. The paper indicates that a 3D space-time deterministic propagation model must be used if a well correlated channel model, both in LoS and NLoS conditions, is required to assess a system performance.

Efficient radio spectrum utilization and low energy consumption in mobile devices are essential in developing next generation wireless networks. This paper presents a new medium access control (MAC) mechanism to enhance spectrum efficiency and reduce energy consumption in a wireless ad hoc network. A set of coordinator nodes, distributed in the network area, periodically schedule contention-free time slots for all data transmissions/receptions in the network, based on transmission requests from source nodes. Adjacent coordinators exchange scheduling information to effectively increase spatial spectrum reuse and avoid transmission collisions. Moreover, the proposed MAC scheme allows a node to put its radio interface into a sleep mode when it is not transmitting/receiving a packet, in order to reduce energy consumption. Simulation results demonstrate that the proposed scheme achieves substantially higher throughput and has significantly lower energy consumption in comparison with existing schemes.

This paper investigates the possible gain in heterogeneous network power consumption when dynamically switching on or off small-cells depending on user traffic. Using a ray-based propagation model complemented with a space- and time-variant traffic model, the quality of service and power consumption of a large-scale realistic LTE heterogeneous network is assessed. The power consumption of the small-cell layer can be drastically reduced outside busy hours without compromising users' quality of service. A 29% gain in daily energy consumption is obtained in the studied scenario compared to the always-on scenario.

One major bottleneck in the practical implementation of received signal strength (RSS) based indoor localization systems is the extensive deployment efforts required to construct the radio maps through fingerprinting. In this paper, we aim to design an indoor localization scheme that can be directly employed without building a full fingerprinted radio map of the indoor environment. By accumulating the information of localized RSSs, this scheme can also simultaneously construct the radio map with limited calibration. To design this scheme, we employ a source data set that possesses the same spatial correlation of the RSSs in the indoor environment of interest. The knowledge of this data set is then transferred to a limited number of calibration fingerprints and one or several RSS observations with unknown locations, in order to perform direct localization of these observations using manifold alignment. We test two different source data sets, namely a simulated radio propagation map and the environment's plan coordinates. For moving users, we exploit the correlation of their observations to improve their localization accuracy. The online testing in two indoor environments shows that the plan coordinates achieve better results than the simulated radio maps, and a negligible degradation with 70-85 percent reduction in the calibration load.

Wireless Sensor Networks are increasingly employed as unobtrusive and infrastructureless networks in both indoor and outdoor environments. In order to reach their full potential, a number of key issues, such as localization and topology control, need to be addressed. However, the performance of these protocols is significantly impacted by the assumptions made about the underlying physical layer. Realistic radio propagation models, used as the physical layer models, provide a more accurate evaluation of protocols when performing network simulations. This paper therefore analyzes the performance of a number of propagation models in a real indoor environment. Specifically, the Unit Disk, Lognormal Shadowing, Volcano Indoor Multi-Wall and WINNER II Stochastic channel models are investigated. Field measurements are performed in an office building to empirically determine the channel parameters and evaluate the models based on various error metrics. A network connectivity analysis is also performed using Monte Carlo simulations to demonstrate the impact the choice of the physical layer model has on the network backbone construction. This paper shows that the Volcano Indoor Multi-Wall and WINNER II Stochastic channel models provide better estimate of the actual path losses in an indoor environment. It also shows that the errors introduced can cause connectivity algorithms to significantly under-estimate (sometimes up to a 14 times under-estimation) the power requirements necessary to guarantee a connected network.

Mobile operators need to deploy dense LTE-Advanced small-cell networks in the next few years to cope with the growing mobile data traffic demand. Prediction models and mobile network design tools need to radically evolve to allow a proper evaluation, and then design and optimization of cost-efficient heterogeneous networks. This paper introduces a comprehensive solution for cost and performance analysis. A ray-based propagation model and a 3D traffic mapping tool are used to feed a 3D LTE-A simulator. Then, a case study of a North American city addresses the impact of modeling tools on outdoor small-cell deployment costs. The analysis highlights some applicative results: The identification of hotspots within macro-cells enabled by the presented tool shows a significant impact on deployment costs (18% less than with only per-sector information). A 2D modeling approach overestimates macro offload, leading to an under- designed small-cell network that could be prevented thanks to 3D tools. This qualitative comparison is useful to understand the significance of modeling tools for cost and performance analysis of future heterogeneous networks.

