@ARTICLE{Kaur_Dalveer_Enhance_2019, author={Kaur, Dalveer and Kumar, Neeraj}, volume={vol. 65}, number={No 1}, journal={International Journal of Electronics and Telecommunications}, pages={71-78}, howpublished={online}, year={2019}, publisher={Polish Academy of Sciences Committee of Electronics and Telecommunications}, abstract={Multiple input multiple output (MIMO) is a multiple antenna technology used extensively in wireless communication systems. With the ever increasing demand in high data rates, MIMO system is the necessity of wireless communication. In MIMO wireless communication system, where the multiple antennas are placed on base station and mobile station, the major problem is the constant power of base station, which has to be allocated to data streams optimally. This problem is referred as a power allocation problem. In this research, singular value decomposition (SVD) is used to decouple the MIMO system in the presence of channel state information (CSI) at the base station and forms parallel channels between base station and mobile station. This practice parallel channel ensures the simultaneous transmission of parallel data streams between base station and mobile station. Along with this, water filling algorithm is used in this research to allocate power to each data stream optimally. Further the relationship between the channel capacity of MIMO wireless system and the number of antennas at the base station and the mobile station is derived mathematically. The performance comparison of channel capacity for MIMO systems, both in the presence and absence of CSI is done. Finally, the effect of channel correlation because of antennas at the base stations and the mobile stations in the MIMO systems is also measured.}, type={Artykuły / Articles}, title={Enhance the Capacity of MIMO Wireless Communication Channel using SVD and Optimal Power Allocation Algorithm}, URL={http://www.czasopisma.pan.pl/Content/110198/PDF/11_1329_new.pdf}, doi={10.24425/ijet.2019.126285}, keywords={MIMO, water filling algorithm, singular value decomposition, channel state information, channel capacity}, }