Massive MIMO channel prediction using recurrent neural networks

Massive MIMO has been classified as one of the high potential wireless communication technologies due to its unique abilities such as high user capacity, increased spectral density, and diversity among others. Due to the exponential increase of connected devices, these properties are of great importance for the current 5G-IoT era and future telecommunication networks. However, outdated channel state information (CSI) caused by the variations in the channel response due to the presence of highly mobile and rich scattering is a major problem facing massive MIMO systems. Outdated CSI occurs when the information obtained about the channel at the transmitter changes before transmission. This leads to performance degradation of the network. In this work, we demonstrate a low complexity channel prediction method using neural networks. Specifically, we explore the power of recurrent neural network utilizing long-short memory cells in analyzing time series data. We review various neural network-based channel prediction methods available in the literature and compare complexity and performance metrics. Results indicate that the proposed methods outperform conventional systems by tremendously lowering the complexity associated with channel prediction.This work is funded by the scientific and technological research council of Turkey (TÜBITAK) under grand 119E392

Enhancing the security performance of ostbc using pre-equalicodization

In this study, we first quantify the secrecy performance achieved by employing precoded orthogonal space time block coding (POSTBC) in order to use it as a benchmark for comparison purposes with a new proposed security scheme. In POSTBC, space time codewords are precoded before being transmitted with an optimum pre-coding matrix based on the main channel of the legitimate parties. The obtained results demonstrate a considerable secrecy gap region in the resulting bit error rate (BER) performance due to using POSTBC. Afterwards, a new method called pre-equlicodization (precoding along with semi pre-equalization) is proposed to further enhance the secrecy performance. In pre-equlicodization scheme, the transmitted symbols are precoded by a new modified matrix called pre-equalicodizing matrix. This matrix is built by manipulating each row element in the optimal selected precoding matrix by the corresponding amplitude square inverse of the estimated channel gain over each data stream. The comparative simulation results prove that the employment of the proposed method can provide robustness against eavesdropping while assuring confidentiality and reliability between the legitimate communication parties albeit Eve is considered to have full knowledge of the used method, but not the main channel since TDD is adopted.Institute of Electrical and Electronics Engineer