A new training sequence for secure channel estimation in MIMO systems

In wireless environment, the channels are really affected by a number of factors such as: fading, interference, noise. In most of wireless communications, we have applied the training sequences as known signal at the receiver for estimating the channel as well as the transmitted signal. Nowadays, many paid services in the entertainment industry have required the high security for their data and this issue is challenge which needs to be solved. Recently, the semi-blind channel estimations have contributed in term of remarkable enhancement in the total bandwidth efficiency of multiple-input multiple-output (MIMO) systems. To obtain the high data rate demands, there is a fewer training symbols using in these semi-blind algorithms. However, each system model must be satisfied the safe data for both the suppliers and the customers. Based on the information theory, we propose the new transmit structure with the training data embedding secure symbols for distinguishing authorized users and the eavesdroppers. This solution is so-called security on the physical level which is considered as the robust solution for processing by the traditional software. In this investigation, we also focus on normalized mean square error (NMSE) analysis for different performance of two types of users mentioned. Simulation results confirm our modified scheme and illustrate that the semi-blind channel estimation with embedded secure data is capable of improving the security of the overall system.