As of today, wireless sensor networks (WSNs) are regularly deployed to monitor physical phenomena. This is made possible by the collection of time-stamped data building on synchronized sensor clocks. Some applications benefit from a temporary deployment of the network. This is for instance the case for acoustics calibration of a concert hall using connected microphones. In this case, the clock synchronization protocol must converge fast and in a bounded time. In this paper, we propose TAYLORS, a distributed and thus robust synchronization protocol for WSN that offers a fast bounded convergence and that keeps a stable clock even in dynamic settings. TAYLORS combines both max-consensus at initialization and average-consensus over the long term. This work provides as well a novel mathematical model to derive a worst-case bound on convergence that is leveraged to motivate the design of TAYLORS. Experimental results show that the proposed solution is simple, fast and suitable for very basic micro-controllers.

Avionics Full-DupleX (AFDX) is a switched Ethernet-based network used in modern commercial airplanes for the transmission of command and control avionics flows. These critical flows require deterministic guarantees leading to a lightly loaded network. Aircraft manufacturers envision to carry additional non avionics flows (i.e. video, audio, service) to take advantage of the spare bandwidth. However, it is then compulsory to preserve the real-time guarantees of avionics flows in terms of bounded jitter at the transmitter output and of bounded end-to-end latency. Depending on the type of additional traffic, Quality of Service (QoS) end-to-end guarantees may be offered to the additional flows of lower criticality in terms of reduced delay or bounded jitter for instance. These guarantees can be ensured by scheduling policies at transmitter and switch level. However, an important safety-related constraint is the asynchronous design of avionics distributed systems that prohibits the use of a network-wide synchronization of end systems and switches. Thus, time-triggered networking such as emerging Time-Triggered Ethernet (TTEthernet) or Time-Sensitive Networking (TSN) cannot be leveraged. This paper underlines the benefits of only scheduling flows at the transmitter, which is compatible with the asynchronous safety constraint of avionics systems. We show that it is possible to build a table schedule that carries both critical avionics flows and additional video flows that meet their timing and bandwidth allocation constraints. Therefore, we design scheduling strategies for efficient distribution of flows in the table scheduling whose performance is compared to the optimal schedule minimizing the emission lag of additional flows. Proposed heuristics are constructed such as to favor the network responsiveness for avionics flows thanks to slot over-provisioning. Extensive results on an A350 AFDX industrial configuration show that for a transmitter load of up to 70% of the available bandwidth, the uniform allocation heuristic provides a performance close to optimal in terms of minimum emission lag for additional flows, so offering a practical configuration heuristic to industry.

Time Sensitive Networking (TSN) is gaining interest in the critical embedded networking community thanks to the various Quality of Service (QoS) mechanisms that can be rolled out to offer different levels of determinism to flows in a switched Ethernet network. Among these standards, limited jitter flows can benefit from the Time Aware Shaper (TAS) which requires the deployment of the IEEE802.1AS synchronization. Indeed, TAS assumes a global time with a bounded drift between any two nodes. In this paper, we derive a refined and general mathematical model that offers upper and lower bounds on the worst-case precision that can be applied to different Ethernet technologies. Results for 100Base-T and 1000Base-T technologies are given. Both simulations and empirical measurements validate the almost two times closer upper bound we obtain compared to the state-of-the-art model.

This paper addresses the problem of scheduling real-time wireless flows under dynamic network conditions and general traffic patterns. The objective is to maximize the fraction of packets of each flow to be delivered within their deadlines, referred to as timely-throughput. The scheduling problem under restrictive frame-based traffic models or greedy maximal scheduling schemes like LDF has been extensively studied so far, but scheduling algorithms to provide deadline guarantees on packet delivery for general traffic under dynamic network conditions are very limited. We propose two scheduling algorithms using deep reinforcement learning approach to optimize timely-throughput for general traffic in dynamic wireless networks: RL-Centralized scheduling algorithm and RL-Decentralized scheduling algo-rithm. Specifically, we formulate the centralized scheduling problem as a Markov Decision Process (MDP) and a multi-environments double deep Q-network (ME-DDQN) structure is proposed to adapt to the dynamic network conditions. The decentralized scheduling problem is formulated as a Partially Observable Markov Decision Process (POMDP) and an expert-apprentice centralized training and decentralized execution (EA-CTDE) structure is designed to accelerate the training speed and achieve the optimal timely-throughput. The extensive results show that the proposed scheduling algorithms converge fast and adapt well to network dynamics with superior performance compared to baseline policies. Finally, experimental tests confirm simulation results and also show that the proposed algorithms are feasible in practice on resource limited platforms.

