Research Article A Comprehensive Propagation Prediction Model Comprising Microfacet Based Scattering and Probability Based Coverage Optimization Algorithm A. S. M. Zahid Kausar, Ahmed Wasif Reza, Lau Chun Wo, and Harikrishnan Ramiah Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia Correspondence should be addressed to Ahmed Wasif Reza; awreza98@yahoo.com Received 13 February 2014; Revised 13 July 2014; Accepted 13 July 2014; Published 18 August 2014 Academic Editor: Nirupam Chakraborti Copyright © 2014 A. S. M. Zahid Kausar et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Although ray tracing based propagation prediction models are popular for indoor radio wave propagation characterization, most of them do not provide an integrated approach for achieving the goal of optimum coverage, which is a key part in designing wireless network. In this paper, an accelerated technique of three-dimensional ray tracing is presented, where rough surface scattering is included for making a more accurate ray tracing technique. Here, the rough surface scattering is represented by microfacets, for which it becomes possible to compute the scattering feld in all possible directions. New optimization techniques, like dual quadrant skipping (DQS) and closest object fnder (COF), are implemented for fast characterization of wireless communications and making the ray tracing technique more efcient. In conjunction with the ray tracing technique, probability based coverage optimization algorithm is accumulated with the ray tracing technique to make a compact solution for indoor propagation prediction. Te proposed technique decreases the ray tracing time by omitting the unnecessary objects for ray tracing using the DQS technique and by decreasing the ray-object intersection time using the COF technique. On the other hand, the coverage optimization algorithm is based on probability theory, which fnds out the minimum number of transmitters and their corresponding positions in order to achieve optimal indoor wireless coverage. Both of the space and time complexities of the proposed algorithm surpass the existing algorithms. For the verifcation of the proposed ray tracing technique and coverage algorithm, detailed simulation results for diferent scattering factors, diferent antenna types, and diferent operating frequencies are presented. Furthermore, the proposed technique is verifed by the experimental results. 1. Introduction Nowadays, indoor wireless communication becomes more and more popular in communication feld. Because of increasing demand in this feld, an efective propagation prediction technique and optimized coverage algorithm are required in order to support the demand by using the minimum number of transmitters (  s) and at the same time achieving the maximum indoor wireless coverage. Tough there are a number of existing research works based on ray tracing for propagation prediction [1–7], most of them have not mentioned anything about the coverage. Terefore, researchers are still in need of an efcient and integrated method, which can serve for propagation prediction and coverage optimization. Te main problem for the ray tracing based propagation prediction model is the ray-object intersection test. Tis test consumed the most time and resources in a ray tracing method [8, 9]. Intersection test is performed every time afer a new ray is generated for fnding whether there is a ray-object intersection or not. Hence, if all objects participate in this test, the ray tracing time consumed will be extremely high. To accelerate the ray tracing technique, various methods, such as angular sectoring [10], KD-tree, octree, quadtree [4, 5, 11], and a preprocessing method [8], are proposed. However, the existing models, such as shooting and bouncing ray (SBR) [4], bidirectional path tracing (BDPT) [12], brick tracing (BT) [13], ray frustums (RF) [14], prior distance measure (PDM) [8], and space division (SD) [15] techniques, Hindawi Publishing Corporation e Scientific World Journal Volume 2014, Article ID 601729, 17 pages http://dx.doi.org/10.1155/2014/601729