PERFORMANCE ANALYSIS OF FRAME AGGREGATION BASED IEEE 802.11N WIRELESS LOCAL AREA NETWORK (WLAN)

ABSTRACT

The IEEE 802.11 Wireless Local Area Network (WLAN) standard was able to ease the communication difficulty by providing mobility and low cost of system deployment for its users. On the other hand, the WLAN has difficulty in meeting the optimum Quality of Service (QoS)demand for data applications. Consequently, a later variant of the amendment standard, IEEE 802.11n, came with improvement strategies. The introduction of frame aggregation, block acknowledgment and reverse direction protocol techniques at the Media Access Control (MAC) sub-layer of the Datalink layer reduced the overhead cost to an optimum value. This work analyzed the performance of MAC Service Data Unit (MSDU) frame aggregation technique at variable aggregation sizes and number of contending stations in an error-prone WLAN channel. The frame aggregation technique was selected for analysis based on its popularity as compared to other MAC improvement techniques. Firstly, an analytical approach that models the network based on discrete time Markov chain (DTMC) was developed  and  then  simulated  in  MATLAB  environment.  The  values  of  the  MSDU  frame aggregation sizes, the variable number of contending stations and  variable bit-error-rate (BER) values of the WLAN channel were chosen arbitrarily but within the practical range for a number of simulation cycles. Based on the generated results, it was observed that the MSDU aggregation size should not be increased beyond 46 for the various BER values of the channel considered for this work else the performance throughput would depreciate. This performance information is very resourceful for optimal design and implementation of frame aggregation technique in the WLAN network.

CHAPTER ONE

INTRODUCTION

1.1      Background

Wireless Local Area Network (WLAN) involves the connection of devices without the use of cables [1]. Although the origin of radio frequency based wireless networking can be traced back to the University of Hawaii’s ALOHANET research project in the 1970s, but it was until the IEEE 802.11 Wireless standard validated it officially in 1997 that it started recording very fast growth globally [2]. Prior to 1997, the demand for wireless networking was seldom met fully because of challenges like interoperability of products from various manufacturers, security in addition to the very low obtainable performance output compared to the then available 10 Mbps wired Ethernet standard [3]. The most obvious advantage of wireless networking is mobility [4,

5, 6]. Wireless networking relieved users of the restriction of being connected by physical cables which, of course, limits the users’ movement dramatically. More so, wireless networks typically have a great deal of flexibility, which can translate into rapid deployment [7, 8]. However, some of the limitations of the network include the fact that the speed of the network is constrained to the available bandwidth [9]. Also, security on the network poses a great challenge since the network transmissions are available to anyone within the range of the transmitter with the appropriate antenna [9].

The operation of WLAN can either be through Infrared (IR) propagation or Radio frequency (RF) propagation methods [9, 10]. The wavelength of the IR is slightly longer than that of the visible light and the link is limited to distances under 15 m [9]. The diffused infrared optical propagation channel is suitable for indoor setup and does not require line-of-sight (LOS) [9]. However, it is seldom used in outdoor topology because it is easily blocked by walls, partitions

and other office construction; instead, the RF propagation method is commonly used and can penetrate these barriers and offers wider coverage range [4]. RF propagation method can be deployed in both indoor and outdoor scenario with functional frequencies of 2 GHz and 5 GHz in the unlicensed Industrial Scientific and Medical (ISM) frequency band [10, 11]. The ISM bands are frequency bands that are set aside for communication equipment that support industrial, scientific and medical services.

The WLAN makes use of a contention-based protocol known as Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) [5,  6].  This protocol ensures that  the possibility of collision in the network is reduced significantly using control frames. It  is very suitable in transmission of asynchronous frames. Asynchronous frame transmission involves orderly and sequential  frame  exchanges  where  each  frame  transmission commences  at  the  end  of  the previous transmission. This is to avoid a situation whereby simultaneous exchanges are experienced in a time slot. There are three signaling frame types in IEEE WLAN, viz. Data, Control and Management frames [9].

This work analyzed the performance of frame aggregation improvement technique of IEEE

802.11n network at variable aggregation sizes and contending stations for various bit-error-rate (BER) values of the WLAN error-prone channel. The network was modeled based on discrete time Markov chain (DTMC) and then simulated in MATLAB environment. Performance results were generated and inferences were drawn based on observation.

1.2      Problem Statement

The  Station  (STA)  that  has  successfully  seized  the  communication  channel  through  the

CSMA/CA process communicates by exchanging frames during a period of time known as

Transmission Opportunity (TXOP) [12,13]. TXOP is an interval of time when a particular Quality of Service (QoS) STA has the right to initiate frame exchange sequences onto the Wireless Medium (WM) [12]. The process of allowing stations to exchange one pair of frame at a time and then re-start the process of competing for the channel again to resume sending the remaining frames is a characterized inefficiency of the IEEE WLAN legacy network [14]. The IEEE 802.11n standard allows the exchange of multiple frames for the TXOP when the channel is seized. Several sub-frames are concatenated together to form an aggregate frame. The aggregate frame reduces the overhead cost that would have been incurred if the sub-frames were to be transmitted independently. This is a characterized improvement in the IEEE 802.11 WLAN standard. However, this  improvement  could  be  marred  if  the  specification  for  the  optimal aggregation value is not adhered to in the application. This work analyzed the performance of the IEEE 802.11n WLAN network by varying the aggregation size of the MSDU frames and the number of contending stations in an error-prone WLAN channel.

1.3      Objectives

The main objective is to determine the effect of these variable system parameters in terms of performance throughput and average access delay in the network. The optimal values of these parameters would be obtained in this work. The result  of the analysis would assist  in the optimization of the network design parameters.

1.4      Scope

The work is centered on the Media Access Control (MAC) sub-layer of the Data Link layer in the Open System Interconnection (OSI) reference model. The work analysis is carried out only on the frame aggregation improvement technique that is employable at this layer. The reason for choosing frame aggregation technique is basically due to its popularity. The functional area of

the analysis implemented in the study resides only on the network performance. The approach adopted in the work is limited to a non-real time analysis only.

1.5      Methodology

The approach adopted for this work is unique. The literature review on the current state of art in the IEEE WLAN works was studied. A physical architecture that comprised of 160 Endpoint stations and one Access point station was adopted and a physical model that represented the network was realized. The specifications for deployment of IEEE 802.11n Wireless LAN base on the IEEE standards were adhered to. There were assumptions made in order to realize the modeled network according to these specifications. Some analytical expressions were generated from these assumptions based on Markov’s queuing principle. These expressions were converted into simulation model using MATLAB simulation software. The values of the variable frame aggregation sizes, the variable number of contending stations and variable bit-error-rate (BER) of the error-prone WLAN channel were chosen arbitrarily but within the practical range for the number of simulation cycles. Performance results were generated from the simulation and were used to draw the inference for the work.

1.6      Thesis Outline

This work is organized into five chapters. This chapter one introduced the WLAN, the problem statement, the objectives, the significant, the methodology and the scope. Chapter two fully describes the IEEE 802.11 WLAN technology and the current research contributions from other researchers in the area. More emphasis was made on works that treated IEEE 802.11n MAC improvement techniques. Chapter three modeled the IEEE 802.11n WLAN network. The model is  analytical.  The  analytical  approach  was  based  on  Markov’s  queuing  principle  and  the simulation  approach  involved  program  scriptingusing  MATLAB  simulation  software.  In

chapterfour, the model was simulated and validated. Results were generated and analyzed. Then conclusion and recommendation were drawn in chapter five.

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