In this paper, we address the problem of building adaptive network coding coefficients under dynamic network conditions (e.g., varying link quality and changing number of relays). In existing linear network coding solutions including deterministic network coding and random linear network coding, coding coefficients are set by a heuristic or randomly chosen from a Galois field with equal probability, which can not adapt to dynamic network conditions with good decoding performance. We propose INCdeep, an adaptive Intelligent Network Coding with Deep Reinforcement Learning. Specifically, we formulate a coding coefficients selection problem where network variations can be automatically and continuously expressed as the state transitions of a Markov decision process (MDP). The key advantage is that INCdeep is able to learn and dynamically adjust the coding coefficients for the source node and each relay node according to ongoing network conditions, instead of randomly. The results show that INCdeep has generalization ability that adapts well in dynamic scenarios where link quality is changing fast, and it converges fast in the training process. Compared with the benchmark coding algorithms, INCdeep shows superior performance, including higher decoding probability and lower coding overhead through simulations and experiments.

A network with reliable and rapid communication is critical for Unmanned Aerial Vehicles (UAVs). Flying Ad Hoc Networks (FANETs) consisting of UAVs is a new paradigm of wireless communication . However, the highly dynamic topology of FANETs and limited energy of UAVs have brought great challenges to the routing design of FANETs. It is difficult for existing routing protocols for Mobile Ad Hoc Networks (MANETs) and Vehicular Ad Hoc Networks (VANETs) to adapt the high dynamics of FANETs. Moreover, few of existing routing protocols simultaneously meet the requirement of low delay and low energy consumption of FANETs. This paper proposes a novel Q-learning based Multi-objective optimization Routing protocol for FANETs to provide low-delay and low-energy service guarantees. Most of existing Q-learning based protocols use a fixed value for the Q-learning parameters. In contrast, Q-learning parameters can be adaptively adjusted in the proposed protocol to adapt to the high dynamics of FANETs. In addition, a new exploration and exploitation mechanism is also proposed to explore some undiscovered potential optimal routing path while exploiting the acquired knowledge. Instead of using past neighbor relationships, the proposed method re-estimates neighbor relationships in the routing decision process to select the more reliable next hop. Simulation results show that the proposed method can provide higher packet arrival ratio, lower delay and energy consumption than existing good performing Q-learning based routing method.

AFDX is the standard switched Ethernet solution for the transmission of avionics flows. Today's AFDX deployments in commercial aircrafts are lightly loaded to ensure the determinism of control and command operations. Manufacturers envision to take advantage of the remaining AFDX bandwidth to transmit additional non avionics flows (video, audio, service). These flows must not compromise the in-time transmission of avionics ones: constraints on jitter at source end system and end-to-end latency have to be insured for each avionics flow. In this paper, we investigate the scheduling of avionics and additional flows, mainly at the end system level. We show that an event-triggered strategy is better than a time-triggered one for additional flows at source level, but it might compromise the jitter constraint of avionics flows and increase the end-to-end latency of additional ones. We consider two time-triggered scheduling strategies, i.e. an optimal one and a simpler one based on a heuristic. We show that the later one performs nearly as well as the former one and that, for both of them, the difference with an event-triggered strategy at source level is limited and can be statically bounded.

We present PCach, a smartphone application designed to relieve the congestion in cellular networks resulting from the exponential growth of mobile data traffic. The basic idea underlying PCach is simple: use Wi-Fi to proactively cache content on the smartphone's memory, which otherwise would have been delivered through the cellular network during the next Wi-Fi coverage time gap. However, it leads to several challenging questions, including how much mobile data actually flows through cellular networks, how much data can be precached, and when and what to pre-cache. By analysing the extensive MACACO measurement dataset, our analysis shows that the median smartphone user transfers 15% of her data via the cellular network and that up to 80% of it could be pre-cached via Wi-Fi. From our empirical observations, we introduce an algorithm that can run stand-alone on off-the-shelf smartphones and predict with good accuracy when and what to pre-cache.

