Access Mechanisms to IEEE 802.11 WiFi Networks and Their Analytical Model 

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Capacity Evaluation of a Wi Cell

For the WiFi, the major problem is to get the residual and eective throughput a user can expect from its wireless access point. The WiFi standard is based on the well-known Carrier Sense Multiple Access with Collision Avoidance (CSMA / CA) mechanism which manages the multiple access to an access point by dierent users. This is in done in a distributed manner.
Each user must verify that the channel is free during a given amount of time (called Inter-Frame Space (IFS)) before transmitting. If the channel is busy, the user must wait again for a random time (known as Backo time) to try a retransmission. Even when a station succeeds to transmit on a channel that is supposed « free », a collision can still occur. For example, if two stations connected to the same access point have by coincidence waited the same random time. This stochastic nature of the mechanism makes it dicult to get an accurate estimate of the actual capacity of the wireless cell. One could argue that if we do not want to take a risk, it is enough to oversize the network by introducing a large number of wireless access points to cover a given area. Unfortunately, this solution feasible at high cost with wire can lead to strong interferences between cells in wireless. In addition to the extent that CSMA / CA is used, the problem of the Exposed node will appear very quickly with an abundance of access points. Thus it is essential to evaluate precisely and accurately as possible the capacity of a wireless cell, in order to optimize the use of the radio resource available for each access point.

Qos Parameters for WiFi

The original access mechanism of the WiFi standard, based on CSMA / CA was not designed initially to support quality of service. Thus there was no dierentiation mechanism between ows from dierent kinds of services. This motivated the development of an amendment to the original standard which allows giving priority to certain types of ows (e.g. for voice services, streaming, etc). Unfortunately it required the introduction of dierent backo times for each ow, which complicates the task of evaluation of the cell capacity. In addition, there are numerous parameters available within the Quality of Service (QoS) enhanced protocol that allow a network administrator to dynamically manage the dierentiation between the services. However due to the high complexity of the protocol and its random nature, it is not possible at rst sight to dene the in uence of each parameter on the effective capacity available to each service. This evaluation can only be done through incremental simulations or analytical models.

Thesis Goals and Contributions

To evaluate the capacity of aWiFi cell, a way to model the access mechanism of the radio resource was needed. Many models appeared shortly after the appearance of the standard. However, each model made some assumptions for purposes of simplication. The most common assumptions were the saturation of the channel and the approximation of an ideal channel. The channel can be considered saturated if a user always has a packet to transmit, or in other words that the buer of the user is never empty. This assumption is often justied as it can be considered the worst case scenario which will not lead to overestimated capacity. However, this will obviously lead to an oversized network which is not desirable. In addition, this assumption is itself dicult to justify if we consider that a user rarely has a packet to transmit continuously. For instance, the trac of a user viewing web pages has been the subject of intense research and often modeled for simplicity has a series of burst period followed by silence period maybe due to the fact that the user takes time to read the required information that has been downloaded and does not interact continuously. A second approximation often assumed in the existing models considers the channel as ideal. Thus, each transmitted packet arrives without error with a probability equal to 1 if it does not encounter a collision. It is well known that the wireless medium is far from being error free. If for the wired network, the BER is around 10􀀀14, wireless networks have a BER of around 10􀀀7 or about 10 million times more errors. So once again we claim that this is a rough assumption.
Finally, many models do not consider the enhanced access mechanism of the WiFi which supports QoS.
In this thesis we propose to model the access mechanism of a WiFi’s cell with QoS support and without the aforementioned approximations ofsaturation and error-free channel. Indeed we consider the possibility that the buer of the user can be empty with a given probability. Moreover, even if the user was granted access to the medium, there is non zero probability that an error occurs. For theses purposes we extend an existing model known as Bianchi’s model [16] which was further extended to accommodate the QoS enhancement by Kong [48]. The new model allows for more accurate dimensioning of a WiFi network. Moreover, the modeling of the QoS standard capability allows a better understanding of the in uence of each parameter of the protocol. Thus our model may be considered as a tool for calibrating parameters of the network to give specic quality of service to dierent users.

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Table of contents :

List of Figures
List of Tables
1 Introduction 
1.1 « Ubiquitous Wireless »
1.2 Challenges
1.2.1 Capacity Evaluation of a Wi Cell
1.2.2 Qos Parameters for WiFi
1.3 Thesis Goals and Contributions
1.3.1 Stochastic Model for Wi Access
1.3.2 Femtocell
1.4 Thesis Outline I Background and state of the ART
2 Access Mechanisms to IEEE 802.11 WiFi Networks and Their Analytical Model 
2.1 MAC of the IEEE 802.11 and 802.11e description
2.1.1 introduction
2.1.2 Distributed Coordination Function
2.1.3 Enhanced Distributed Coordinated Access function
2.2 State of The ART
2.2.1 Seminal Models
2.2.2 DCF models
2.2.3 EDCA models
2.2.4 Summary Table
3 Frequency Allocation to Femtocell 
3.1 Introduction
3.2 Description
3.2.1 Access Control
3.3 Challenges
3.3.1 Femtocell to Macrocell Downlink Interference
3.3.2 Macrocell to Femtocell Uplink Interference
3.3.3 Femtocell to Femtocell Uplink Interference
3.3.4 Femtocell to Femtocell Downlink Interference
3.4 Existing Allocation Scheme
3.4.1 Introduction
3.4.2 Experimental Results in the Literature
3.4.3 Cross-Tier Allocation Scheme
3.4.4 Co-tier allocation scheme
4 Stochastic Model of EDCA 
4.1 System Model
4.1.1 Four Dimensional Markov Chain
4.1.2 Markov Chain
4.1.3 Characteristic of Our Model: the Unsaturated Mode .
4.1.4 Transition probabilities
4.1.5 Probability in steady state and equation systems
4.2 Throughput derivation
4.3 Delay derivation
5 Frequency allocation to femtocell a double frequency reuse assignment scheme 
5.1 Double Frequency Reuse: A novel Channel Allocation Scheme for Femtocells
5.2 Femtocell’s Channel Selection
5.3 Other Fundamentals Parameters
5.3.1 Radio Resource Granularity
5.3.2 Femtocell Transmission Power
5.3.3 Adjacent Channel Interference
6 Analytical Results of the Stochastic Model of EDCA 
6.1 Equations System
6.2 Unsaturated mode and error prone channel eects on the throughput
6.3 AIFS and CWmin dierentiation mechanism
6.3.1 AIFS mechanism
6.3.2 CWmin mechanism
6.4 Some delay results
7 Simulation and Results for Femtocell Channels Reuse 
7.1 Performance derivation
7.2 Simulation Parameters
7.2.1 Propagation Models
7.3 Macrocell-Femtocell Simulator
7.4 Results
7.4.1 Introduction
7.4.2 Femtocell RSS Performance
7.4.3 Femtocell SINR Performance
7.4.4 Eect of the Transmission Power
8 Conclusion 


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