For more than a decade, mobile network data traffic and users’ demand are considerably increased due to the advent of evolving mobile technologies, capable end-user devices and data-intensive content. Different forecasts show that the growth will continue for similar reasons. To accommodate the increasing network traffic and users’ demand, operators should continuously expand the capacity of their mobile networks using different capacity enhancing technologies. Network densification using small cells is one of the important capacity enhancement methods that are being implemented. To successfully exploit capacity benefits of network densification, efficient network planning is needed to address its deployment challenges including availability and cost of site, energy source and backhaul while minimizing interference and maximizing network capacity and users’ throughputs. Using street furniture including lamp posts and utility poles during the planning of dense/ultra-dense networks is being considered as one method to address the availability of sites and cost challenges. But technoeconomic benefits of using the furniture and usage methods are not studied in the context of Addis Ababa. In this thesis work, the techno-economic benefits of using the furniture from an outdoor network planning perspective for a selected area of Addis Ababa will be investigated. The outdoor planning optimization is performed using technical and economic objectives while considering lamp posts and utility poles of the selected areas as part of candidate locations for small cells. The multiobjective optimization is solved using Genetic algorithm and its implementation and result analysis are performed using MATLAB. Propagation computation for network simulation is undertaken using a deterministic dominant path model that is implemented within WinProp. Empirical economic analysis results show that using streetlamp posts and utility poles decreases deployment cost by 17% compared to using a new standalone pole (dedicated pole used for only small cell deployment). Furthermore, obtained Pareto optimal networks from outdoor planning simulation that considers 143 lamp posts and 81 utility poles as candidate cells provide 53 lamp posts and 43 utility poles. Thus, only 24% is consumed by street posts for 96 sites while for 13 sites using new standalone pole 57% of the total deployment cost is consumed.