As wireless sensor networks become more ubiquitous in the world, the need for lightweight, resilient time synchronization protocols is apparent. Wireless nodes' internal clocks are subject to drift over time due to manufacturing imperfections and environmental changes. While various protocols have been introduced that attempt to correct for this drift, they each have their own peculiarities and issues. This paper presents a new protocol, the Sticking Heartbeat Aperture Resynchronization Protocol (SHARP), that reduces synchronization error and resolves shortcomings of existing protocols. We have implemented and compared SHARP to two existing (and noteworthy) time synchronization protocols, Reference Broadcast Synchronization (RBS) and Simple Synchronization Protocol (SISP), on Atmel ATMega328p based microcontroller platforms with IEEE 802.15.4 Xbee radio modules. We show that SHARP exhibits a higher level of synchronization than SISP (which in turn exhibited much better performance than RBS), while requiring significantly fewer messages.

The SImple Synchronization Protocol (SISP) has been designed for tiny sensors to offer a wireless synchronization service to the network. SISP is completely distributed with a flat architecture. Nodes broadcast a SYNC message periodically that contains the value of their view of a shared clock counter. Every time a SYNC message is received, nodes update their shared clock by averaging it with the clock value embedded in the message. This protocol converges in practice very well, and requires a small amount of energy as SYNC messages can be sent every second only. Moreover, computations are basic, perfectly fitting the tiny sensor platforms needed for the Internet of Things. Its distributed operations enable the network to adjust seamlessly to the appearance or disappearance of other nodes. This paper concentrates on the convergence analysis of this promising protocol. Convergence time and synchronization accuracy are determined analytically, by simulations and by experimenting a real sensor platform. All results show that this protocol offers an accuracy in the order of a few tens of microseconds. Moreover, our analytical derivations capture very well an upper bound on the synchronization accuracy.

Wireless networks have become a very attractive solution for soft real-time data transport in the industry. For such technologies to carry real-time traffic, reliable bounds on end-to-end communication delays have to be ascertained to warrant a proper system behavior. As for legacy wired embedded and real-time networks, two main wireless multiple access methods can be leveraged: one is time division multiple access (TDMA), which follows a time-triggered paradigm, and the other is carrier sense multiple access with collision avoidance (CSMA/CA), which follows an event-triggered paradigm. This paper proposes an analytical comparison of the time behavior of two representative TDMA and CSMA/CA protocols in terms of the worst-case end-to-end delay. This worst-case delay is expressed in a probabilistic manner because our analytical framework captures the versatility of the wireless medium. Analytical delay bounds are obtained from delay distributions, which are compared to fine-grained simulation results. Exhibited study cases show that TDMA can offer smaller or larger worst-case bounds than CSMA/CA depending on its settings.

With the world population becoming increasingly urban and the multiplication of mega cities, urban leaders have responded with plans calling for so called smart cities relying on instantaneous access to information using mobile devices for an intelligent management of resources. Coupled with the advent of the smartphone as the main platform for accessing the Internet, this has created the conditions for the looming wireless bandwidth crunch.

Emerging applications of Ultra-Wide Band (UWB) combine low to medium rate communications with positioning capabilities allowing centimeter level accuracy in ranging. For positioning systems employing UWB radios, time-based schemes provide very good accuracy due to the high time resolution of UWB signals. These time-based positioning systems rely on measurements of travel times of signal between nodes allowing to estimate the distance between nodes. The standard IEEE 802.15.4a-2007 propose TWR and SDS-TWR time-based protocols for ranging purpose. However, the accuracy of TWR is quite poor due to the effects of clock skews. SDS-TWR mitigates the clock skew error at the expenses of the number of message exchanges, which is increased. In this work, we present a novel approach for accurately estimating the ToF in UWB taking into account the clock skew between nodes while minimising the number of exchanged messages. Experimentations were carried out in our Open Source Framework, which enables fast prototyping of protocols based on an UWB Physical Layer.

Wireless networks have become a very attractive solution for soft real-time data transport in the industry. For such technologies to carry real-time traffic, reliable bounds on end-to-end communication delays have to be ascertained to warrant a proper system behavior. As for legacy wired embedded and real-time networks, two main wireless multiple access methods can be leveraged: (i) time division multiple access (TDMA), which follows a time-triggered paradigm and (ii) Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA), which follows an event-triggered paradigm. This paper proposes an analytical comparison of the time behavior of two representative TDMA and CSMA/CA protocols in terms of worst-case end-to-end delay. This worst-case delay is expressed in a probabilistic manner because our analytical framework captures the versatility of the wireless medium. Analytical delay bounds are obtained from delay distributions, which are compared to fine-grained simulation results. Exhibited study cases show that TDMA can offer smaller or larger worst-case bounds than CSMA/CA depending on its settings.

