Physical-Layer Secure Transmission Method with Random Sparse Array

With the characteristics of narrow scanning beam and high spatial resolution, sparse array becames a research hotspot. However, it can produce higher side lobes which leads to the information leakage easily. A physical layer secure transmission method based on sparse array was proposed in this paper to achieve secure communications. We used the genetic algorithm with two objective functions to produce multiple sparse array structures with low sidelobes, and then created a codebook. When transmitting signals, we selected a sparse array structure randomly for each symbol from the codebook. Both theoretical analysis and simulation results show that the proposed method can ensure the communication security. Introduction Wireless mobile communication is experiencing a huge change in data business with the popularity of variety intelligent and the increasing demand for future wireless applications in recent years, which speeds up the research on the fifth generation(5G) network[1] and providing a more safe and reliable service is a primary task in the design and implementation of the 5G network [2].Compared to traditional wireless communication network, physical layer security is identified as a promising strategy to safeguard data confidentiality by smartly exploiting the imperfections of the communications medium, and it can reap the benefits offered by promising technologies, e.g massive multiple-input multiple-output[3]. Massive MIMO technology has these characteristics of increasing frequency efficiency, reducing transmission power and forming a narrow beam communications. Small array element spacing leads to serious mutual coupling effect which degrades the system performance, So sparse array[4] with fewer array elements has weak mutual coupling effect, which are more suitable for Massive MIMO system. Periodic thinning of the antenna array produces high sidelobes, causes some interference to security communication. We can use intelligent optimization algorithms[5], such as genetic algorithm, simulated annealing algorithm, to optimize the sparse array structure , However, it only can overcome the large sidelobe levels, and cannot prevent the eavesdroppers from acquiring sensitive information from the received signal. Recently, Several approaches related to antenna subset modulation have been proposed for achieving enhanced security. In [6], according to the training sequence for estimating channel parameters from the desired receiver, selecting randomly part of array elements in order to achieve the purpose of equivalent random channel change, so as to ensure the eavesdropper's low probability of intercept. While [7] proposed a technique to select an antenna subset randomly for every symbol. 237 Advances in Computer Science Research (ACRS), volume 54 International Conference on Computer Networks and Communication Technology (CNCT2016)