Analysis of TDD Cellular Interference Mitigation Using Busy-Bursts
IEEE Transactions on Wireless Communications
An empirically based path loss model for wireless channels in suburban environments
IEEE Journal on Selected Areas in Communications
An exact path-loss density model for mobiles in a cellular system
Proceedings of the 7th ACM international symposium on Mobility management and wireless access
Revisiting circular-based random node simulation
ISCIT'09 Proceedings of the 9th international conference on Communications and information technologies
Wireless Personal Communications: An International Journal
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When simulating a wireless network, users/nodes are usually assumed to be distributed uniformly in space. Path losses between nodes in a simulated network are generally calculated by determining the distance between every pair of nodes and applying a suitable path loss model as a function of this distance (power of distance with an environment-specific path loss exponent) and adding a random component to represent the log-normal shadowing. A network with N nodes consists of N(N - 1)/2 path loss values. In order to generate statistically significant results for system-level simulations, Monte Carlo simulations must be performed where the nodes are randomly distributed at the start of every run. This is a time-consuming operation which need not be carried out if the distribution of path losses between the nodes is known. The probability density function (pdf) of the path loss between the centre of a circle and a node distributed uniformly within a the circle is derived in this work.