This paper presents a simple and effective method to study the spectral and energy efficiency (SE-EE) trade-off in cellular networks, an issue that has attracted significant recent interest in the wireless community. The proposed theoretical framework is based on an optimal radio resource allocation of transmit power and bandwidth for the downlink direction, applicable for an orthogonal cellular network. The analysis is initially focused on a single cell scenario, for which in addition to the solution of the main SE-EE optimization problem, it is proved that a traffic repartition scheme can also be adopted as a way to simplify this approach. By exploiting this interesting result along with properties of stochastic geometry, this work is extended to a more challenging multicell environment, where interference is shown to play an essential role and for this reason several interference reduction techniques are investigated. Special attention is also given to the case of low signal-to-noise ratio (SNR) and a way to evaluate the upper bound on EE in this regime is provided. This methodology leads to tractable analytical results under certain common channel properties, and thus allows the study of various models without the need for demanding system-level simulations.

Recent civil airborne platforms are produced using Integrated Modular Avionics (IMA). IMA promotes both sharing of execution and communication resources by the avionics applications. Designs following IMA decrease the weight of avionics equipment and improve the whole system scalability. However, the price to pay for these benefits is an increase of the system's complexity, triggering a challenging system integration process. Central to this integration step are the timing requirements of avionics applications: the system integrator has to find a mapping of applications and communications on the available target architecture (processing modules, networks, etc.) such as end-to-end delay constraints are met. These challenges stress the need for a tool capable of evaluating different integration choices in the early design stages of IMA. In this paper, we present and formalize the problem of spatial and temporal integration of an IMA system. Then, we focus on the temporal allocation problem which is critical to ensure a proper timely behavior of the system. Two main properties are presented to ensure perfect data transmission for hard real-time flows. To quantify the quality of a set of valid temporal allocations, CPM utilization and communication robustness performance criteria are defined. We show on an example that both criteria are antagonist and that they can be leveraged to choose an allocation that either improves the system computing performance or the robustness of the network.

Recent modular avionics architectures have been designed to share computation and communication resources. However, such an approach creates new challenges to master the temporal properties of avionics applications. In the context of IMA (Integrated Modular Avionics), it is crucial to investigate the performance gains that future integration platforms and software will propose. This paper brings to light the impact of spatial and temporal integration choices on the communication performance (e.g. message loss rate, latencies, ...). The conclusion of this investigation is that it is necessary to conduct a thorough modeling and simulation study of an IMA architecture integrating several applications during its early design stages.

The flexibility of wireless connectivity is appealing in the context of industrial networks. This paper discusses the use of a wireless protocol to interconnect remotely located fieldbuses. The focus of this paper is to analyze the feasibility and design issues related to this type of hybrid network architecture. Therefore, we concentrate on deriving appropriate bridging strategies for a network topology composed of remotely located CAN buses interconnected through a wireless local area network following the IEEE802.11g protocol. Using this very simple and cost-effective architecture, we show in this study that by intelligently leveraging the features of CAN and IEEE802.11g in the interconnection policies employed, the missed deadlines can be limited for the CAN frames carried by the wireless network.

In this paper, we argue that the ability to accurately spot random and social relationships in dynamic networks is essential to network applications that rely on human routines, such as, e.g., opportunistic routing. We thus propose a strategy to analyze users' interactions in mobile networks where users act according to their interests and activity dynamics. Our strategy, named Random rElationship ClASsifier sTrategy (RECAST), allows classifying users' wireless interactions, separating random interactions from different kinds of social ties. To that end, RECAST observes how the real system differs from an equivalent one where entities' decisions are completely random. We evaluate the effectiveness of the RECAST classification on real-world user contact datasets collected in diverse networking contexts. Our analysis unveils significant differences among the dynamics of users' wireless interactions in the datasets, which we leverage to unveil the impact of social ties on opportunistic routing.

In this paper, we propose an auction-based cooperative sensing protocol for secondary users in cognitive networks. The proposed auction mechanism is based on a novel modified Vickrey auction with a three dimensional bid, that accounts for detection gains as well as for virtual currency gains. We present a formal proof to show that the proposed three dimensional bidding mechanism preserves the truthfulness property of the classic Vickrey auction. The cooperative auction is combined with a prioritized access scheme to increase the efficiency and to reduce the response time for the coalition formation procedure. Our auction-based cooperative sensing mechanism can be easily applied to different network scenarios, by defining specific utility functions. The proposed cooperative sensing auctioning mechanism is illustrated for both downlink and uplink. Our simulation results show that users' cooperation is incentivized by the proposed algorithm, which leads to significant detection gains for the downlink and the uplink scenarios, with a more efficient energy expenditure.