This paper analyzes LTE-A Heterogeneous Network (HetNet) performance in terms of usual Quality of Service (QoS), energy efficiency and Electromagnetic Field (EMF) exposure. The main objective is to identify network deployment rules that would allow achieving optimal performance from multiple key indicators taking into account a realistic forecast of wireless data traffic demand growth. This study relies on simulation results obtained with an innovative network coverage and analysis tool taking into account both uplink (UL) and downlink (DL). In particular, EMF exposure sources resulting respectively from the base-station and the User Equipment (UE) transmissions are jointly analyzed. The main outcome is the characterization of HetNet with different small-cell deployment strategies against a realistic network traffic growth over a period of five years. EMF exposure, which is of growing importance, is in particular reduced with small-cell densification as long as the user traffic demand remains well under the network capacity.

Energy efficiency is an important performance measure of wireless network protocols, particularly for battery-powered mobile devices such as smartphones. This paper presents a new energy efficient medium access control (MAC) scheme for fully connected wireless ad hoc networks. The proposed scheme reduces energy consumption by putting radio interfaces in the sleep state periodically and by reducing transmission collisions, which results in high throughput and low packet transmission delay. The proposed MAC scheme can also address energy saving in realtime traffics, which require very low packet transmission delay. An analytical model is established to evaluate the performance of the proposed MAC scheme. Analytical and simulation results demonstrate that the proposed scheme has significantly lower power consumption, achieves substantially higher throughput, and has lower packet transmission delay in comparison with existing power saving MAC protocols.

Indoor small-cell (Femto) technology recently gained attention due to its potential benefits for wireless carriers (significant capacity off load and extension of coverage at low cost). These indoor small-cell base stations are seen as enablers of heterogeneous networks in urban areas. However, there are still hard technical challenges to be addressed (e.g. the optimization of the interference management) and deployment strategies to be planned out (e.g. open or closed access mode, spectrum usage, etc.). Consequently, reliable simulations are necessary in the perspective of massive femto-cell deployments leading to heterogeneous topologies. A novel solution is introduced and exploited in this paper. It relies on a suite of simulation tools including generation of random 3D femto-cell deployments in real environments, realistic path-loss predictions using a ray-based model and a 3D downlink performance analysis (i.e. considering all floors) of heterogeneous LTE networks in terms of coverage, macro offload and throughput. A first study demonstrates a significant macro offload and power consumption reduction in a realistic dense corporate FAP deployment. Then, a second study shows the large growth of indoor capacity enabled by dense FAP deployments but also the coverage degradation for non-subscribers when closed-access mode is used.

We propose to analyze the impact of vehicular scattering on both individual users and global throughput of a LTE heterogeneous network. The studied network consists of a real world hexagonal configuration with 7 three-sector Macro Base Stations and 15 added Small Cells. Propagation modeling is site-specific and the main contribution of this paper relies on the introduction of channel dynamics due to vehicular traffic flow crossing radio links. Connection losses and throughput degradations due to vehicle passing are observed for individual users. The global throughput gain achieved by offloading Macro Base Stations is reduced but remains attractive.

LTE and LTE-Advanced have introduced complex system features to improve system capacity. Although exhaustively simulated, it often happens that the simulated capacity figures differ from the actual performance seen in the field. This paper explores the combination of real measurements from LTE devices and realistic propagation models to generate coverage maps that are truly representative of radio performance. The paper illustrates the proposed methodology by forecasting the gain of inter-cell interference mitigation implemented in a UE device.

This paper proposes an efficient two-stage channel quantization and feedback scheme for the downlink limited-feedback network multiple-input multiple-output (MIMO) system. In the first stage, the users report their best set of base-station antenna and physical resource block combinations, and the base-stations schedule the best user for each antenna in each resource block. The scheduled users are then polled in the second stage to feedback their quantized channel vectors. This paper proposes an analytical framework to show that, under a total feedback budget of B bits, the number of bits assigned to the second feedback stage should scale as log B, and in quantizing channel vectors from different base-stations, each user should allocate feedback bits in proportion to the channel magnitudes in dB scale. Under these optimized bit allocations, the overall sum rate of the system is shown to scale double-logarithmically with B, linearly with the total number of antennas, and logarithmically with transmit power, thus achieving both multiuser diversity and spatial multiplexing gains under limited feedback. Finally, realistic wireless propagation model of an urban small-cell deployment is used to show that the proposed scheme can approach the performance of a network MIMO system with full channel state information with only modest amount of channel feedback.

