Simulation of Small-Scale Fading in Mobile Channel Models for Next-Generation Wireless Communications

Simulation of Small-Scale Fading in Mobile Channel Models for Next-Generation Wireless Communications

Stelios A. Mitilineos (National Center for Scientific Research, “Demokritos,” Greece), Christos N. Capsalis (National Technical University of Athens, Greece) and Stelios C.A. Thomopoulos (National Center for Scientific Research, “Demokritos,” Greece)
DOI: 10.4018/978-1-60566-108-7.ch015
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Small-scale fading strongly affects the performance of a radio link; therefore radio channel simulation tools and models are broadly being used in order to evaluate the impact of fading. Furthermore, channel simulation tools and models are considered to be of utmost importance for efficient design and development of new products and services for Next Generation (Wireless) Networks (NGNs and NGWNs). In this chapter, a brief description of the most popular and broadly accepted mobile radio channel models and simulation techniques is given, mainly with respect to small-scale fading. In addition, certain research results on radio channel simulation are presented. The authors hope that the information provided herein will help researchers to acquire an insight to small-scale fading simulation techniques, which will be useful for a solid understanding of the underlying physical layer properties of NGWNs.
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I. Introduction

According to the ITU definition (ITU, 2004), a Next Generation Network (NGN) is principally an heterogeneous network. NGNs are packet and IP-based networks, able of providing services (such as navigation or telecommunications services) using multiple broadband transport technologies, while service-related functions are independent from the underlying transport technologies. A user of a NGN enjoys different services from different providers seamlessly, anytime, anywhere (ubiquitous computing – ubiquitous communications). From a business-oriented point of view, NGNs will allow unrestricted access by users to different service providers; a specification that is expected to bring revolutionary effects to business models and functionality of all Information and Communication Technology (ICT) enterprises. One of these effects is the already noticed unification of business sectors that were separated until now, like fixed and mobile telephony, internet and entertainment. From the user point of view, this means that she will be able of watching a streaming-video movie or placing a transatlantic call through a unique internet provider, or watching the weather forecast and hear her favourite songs from her mobile phone on the way to work. Furthermore, NGNs will naturally comply with all current and future regulatory requirements, regarding e.g. emergency communications (E-112 or E-911 for E.U. and U.S.A. respectively), or security and privacy/ethical issues, etc.

The heterogeneity of NGNs consists in services as well as physical networks. NGNs will offer a wide range of services, from relatively simple voice telephony and data transfer, to more demanding applications like streaming video, virtual private networks, public network computing or unified messaging. Furthermore, several futuristic services have been proposed like interactive and location-based gaming, distributed virtual reality, remote home/office management etc. The ultimate goal is nowadays considered to be the full integration of navigation and communications networks in order to provide exotic new services to end users (Ruggieri, 2006). On the other hand, as long as physical networks are concerned, NGNs will comprise of lines ranging from simple PSTN to DSL broadband in wired cases, and from 2G to 4G cellular or WLAN, WiMAX, Wireless Sensor Networks, and other more exotic ones like interplanetary internet (Akan 2004), in wireless cases. This means that NGNs will be capable of seamlessly internetworking through legacy and broadband networks and will be characterized by generalized mobility. So far, the only means of achieving these goals is considered to be an all-IP approach, i.e. using the IP protocol in order to interconnect the most diverse devices and networks; therefore NGNs are often referred to all-IP networks as well, while the IPv6 protocol is expected to significantly contribute towards this direction (Dixit, 2006). At the same time, the most attractive physical layer means of implementing NGNs is via wireless infrastructure and/or ad-hoc networks (Next Generation Wireless Networks, NGWNs) in conjunction with gigabit-per-second order throughput wired infrastructures. Even in the case of wired NGNs, digital content is expected to be delivered to the end user via mobile handheld devices (mobile phones, palmtops, VoIP wireless phones etc.).

Key Terms in this Chapter

Small Scale Fading: Severe signal strength fluctuations within distances in the order of wavelength.

Simulation: Artificial Reality, i.e. the research field whose intention is to mimic one or more attributes of reality.

Smart Antennas: Antenna arrays that are capable of automatically controling each element’s gain and phase, thus delivering optimal or sub-optimal radiation patterns with respect to a desired evaluation criterion.

Geometric Channel Models: Channel models based on abstract geometric characteristics of the propagation environment.

Empirical Channel Models: Channel models based on in-situ channel measurements.

Frequency Selective Fading: A type of small scale fading where different frequency signal components therefore experience decorelated fading; corresponds to the case where the signal bandwidth is larger than the channel coherence bandwidth.

Mobile Channel: A wireless communications propagation description, referring to mobile receivers and/or transmitters.

Deterministic Channel Models: Channel models based on (usually digital) architectural plans or topographical maps of the propagation environment.

Frequency Flat Fading: A type of small scale fading where all frequency signal components experience the same magnitude of fading; corresponds to the case where the signal bandwidth is smaller than the channel coherence bandwidth.

Statistical Channel Models: Channel models based on given probability density functions of channel characteristics.

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