Due to faster deployment and lower cost of wireless local loop (WLL) infrastructure as compared to a wired one, worldwide roll-out of WLL service has been highly anticipated. Most of WLL systems deployed so far belong to narrowband systems mainly aimed at providing voice service. These systems can be used as a bypass of wire-line local loop in dense areas and as an extension of existing telephone network in remote areas. In recent years, media-rich content of Internet has put speed pressure on the local loop. Application of WLL systems has been extended to broadband services to meet the need,. | Wireless Local Loops Theory and Applications Peter Stavroulakis Copyright 2001 John Wiley Sons Ltd ISBNs 0-471-49846-7 Hardback 0-470-84187-7 Electronic 2 Propagation Models for Wireless Local Loops Dongsoo Har and Howard H. Xia Introduction Due to faster deployment and lower cost of wireless local loop WLL infrastructure as compared to a wired one worldwide roll-out of WLL service has been highly anticipated. Most of WLL systems deployed so far belong to narrowband systems mainly aimed at providing voice service. These systems can be used as a bypass of wire-line local loop in dense areas and as an extension of existing telephone network in remote areas. In recent years media-rich content of Internet has put speed pressure on the local loop. Application of WLL systems has been extended to broadband services to meet the need contending with ISDN Asymmetrical Digital Subscriber Line ADSL and cable TV. It is critical to understand the propagation characteristics of radio signal in the WLL environment to improve system economies of WLL services. In order to predict path loss in wireless systems signal variation over distance is typically expressed in terms of an inverse power law with a statistical shadowing component that is obtained after averaging out the fast-fading effects. Specifically the radio signal received at a receiver from a base station at a distance R can be written down as where represents the shadow effect and y is the path loss exponent. In typical land-mobile radio environments is found to be a zero-mean Gaussian random variable with a standard deviation of 8 dB. Range dependence of path loss can also be expressed as an intercept-slope relationship in dB scale as L dB Zi 10y log R where I is an intercept taken at a unit distance. The size of a cell in general varies according to propagation environment and traffic density. Macrocell path loss models 1-4 are typically used for large cells with low traffic density. The prediction models 2 5-10
