EEOPA Algorithm for MIMO-OFDM with Energy-Efficiency and QOS Constraints
Sk.Nageena1, M.Ramana Reddy2, P.Prasanna Murali Krishna3
Citation : Sk.Nageena,M.Ramana Reddy,P.Prasanna Murali Krishna, EEOPA Algorithm for MIMO-OFDM with Energy-Efficiency and QOS Constraints International Journal of Innovative Research in Electronics and Communications 2015, 2(8) : 16-22
Wireless communications is, by any measure, the fastest growing segment of the communications industry. As such, it has captured the attention of the media and the imagination of the public. Cellular systems have experienced exponential growth over the last decade and there are currently around two billion users worldwide. Indeed, cellular phones have become a critical business tool and part of everyday life in most developed countries, and are rapidly supplanting antiquated wire line systems in many developing countries. In addition, wireless local area networks currently supplement or replace wired networks in many homes, businesses, and campuses. Many new applications, including wireless sensor networks, automated highways and factories, smart homes and appliances, and remote telemedicine, are emerging from research ideas to
concrete systems. The mobile multimedia communication systems is rapid development the recent years. The main parameter is energy efficiency optimization and quality of service constraint for MIMO-OFDM communication. The various algorithm to be minimize the energy level for the transmitted signal. But it have some limitation. So we used proposed energy efficiency optimized power allocation (EEOPA).and to improve the energy efficiency for MIMO-OFDM mobile multimedia communication system. The EEOPA algorithm used
to solve the problem of multi-channel optimize to multi target in single channel optimization. The method to calculate the channel characteristics using singular variable decomposition method (SVD).
An energy-efficiency model is first proposed for MIMO-OFDM communication systems with statistical QoS constraints. By using (SVD) method, to view their channel characteristics. Furthermore, the optimization problem is in solved by grouping all sub channels. Therefore, a solution is derived for MIMO-OFDM systems.