Abstract— The need for more wireless communication will keep increasing while there is limited electromagnetic spectrum. To meet this demand, new clever and efficient technologies need to be implemented. Massive MIMO as a new technology would improve the data throughput due to the enhanced spatial correlation. By deploying exponential correlation model, the impact of the channel spatial correlation on the energy and spectral efficiencies of massive MIMO is studied. This paper investigates a system model that has a base station (BS) with a large number of antennas and one user equipment with multiple antennas. The linear minimum mean square error (LMMSE) is used as pilot based estimator to create the lower capacity limits. Also, the influence of the channel spatial correlation on the estimation accuracy is investigated. Several scenarios are applied by adding different base station antenna numbers and several values of user terminal antennas. The spectral efficiency tends to be sensitive to the variation of correlation factor in the case of using higher signal to noise ratio (SNR). It is observed that the system is more energy efficient with higher number of antennas in the base station. Moreover, the spectral efficiency is getting higher with greater number of antennas in the user equipment. Index Terms— base station; massive MIMO; user equipment; channel state information; spatial correlation I. INTRODUCTION URING the previous decade, the demand for wireless data traffic has been increasing rapidly while the available electromagnetic spectrum is limited [1]. This high demand will keep growing due to the large growth in the number of smart phones and tablet devices [2]. By 2020, it is forecasted that the mobile data traffic will surpass 30 Exabyte a month while it was 6.2 Exabyte a month in 2016 [3]. The number of connections and mobile devices are expected to increase also from 7.9 billion in 2016 to more than 11.6 billion by 2020. It is necessary to increase the wireless throughput by applying efficient new technologies that can be implemented in reality [4], [5]. The wireless spectral efficiency depends on several factors such as channel estimation accuracy, spatial correlation, SNR and resources of signal processing [6]. The implementation of multiple antennas in the BS is significantly affective approach to enhance the wireless system and improve its spectral efficiency [7]. The multiple input multiple output (MIMO) is engaged into several wireless standers such as LTE- Advanced [8], [9]. One of the improved shape of this technology is Multiuser MIMO where the base station is equipped with multiple antennas and serves multiple users simultaneously where each user has single antenna [8]. This method has its own problems such as multiusers interference and channel state information (CSI) acquisition. Fig. 1. Wireless channel between the BS and the user terminal for uplink and downlink. The ultimate form of multiple antennas technology is called Massive MIMO [10]. The proposed concept of massive MIMO is based on equipping the base station (BS) by hundreds of antenna arrays which is much larger than the number of user terminals. Theoretically, massive MIMO can provide higher capacity that can be increased by simply having more antennas at the BS [1]. Also, the large number of antennas in the BS can reduce the transmit power for uplink and downlink transmissions. Moreover, because of the channel reciprocity, the overhead pilot sequences are linearly related to the number of user terminals and have nothing to do with the number of antennas in the BS. Since the number of BS antennas is higher than the users, the channel estimation will be more accurate and the signal processing will be simpler [11]. The great number of BS antennas would increase the energy efficiency since the Spatial Correlation Influence on The Channel Estimation and Spectral Efficiency for Massive MIMO Systems Saleh Albdran, Ahmed Alshammari, and Mohammad Matin D International Journal of Computer Science and Information Security (IJCSIS), Vol. 15, No. 6, June 2017 285 https://sites.google.com/site/ijcsis/ ISSN 1947-5500