The placement of the access points (APs) has a significant impact on the wireless system performance, especially for irregular heterogeneous networks with hierarchical APs such as macro/micro base-stations, pico-stations, and femto-stations. Traditional system modeling and optimization are based on the regular 2D hexagonal cellular topology and a set of predefined large-scale propagation models, which is highly abstract and may be inaccurate. This paper considers the AP placement optimization problem in realistic deployment environments, where radio-wave propagation characteristics are accurately modeled using ray-tracing techniques. Toward this end, this paper proposes a novel concept of area proportional fairness utility for the entire network under a given user geographic distribution, and proposes an iterative method to optimize the placement of the APs for utility improvement while taking into account the mutual interference between the APs. The significant benefit of the placement optimization is shown in a numerical experiment conducted in a realistic Chicago downtown topology, where placement optimization is shown to improve the sum rate by up to 40%.

This paper presents a propagation model generating time series of large-scale power variations for small-cell radio links intersected by vehicular traffic. The model combines stochastic processing and geometric computation. For each road crossing a link, a two-state process parameterized by mobility statistics represents the obstruction status. When the status is set to obstructed, a fluctuation pattern is generated. Based on previously published measurements, both mobility statistics and time series results are validated through the comparison of respectively inter-obstruction duration distributions and outage probabilities. The proposed model avoids resource-consuming iterative propagation prediction while providing realistic and frequency adaptive results.

One major bottleneck in the practical implementation of received signal strength (RSS) based indoor localization systems is the extensive deployment load required to construct radio maps through fingerprinting. Several works aimed to employ radio propagation models as alternative to fingerprinting but the different sources of inaccuracies in the generation of these models result in high localization errors. In this paper, we propose an indoor localization scheme that can be directly deployed and employed without building a full radio map of the indoor environment. The proposed scheme employs the information from a radio propagation simulator and limited number of calibration measurements to perform direct localization using manifold alignment. For moving users, we exploit the correlation of their reported observations to improve the localization accuracy. The online performance evaluation shows that our algorithm achieves localization errors in the order of 2.5 to 3 m with as low as 15% - 30 % of the complete fingerprinting load.

As wireless cellular networks are facing both a rapid growth of traffic demand and, in some countries, a higher public concern about field exposure, the wireless carriers are seriously considering radio network topology evolution. Deployment of small- or micro-cells, possibly as a complement to the macrocell layout, should offer high local capacity along with a reduced transmit power (at both the downlink and uplink). Network simulations assess the performance of such deployment scenarios, providing the required outcomes for elaboration of optimal strategies, engineering rules and business models. This paper presents an original suite of simulation tools based on advanced propagation models and 3-dimensional calculation of the signal-to-interference ratio (meaning calculation into the streets and into each building floor over the study area) for realistic analysis of heterogeneous macro and small-cell LTE networks in terms of coverage, spectral efficiency and total throughput. A dense urban scenario is analyzed, where the usual macro deployment scheme is completed with almost-uniformly distributed small-cells. The present study characterizes the promising improvements but also some challenging aspects of small-cell network deployments.

This paper proposes an efficient two-stage beamforming and scheduling algorithm for the limited-feedback cooperative multi-point (CoMP) systems. The system includes multiple base-stations cooperatively transmitting data to a pool of users, which share a rate-limited feedback channel for sending back the channel state information (CSI). The feedback mechanism is divided into two stages that are used separately for scheduling and beamforming. In the first stage, the users report their best channel gain from all the base-station antennas and the basestations schedule the best user for each of their antennas. The scheduled users are then polled in the second stage to feedback their quantized channel vectors. The paper proposes an analytical framework to derive the bit allocation between the two feedback stages and the bit allocation for quantizing each user's CSI. For a total number of feedback bits B, it is shown that the number of bits assigned to the second feedback stage should scale as log B. Furthermore, in quantizing channel vectors from different base-stations, each user should allocate its feedback budget in proportion to the logarithm of the corresponding channel gains. These bit allocation are then used to show that the overall system performance scales double-logarithmically with B and logarithmically with the transmit SNR. The paper further presents several numerical results to show that, in comparison with other beamforming-scheduling algorithms in the literature, the proposed scheme provides a consistent improvement in downlink sum rate and network utility. Such improvements, in particular, are achieved in spite of a significant reduction in the beamforming-scheduling computational complexity, which makes the proposed scheme an attractive solution for practical system implementations.

