Recently, tools from stochastic geometry have gained much attention for modeling and analysis of dense cellular networks. Although, extensive studies are available in literature in this respect however, the approaches are generalized and often lack significance towards practical scenarios where network conditions vary dynamically. The main objective of this research is to provide some insights into the stochastic geometry based analysis of cellular networks, through suitable modifications, so that it can be used to estimate parameters of interest i.e., intensity and coverage probability for different tiers and scenarios under consideration. The main definition for probability of coverage has been re-defined and complete closed form expression is derived. The intensity for different tiers have been estimated, with the help of proposed approach, beyond which no more gain in coverage probability can be achieved. Monte-Carlo simulations have been performed for validation of proposed approach and results are also compared with state-of-the-art approach.