Unparalleled increasing demands for high capacity and consistent service quality on cellular network havernbeen challenging for telecom operators. However, current deployed and existing radio access network isrnsignificantly behind the growth. This promotes operators to network upgrade, expansion and base stationrn(BS) densification. Operators are also trying to mix macro and small cell on their radio access network asrna potential solution to meet their customer demands by enhancing their network capacity and coveragernextension. However, addition of the small cell on existing network increases energy consumption. rnThis thesis study considers energy efficient BS deployment for enhancement of LTE network capacity. Forrnthis purpose, small cell deployment underlay to the existing macro BS is used in outdoor scenario in 2x2rnsquare kilometer area located in Addis Ababa. Candidate locations for the small cell first selected mainlyrnbased on traffic distributions in the selected area of study. Then radio propagation simulations performedrnusing WinProp radio planning and simulation tool followed by Genetic algorithm based optimization tornfind out the optimal number and locations of the small cell obtaining enhanced capacity and improvedrnenergy efficiency with minimized additional power consumption. The result analysis is observed in MatLabrnimplementation. rnFinally, aggregate capacity and energy efficiency have been evaluated. The result shows that both thernaggregate network capacity and energy efficiency increased with number of small cell. There is 77.94%rncapacity and 24.7% energy efficiency improvement as compared to the original macro BS only network,rnwhich respectively requires 82 and 59 small cells transmitting at 0.5-watt power. At the same time,rnimprovement of capacity requires 18 small cell while it takes 23 and above small cell for energy efficiencyrnto be improved. For small cell more than 59, the energy efficiency start declining which indicates smallrncell deployment beyond this value has no importance as it declines energy efficiency. The aggregaternnetwork capacity has improved by 66.99% when selection of the small cell limited on its impact on energyrnefficiency. The maximum energy efficiency achieved is 24.7%, 22.32%, 17.88% and 11.12% respectivelyrnfor small cell transmitting at 0.5watt, 2watt, 5watt and 10watt. This result can possibly be improvedrnfurther by using different techniques such as sleep mode and cell zooming operations.