A time-variant wireless stochastic channel model for femtocell configurations is proposed in this paper. The idea is to introduce time-variant components into geometry-based stochastic channel predictions. The proposed model aims at feeding system-level simulations with realistic non-stationary characteristics for wireless systems serving indoor areas. The model formulation is generic, and has been adjusted to static line-of-sight links in corporate environments at frequencies around 2GHz.

Two different indoor-to-outdoor path-loss models are proposed in this paper: an analytical formula derived for link-level and system-level simulations in heterogeneous radio networks, and a ray-tracing based model providing deterministic path-loss predictions, helpful for precise radio analysis or radio-planning tasks. The models were elaborated from CW measurements collected around a large set of indoor transmitter situations at frequency 2.1GHz. They were elaborated for simulation of useful and interfering signals in the context of femtocell deployments.

The effect of an arbitrary indoor infrastructure environment on the performance of a wireless multihop network is investigated. To this end, an accurate channel modeling tool based on 3D ray tracing is used first to evaluate the signal strength in different areas of the environment. Then, a discrete event simulator is applied to examine the performance of the network with two classes of routing protocols: traditional vs. opportunistic. It is shown that for an indoor environment, opportunistic routing performs better based on the obtained results, with respect to throughput, delay and delivery ratio.

Recent radio systems (3G, DVB-T/H) present a wideband bandwidth possibly enlarging the capacity of the networks. The systems are interference-limited and thus an accurate radio network planning requires a refined characterization of the interference levels. A French research project called Semafor has been set up to investigate this characterization by means of two tools. First a hardware equipment is able to detect low interference levels by making use of antenna arrays and powerful algorithms. Second a coverage simulation tool is used. It is based on a propagation model able to estimate accurately large range echoes. System parameters like the interference level and SINR for DVB are simulated and validated by extensive measurement campaigns realized in the project with sophisticated testbeds.

Siradel takes part in a French research project (RNRT) named Rhodes that has been initialised in 2003 to experiment a joint deployment of a UMTS/TDD and WLAN network. Siradel coordinates the workpackage dealing with the multisystem (WLAN, UMTS) radio planning. Thus radio propagation prediction tools have been designed in the frame of that project to deal with complex multienvironments (indoor, outdoor, mountainous). The presented propagation modelling is used to simulate the coverage of the hybrid network and determine the cell boundaries. The paper presents the distinct solutions to predict the propagation either from outdoor UMTS base stations or from in-building WLAN transmitters. The focus is set on the terrain representation of both environments. The outdoor map data and the 3D building model have to be perfectly adjusted in a common coordinate system. This is indeed a key feature to achieve a full analysis of the hybrid network. A measurement campaign has been realised to calibrate and validate the propagation prediction tools. The synthesised results are presented here.

The design of a deterministic radio propagation model adapted to built-up areas is a tedious problem when considering the needs of radio planners, i.e. great accuracy and reasonable processing time. In that perspective, an innovative model for micro-cells has been developed by the French company Siradel. It combines two usual modeling methods: the multiple knife-edge approximation to take into account the propagation above rooftops and 2D ray-tracing to predict lateral interactions. Radio grid coverage and comparisons with experimental data are presented to prove the pertinence of the model.

Indoor wireless local networks (WLAN) development in the millimetre band gives new perspectives, which are very promising in terms of announced data rate and offered services. Nevertheless strong free space attenuation as well as pieces of furniture and wall attenuations result in difficult propagation conditions. A French research project (RNRT COMMINDOR) has been set up to study and design new high data rate (155 Mbit/s) radiocommunication systems at 60 GHz in an indoor environment. SIRADEL takes part in this project by modelling the propagation phenomenon thanks to a ray-tracing tool associated to the Uniform Theory of Diffraction (UTD). Simulations are then compared to measurements realised within the framework of this project by the LCST Laboratory of INSA Rennes. The good behaviour of the propagation model is analysed for LOS and NLOS situations.