In this work we examine data delivery in dynamic wireless ad hoc networks that exchange packets opportunistically. Legacy mobile ad hoc network (MANET) protocols send packets along a predetermined path between a source and a destination. Node mobility, however, may create network partitions and a multi-hop link may not be present at the onset. Such node mobility may instead be leveraged to create an asynchronous path between a source and destination enabling opportunistic message exchange. In this work we propose an analytic model for this data exchange by defining a node's probability to forward packets to an encountered node. Drawing on results from mobility studies, we derive the statistics on the packet exchange and packet delivery performance for opportunistic networks. This model is validated for several simulation scenarios. The work provides a foundation for a one-to-one performance comparison of existing opportunistic forwarding protocols.

One of the most powerful ways to achieve transmission reliability over wireless links is to employ efficient coding techniques. This paper investigates the performance of a transmission over a relay channel where information is protected by two layers of coding. In the first layer, transmission reliability is ensured by fountain coding at the source. The second layer incorporates network coding at the relay node. Thus, fountain coded packets are re-encoded at the relay in order to increase packet diversity and reduce energy consumption. Performance of the transmission is measured by the total number of transmissions needed until the message is successfully decoded at the destination. We show through both analytical derivations and simulations that adding network coding capabilities at the relay optimizes system resource consumption. When the source uses a random linear fountain code, the proposed two-layer encoding becomes more powerful as it reduces the transmission rate over the direct link between the source and the destination.

SUMMARY Recent advances in information theory and networking, e.g. aggregation, network coding or rateless codes, have significantly modified data dissemination in wireless networks. These new paradigms create new threats for security such as pollution attacks and denial of services (DoS). These attacks exploit the difficulty to authenticate data in such contexts. The particular case of xor network coding is considered herein. We investigate different strategies based on message authentication codes algorithms (MACs) to thwart these attacks. Yet, classical MAC designs are not compatible with the linear combination of network coding. Fortunately, MACs based on universal hash functions (UHFs) match nicely the needs of network coding: some of these functions are linear h(x1⊕x2) = h(x1)⊕h(x2). To demonstrate their efficiency, we consider the case of wireless sensor networks (WSNs). Although these functions can drastically reduce the energy consumption of authentication (up to 68% gain over the classical designs is observed), they increase the threat of DoS. Indeed, an adversary can disrupt all communications by polluting few messages. To overcome this problem, a group testing algorithm is introduced for authentication resulting in a complexity linear in the number of attacks. The energy consumption is analyzed for cross‐point and butterfly network topologies with respect to the possible attack scenarios. The results highlight the trade‐offs between energy efficiency, authentication and the effective throughput for the different MAC modes. Copyright © 2011 John Wiley & Sons, Ltd.

This paper concentrates on the proper use of fountain codes for the transmission of sporadic data in a wireless sensor network (WSN). Fountain codes offer great perspectives for the self-organization of WSNs: they self adapt to the channel error rate without control packets. Deploying fountain codes in a WSN raises two problems. First, the size of the data transmitted by a sensor is small in comparison to the size usually considered with fountain codes. Second, WSNs mostly rely on multi-hop transmissions. It implies a non null transmission duration for the end-to-end acknowledgement of the reception. During this period of time, the source is still transmitting useless packets, creating a specific overhead we define as the overflow. This paper brings the overflow problem to light and analyses its impact on the network performance. Our work can be viewed as the networking counterpart of the results presented by Pakzad et al. at ISIT 2005 applied to WSNs.

This paper concentrates on characterizing energy, latency and capacity trade-offs in multi-hop wireless ad-hoc networks. Therefore, a multiobjective framework is proposed to derive the Pareto-optimal set of solutions with respect to these three criteria. The work presented in this paper assumes a linear network where transmission powers and relay positions are optimization variables. We study the asymptotic state where the distance between source and destination is very high such that the number of hops tends to infinite. Two types of traffic are considered in the following. First, low rate traffic is analyzed by characterizing the multiobjective performance of a single packet transmission using an interference free multi-hop relaying strategy. Second, a continuous flow of packets from a unique source is considered. In the first case, we show an important theorem which states that all Pareto optimal solutions with respect to delay and energy metrics provide the same target SNR at the receiver side. In the second case, our analytical results highlight how the energy/delay Pareto front moves when considering a capacity constraint and the optimal re-use factor is derived.

