WLAN Throughput Performance - Research Paper Example

WLAN Throughput Performance ment of the Problem Throughput is defined as the fraction of the total channel capa that is used for data transmission (Bianchi, 535-547). Throughput efficiency is affected by several factors. Listed below are just some of the problems affecting WLAN throughput: Nominal bit rate downshifts with distance Due to path loss, the radio signal becomes weak and distorted. This signal degradation results in a downshift to a lower bit rate. This phenomenon allows the radio link to use simpler modulation scheme thus making it easier for the equipment to distinguish between digital zeroes and ones. Contention between multiple active users When there are multiple simultaneously active users transmitting data on the WLAN radio channel, the throughput decreases. This is because the users experience collision. These colliding parties must wait for a defined back off period before retransmitting. This results in loss of airtime thus affecting the system’s throughput. Interference Radio based WLAN are unregulated. Other products transmitting energy in the same frequency spectrum results in interference. For instance, microwave ovens can be a source of interference to a WLAN system. Most WLAN manufacturers design their products to account for this interference. Interference mostly arises from other access points (AP) on the same and adjacent radio channels. It can be mutual and harmful. In minimizing interference, different radio channels are used. Frequency hopping and other frequency optimization techniques are developing to help manage interference. Interoperability of wireless devices WLAN systems from different vendors may not be interoperable. This is because different technologies will not interoperate. For instance, a system based on spread spectrum frequency hopping technology will not communicate with another system based on spread spectrum direct sequence technology. Moreover, systems using direct frequency bands will not interoperate even if they employ the same technology. In addition to that, systems from different vendors may not interoperate even if they both employ the same technology. There are varieties of wireless applications. User demand and capacity are ever increasing. Telecommunication service providers are often faced with the challenge of providing better quality of service (QoS) to the end users. In this paper is the investigation on causes that result on degraded systems throughput performance. 2. Review of Related Works There are quite a number of researches that have studied the efficiency of the IEEE 802.11 protocol by investigating the maximum achievable throughput under various network configurations. The backoff mechanism has been analyzed and alternatives proposed to improve the performance of the existing standard mechanism. Bianchi provides a simple analytical model that computes saturation throughput performance assuming finite number of stations and ideal channel conditions (535-547). Wu et al. extends this model with a consideration of the frame retry limits which precisely predicts 802.11 DCF throughputs. However, no known work exists that considers finite load throughput of 802.11 DCF and that which considers protocol parameters such as timeouts (599-607). There are a number of studies on the performance of WLANs using the 802.11 MAC protocol. Some preliminary investigations on the voice capacity of the IEEE 802.11b network have been conducted in (Hole and Tobagi, 196-201) where they observed that in goo channel conditions, a higher number of voice users can be supported by using larger payload sizes. The use of theoretical framework for rate adaption to evaluate IEEE 802.11 is investigated in (Qiao, Choi and Shin, 278-292). The authors propose a computationally expensive dynamic programming approach to find the optional data rates that can be used for fairly simple wireless channel variation models with known probability of transitions from good to bad states and vice versa. They accomplished this by using a discrete Markov Chain. A link adaption strategy for IEEE 802.11b is provided in (Pavon and Choi, 1108-1113), where the frame lengths are classified into three broad categories: 0-100 bytes, 100-1000 bytes, and 1000-2400 bytes. An early investigation on the effect of payload size on throughput is conducted in (6). In this paper, the payload length is considered as an optimization parameter and a cross-layer scheme is proposed that jointly optimizes user’s throughput in IEEE 802.11a WLAN based on channel conditions. The theoretical formulation allows payload to be varied continuously over a wider range. A mathematical framework is then formulated to dynamically adapt the payload length to maximize the throughput for additive white Gaussian noise under different fading channels. 3. Hypothesis Statement. The throughput in WLAN is product and set-up dependent. The factors affecting throughput include the number of users, propagation factors such as distance and multipath difference, the type of WLAN system employed as well as the latency and bottlenecks on wireless portions of the LAN. The payload length can be considered as an optimization parameter. A cross-layer scheme that jointly optimizes user’s throughput in IEEE 802.11a LAN based on channel conditions. The payload can be varied continuously over a wider range. 4. Experiment and Data Collection Simulation Model of IEEE 802.11 A simulation model was developed using the ns-2 simulator to study the throughput, mean delay, and fairness performance of the IEEE 802.11b DCF protocol. To simplify the simulation model, consider a perfect radio propagation environment in which there is no transmission error due to interference ad noise on the system and no hidden and exposed stations problems. The following assumptions are made concerning the data traffic: Streams of data packets arriving at stations are modeled as independent Poisson processes with an aggregate mean packet generating rate greater than packets. Packets are of fixed length. Each station in the network has a large buffer, modeled as a buffer of infinite size, to store packets. A packet arriving at a station are uniformly destined to N-1 other stations in the network. Stations are arbitrarily spaced on the network within the transmission range. Network performance is studied under steady state conditions. Table 1: Parameters used in the simulation Parameter Values Bandwidth 11 Mbps Basic rate 2mbps SIFS 10𝝁s DIFS 50 𝝁s Slot time 20 𝝁s Traffic type UDP Application CBR RTS/CTS Off PHY modulation DSSS CWmin 31 CWmax 1023 Simulation time 50 seconds The table lists the parameter values used in the simulation. Each simulation run lasts for 50s. The observations collected during the transient period are not included in the final simulation results. The models built using ns-2 simulator were validated using empirical measurements from wireless laptops and access points for an IEEE 802.11b wireless LAN (Sarkar, 2005). A good match between ns-2 simulation results and empirical measurements validates the simulation model. 