(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 8, No. 12, 2017 351 | Page www.ijacsa.thesai.org Relevance of Energy Efficiency Gain in Massive MIMO Wireless Network Ahmed Alzahrani, Vijey Thayananthan, Muhammad Shuaib Qureshi Computer Science Department, Faculty of Computing and Information Technology King Abdulaziz University, Jeddah 21589, Saudi Arabia. Abstract—The massive MIMO and energy efficiency (EE) analysis for the next generation technology are the hottest topics in wireless network research. This paper explains about massive MIMO wireless networks and EE for manifold channel which is an evolution massive MIMO. This research will help to design and implement a practical system of next generation network based on massive MIMO where efficient processing provides EE gain. In order to approach this research, different types of manifolds are considered with efficient techniques that depend on the rank of the channel matrix. Employing the specific manifold that helps to analyze the rate of the feedback increases not only the overall performance of the MIMO system but also the EE. We studied the convergence techniques used for optimizing quantization errors which have influences with manifold feedback. Here, we have focused on relevant areas which are very important to analyze EE gain in the future massive network. According to the selected results obtained in this research, many challenges will be possible to make useful proposals. Keywords—Massive MIMO; manifolds; EE gain; feedback; convergence; quantization I. INTRODUCTION Concept of basic MIMO system has been used in many applications for many decades but its design concept used in wireless networks is growing with next generation technology. The EE concepts are very attractive because they are not only used for the cost reductions, but also they are very useful to increase the lifetime of the components used in massive MIMO wireless networks. Massive MIMO wireless networks and communication systems are implemented with a large number of antennas in multi-channel environments [1]. In this, channel used in massive MIMO should be maintained because EE gain depends on the dynamic and statistic behavior of the channel. If the channel state information (CSI) is considered, the feedback employed in the receiver should be optimized to improve EE performance. The optimal feedback design using appropriate manifolds and massive MIMO can be analyzed through energy-efficient algorithms depended on the channel matrix, which needs a manifold to improve the rank and dimension of the covariance matrix [3], [4]. Complexity is a serious concern for massive MIMO because the dimension of the matrix is influenced directly. The novelty of this research is manifold feedback designed for massive MIMO system. Regarding the EE improvement based on massive MIMO, analyzing the key observations of massive MIMO such as feedback and few relevant parameters are useful in this research. As a practical matter, however, this EE excitement is tempered by the feasibility of making perfect and global CSI available at all the terminals of a massive MIMO network. It is very difficult and often impossible to provide such a perfect CSI because of rapid channel variations and power increasing dimensionality of channels. In the massive MIMO scheme, the uncertainty of channel estimates even at the receiver, and limited availability of communication resources to send information back from the receiver to other terminals in a network. Thus, it is critical to developing techniques for providing limited CSI with reasonable EE to the transmitters through the feedback used massive MIMO scheme [9]. This limited CSI at the transmitters helps significantly to boost the capabilities of current wireless technologies. When considering a single user communication and a point-to-point link in the massive MIMO scheme, utilization of antennas is unavoidable. Thus, the transmitter and receiver needs   and   antennas respectively. The practical problem of the conventional receiver is always a big issue in the design. Here, manifold techniques provide big improvements when design of the feedback is efficient. Overhead problem and EE is increased with a total number of antennas used in the transmitter of massive MIMO [6]. The geodesic and chordal distances considered in the manifold of dynamic channel should be appropriate to make efficient calculations. The optimized with dimensions of the manifold which MIMO channel needs to reduce the rank of the channel matrix, power and complexity. A geodesic, which is a non-linear curve of MIMO channel, holds a distance between any two points located on the curve assumed as a surface of any manifolds [2]. This small curve imagined on the manifold of the channel is a straight line. Also these two points are very close to each other in the Euclidean space. Singular value decomposition (SVD) of the matrix and eigenvectors associated to this matrix are necessary steps to calculate the performance of massive MIMO systems. These steps and calculations in MIMO need to be improved through the appropriate optimization techniques [8]. Linear channel model based on SVD with optimization will enhance the EE in an open and closed loop of MIMO system. The sections and sub-sections in the paper are categorized as follows. Section II provides basic information of MIMO and design that enhances the EE. Section III introduces the massive MIMO with feedback and types of manifolds. In Section IV,