Network system designers need to understand the error performance of wireless mobile channels in order to improve the quality of communications by deploying better modulation and coding schemes, and better network architectures. It is also desirable to have an accurate and thoroughly reproducible error model, which would allow network designers to evaluate a protocol or algorithm and its variations in a controlled and repeatable way. However, the physical properties of radio propagation, and the diversities of error environments in a wireless medium, lead to complexity in modeling the error performance of wireless channels. This article surveys the error modeling methods of fading channels in wireless communications, and provides a novel user-requirement (researchers and designers) based approach to classify the existing wireless error models. FOURTH QUARTER 2003, VOLUME 5, NO. 2 www.comsoc.org/pubs/surveys ERROR MODELING SCHEMES FOR FADING CHANNELS IN WIRELESS COMMUNICATIONS: A SURVEY IEEE Communications Surveys & Tutorials • Fourth Quarter 20033 accurate enough to describe the performance of a real wireless mobile channel.Three main physical phenomenon affect radio propagation in a real-world scenario: reflection, diffraction, and scattering. When electromagnetic radiation reflects off objects or diffracts around objects, it can travel from the transmitter to the receiver over multiple paths, giving rise to multipath propagation [2]. This can result in fluctuations in the received signal's amplitude, phase, and angle of arrival, giving rise to multipath fading. System modeling and design, which mitigate the effects of fading, are usually challenging [1]. Therefore, error models of fading channels in wireless mobile communications are very helpful in designing and evaluating the performance of wireless networks and communication systems.The error performance of wireless channels is usually modeled by capturing the statistical nature of the interaction among reflected radio waves. The statistical calculations for Bit Error Rate (BER), which is generally used to characterize channel errors at the physical layer, is a well known practice. From the perspective of higher layers, network protocol developers and algorithm designers are interested in block errors (packet errors), since most of the higher-layer applications (running on top of link layers) exchange blocks of data between peers. For example, bit errors in a link-layer packet may result in the loss of the entire packet; a single packet loss within a message may lead to the loss of the entire message. Therefore, it is desirable to have accurate packet-level error models for wireless channels, which can be used by network protocol developers and network system engineers to simulate and analyze the end-to-end performance at the packet level. It has been observed empirically [3] that errors in wireless fading channels can be approximated by a two-state Markov process. In other words, a well designed channel may enter a state where bursty errors occu...

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Integrated Services (IntServ) and Differentiated Services (DiffServ) are two of the current approaches to provide Quality of Service (QoS) guarantees in the next generation Internet. IntServ aims at providing guarantees to end applications (individual connections) which gives rise to scalability issues in the core of the network. On the contrary, DiffServ is designed to provide QoS to aggregates, and does not suffer from scalability. It is therefore, believed that the combination of IntServ at the edge and DiffServ at the core will be able to provide QoS guarantees to end applications. 1, 2Although there have been several proposals on how to perform mapping of services between IntServ and DiffServ, there hasn't been any study to quantitatively show the level of QoS that can be achieved when the two networks are connected. The objective of this paper is to quantitatively demonstrate the QoS guarantees that can be obtained by end applications when IntServ is run over DiffServ. We have used goodput, drop ratio and non-conformant ratio of packets from the different services and the queue size of DiffServ router to determine the QoS obtained by packets belonging to different traffic classes.

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SUMMARYWith the convergence of wireless communication and IP-based networking technologies, future IP-based wireless networks are expected to support real-time multimedia. IP services over wireless networks (e.g. wireless access to Internet) enhance the mobility and flexibility of traditional IP network users. Wireless networks extend the current IP service infrastructure to a mix of transmission media, bandwidth, costs, coverage, and service agreements, requiring enhancements to the IP protocol layers in wireless networks. Furthermore, QoS provisioning is required at various layers of the IP protocol stack to guarantee different types of service requests, giving rise to issues related to cross-layer design methodology. This paper reviews issues and prevailing solutions to performance enhancements and QoS provisioning for IP services over mobile wireless networks from a layered view.