5. Results and Analysis It was observed that the network throughput decreases as the number of active stations for N=1 to 80 stations at 80% offered load. It was also observed that the network throughput under the ad hoc network was slightly greater than the infrastructure network especially or N>30 stations. Under both the ad hoc and infrastructure networks, the throughput is saturated at around  stations. The maximum achievable throughput is 4.4 Mbps for N=1 station at 80% offered load. This throughput is around 40% of the maximum theoretical bandwidth of 11 Mbps. The minimum throughput under the infrastructure network is 1.7 Mbps which is around 15.6% of the maximum bandwidth of 11 Mbps for N=70 stations at 80% offered load. However the minimum throughput under the ad hoc network is 2.9Mbps for N=80 stations at 80% offered load. The main conclusion we draw from the above results is that under the IEEE 802.11b WLAN deteriorates for N>10 stations, especially at medium to high offered traffics. This throughput deterioration is due to the wastage of transmission capacity in the backoff state of IEEE802.11.b protocol. 6. Conclusion. The results show that IEEE 802.11b does not perform well in terms of high throughput. For example, when the number of active users increases, throughput performance degrades significantly. Using simulation experiments, insight is gained into the performance of IEEE 802.11b WLAN under high traffic load conditions Works Cited Hole, Daniel and Fouad Tobagi. “Capacity of an IEEE 802.11b Wireless LANS Supporting VOIP”, in Proceedings of IEEE ICC, 2004, pp. 196 – 201. D. Qiao, S. Choi and K. G. Shin. “Goodput Analysis and Link Adaptation for IEEE 802.11a Wireless LANs”. IEEE Transactions on Mobile Computing. Vol. 1. No. 4, pp. 278-292. Bianchi, Gabriella.“Performance Analysis of the IEEE 802.11 Distributed Coordination Function”. IEEE Journal on Selected Areas in Communications. Vol. No. 3, 2000, pp. 535-547. H. Wu, Y. Peng, K. Long, J. Cheng and J. Ma. “Performance of Reliable Transport Protocol over IEEE 802.11 Wireless LAN: Analysis and Enhancement”, in Proceedings of IEEE INFOCOMM, Vol. 2, pp. 599-607. J. P. Pavon and S. Choi. “Link Adaptation Strategy for IEEE 802.11 WLAN via Received Signal Strength Measurement”, in Proceedings of IEEE ICC, 2003, pp. 1108-1113. P. Lettieri and M. B. Srivastava. “Adaptive Frame Length Control for Improving Wireless Link Throughput, Range and Engery Efficiency”, in INFOCOM, Vol. 2, 1998, pp. 564-571. J. G. Proakis. Digital Communications. New York, NY, McGraw-Hill Inc., third ed., 1995. A. Goldsmith and S. G. Chua, “Variable-rate variable-power M-QAM for fading channels,” IEEE Transaction on Communication., vol. 45, pp. 1218–1230. IEEE, “International Standard [for] Information Technology-Telecommunications and information exchange between systems-Local and metropolitan area networks-Specific Requirements- Part11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications,” IEEE 802.11-1999, 1999. IEEE, “Supplement to Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications: Highspeed Physical Layer in the 5 GHz Band,” IEEE Std. 802.11a-1999, 1999. IEEE, “Supplement to Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications: Higher Speed Physical Layer Extension in the 2.4 GHz Band,” IEEE Std. 802.11b-1999, 1999. IEEE, “Draft Supplement to Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications: Further Higher-Speed Physical Layer Extension in the 2.4 GHz Band,” IEEE 802.11g/D8.2, April 2003. IEEE, “Information technology Telecommunications and information exchange between systems Local and metropolitan area networks Specific requirements- Part 2: Logical Link Control,” ANSI/IEEE Std. 802.2, 1998. Daji Qiao, Sunghyun Choi, Amjad Soomro, and Kang G. Shin, "Energy-Efficient PCF Operation of IEEE 802.11a WLAN via Transmit Power Control," Elsevier Computer Networks (ComNet), vol. 42, no. 1, pp. 39-54, May 2003. Daji Qiao, Sunghyun Choi, and Kang G. Shin, "Goodput Analysis and Link Adaptation for IEEE 802.11a Wireless LANs," IEEE Trans. on Mobile Computing (TMC), vol. 1, no. 4, pp. 278-292, October-December 2002. S. McCreary and K. Claffy, “Trends in wide area IP traffic patterns- A view from Ames Internet Exchange,” ITC Specialist Seminar, 2000. Pang Q, Liew SC, Lee JYB, Leung VCM (2004) Performance evaluation of an adaptive backoff scheme for WLAN. Wirel Commun Mob Comput 4(8):867–879, December 9. Song N-O, Kwak B-J, Song J, Miller ME (2003) Enhancement of IEEE 802.11 distributed coordination function with exponential increase exponential decrease backoff algorithm. In: Proceedings of the 57th IEEE semiannual vehicular technology conference (VTC 2003-Spring), Jeju, April 2003. Banchs A, Perez X (2006) Distributed fair queuing in IEEE 802.11 wireless LAN. In: Proceedings of IEEE ICC 2002, New York, April 2006. Heusse M, Rousseau F, Guillier R, Duda A (2005) Idle sense: an optimal access method for high throughput and fairness in rate diverse wireless lans. In: SIGCOMM ’05: Proceedings of the 2005 conference on applications, technologies, architectures, and protocols for computer communications. ACM, New York, pp. 121–132 Calì F, Conti M, Gregori E (2000) Dynamic tuning of the ieee 802.11 protocol to achieve a theoretical throughput limit. IEEE/ACM Trans Netw 8(6):785–799 Bononi L, Conti M, Gregori E (2004) Runtime optimization of ieee 802.11 wireless lans performance. 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