During the last decade, many works were devoted to improving the performance of relaying techniques in ad hoc networks. One promising approach consists in allowing the relay nodes to cooperate, thus using spatial diversity to increase the capacity of the system. However, this approach introduces an overhead in terms of information exchange, increasing the complexity of the receivers. A simpler way of exploiting spatial diversity is referred to as opportunistic routing. In this scheme, a cluster of nodes still serves as relay candidates but only a single node in the cluster forwards the packet. This paper proposes a thorough analysis of opportunistic routing efficiency under different realistic radio channel conditions. The study aims at finding the best trade-off between two objectives: energy and latency minimizations, under a hard reliability constraint. We derive an optimal bound, namely, the Pareto front of the related optimization problem, which offers a good insight into the benefits of opportunistic routing compared with classical multi- hop routing.

During the last decade, many works were devoted to improving the performance of relaying techniques in ad hoc networks. One promising approach consists in allowing the relay nodes to cooperate, thus using spatial diversity to increase the capacity of the system. However, this approach introduces an overhead in terms of information exchange, increasing the complexity of the receivers. A simpler way of exploiting spatial diversity is referred to as opportunistic routing. In this scheme, a cluster of nodes still serves as relay candidates but only a single node in the cluster forwards the packet. In this paper, we put forward an analytical framework to optimize the opportunistic communication scheme in order to minimize the energy consumption. Meanwhile, the optimizations of node density and the transmission power are analyzed for different ranges of relay candidates in Rayleigh block fading and additive white gaussian noise (AWGN) channels. In the energy consumption viewpoint, the analyses indicate that the opportunistic communication is more efficient in Rayleigh block fading channel than that in AWGN channel.

Several softwares have been developed for computer-aided design of radio networks. The first constitutive element of such a tool is the propagation modelling algorithm. The second is the planning process providing positions and setup of access points. The last one concerning the frequency channel allocation problem (FAP) is the focus of this paper. Many works devoted to this problem exploit a graph-based modelling that leads to an under-constrained problem as interference between mobile nodes are not taken into account. In this paper a new QoS-based FAP criterion is formulated. This QoS criterion measures the overall throughput taking downlink interference into account. We show on an example that our FAP model outperforms usual graph-based FAP approaches concerning the effective SINR obtained at mobile nodes. Results are based on realistic simulations exploiting a simulator called WILDE (Wireless Lan DEsign) and implementing the MR-FDPF propagation algorithm.

This paper describes an automatic wireless LAN access points planning approach based on a multicriteria modelling and solving. A realistic and efficient wLAN planning approach can not only assess usual objectives based on radio coverage. It has to further implement a Quality of Service (QoS) constraint. In this work, a QoS criterion is defined as the mean available bandwidth per user, derived from a Markov-based performance evaluation model of the medium access control (MAC) layer behavior. Optimizing both coverage and QoS objectives results in finding the optimal trade-off between these concurrent criteria. Rather than optimizing a weighted sum of the optimization criteria that provides a single solution, it is herein proposed to develop a dedicated multicriteria search algorithm. Its main feature is to provide several solutions, each one representing a peculiar tradeoff between the objectives. The planning process estimates for each solution the optimal number of APs and their placement. The AP's coverage is estimated with a powerful multi-resolution radio propagation simulator previously described. This paper presents results for a QoS oriented planning process providing a predefined minimum per-user throughput. The example provided herein applies for 200 users distributed over a 12600 m2building floor.

This paper proposes an automatic base station planning approach. This approach does not only try to assess usual objectives such as radio coverage, but further implements a quality of service (QoS) constraint. This criterion is here defined as the mean available bandwidth per user. Its computation takes the medium access control (MAC) layer behavior, the multiple bit rates of IEEE 802.11b and the coverage area of each access point (AP) into account. A Markov chain is used to evaluate the available bandwidth of each cell independently. This is sensible because a non-overlapping criterion between cells is used during the planning phase to avoid interference between adjacent cells. The planning process estimates an optimal number of APs and their placement minimizing an aggregate criterion using a Tabu meta-heuristic. The AP's coverage is estimated with a powerful multi-resolution radio propagation simulator previously described. This paper presents results for a QoS oriented planning process providing a predefined minimum peruser throughput. The example provided herein applies for 100 users distributed over a 12600 m2building floor