Abstract—In today’s world broadband cellular communication has a vast variety of applications. Some of them include HD video streaming, web browsing, social media and mobile banking. These applications provide opportunities for both network operators as well as consumers. Since these applications consume very large data, mobile operators face tough challenges to deliver bandwidth to the subscribers. Mobile operators invest profoundly to acquire bandwidth in the radio frequency spectrum with an aim to increase the capacity of wireless networks. Despite this fact, the radio frequency spectrum in not an infinite resource, as the whole telecommunication industry is battling a spectrum crisis. Hence, newer technologies such as LTE have evolved with an aim to produce higher throughput from prevailing bandwidth. Although LTE can deliver an increase in capacity by using the regular antenna systems, extensive deployment and optimization of Multiple-Input Multiple-Output (MIMO) antenna techniques can cause further increment in the data throughput of LTE. MIMO works the best for conditions which favor rich scattering, where signals bounce around the environment, using the radio path reflections that exist. The transmitter (Tx) and receiver (Rx) devices have more than one antenna and using the processing power available at either end of the link, they are able to utilize the various paths that are present between the two units to provide improvements in the data rates and signal to noise ratio (SNR). In order to achieve promised throughputs in LTE systems, operators must optimize their networks’ multipath conditions for MIMO, targeting both rich scattering conditions and high SNR for each multipath signal. Even so, MIMO antenna techniques bring along with them their own distinctive challenges, calling for a newer approach towards measurement and optimization of these networks. This project aims to improve the capacity of LTE networks by implementing MIMO technology in these networks, using software simulation.