Research Of MIMO Channel Estimation Based Key Generation Protocol

Due to the openness of the wireless channel, the attacker can easily wiretap and interfere in the communication process, thus hinder the communication security. Nowadays, the main solution to wireless security problem is to share secret keys and perform encryption between communication entities. Being the basis of encryption, the generation of secret keys directly decides how secure the system is.Compared with Single Input Single Output systems, Multiple Input Multiple Output (MIMO) systems can offer more channel randomness and greater key capacity under the influence of multipath fadings. However, the current research on key generation in MIMO systems mainly aims at two kinds of channel parameters, e.g. the amplitude and phase. These two types of algorithms both can not offer a satisfactory key capacity and key generation rate. In this thesis, based on theoretical deviration and simulation results, we propose a key generation method using channel estimation, which can provide greater key capacity and key generation rate.Firstly, this thesis analyzes and proves the feasibility and effectiveness of the channel estimation based key generation. Based on the wiretap channel model, this thesis established the MIMO channel model and proposed the channel estimation based key generation protocol. The key generation protocol contains three main conponents:channel measurement, channel quantization and error correction. In addition, this thesis proposes a theoretical analysis and derivation of key generation rate and key capacity, which confirms the feasibility and effectiveness of channel estimation key generation.Secondly, this thesis uses Compressed Sensing to design the channel estimating algorithm. In the key generation process, the design of channel estimation algorithm affects the performance of key generation. MIMO systems usually show the feature of sparsity. Based on this sparsity feature, this thesis uses Compressed Sensing and puts forward a MIMO sparse channel estimation algorithm for key generation, which uses only a few pilots. Theoretical derivation indicates that this method can effectively reduce the computation complexity and avoid interference of noise. This thesis takes three aspects to perform evaluation, e.g. the key mismatch rate, key generation rate and information entrophy of keys. Proved by simuation results, our algorithm gains better performance in the following three aspects. Therefore, our algorithm has better stability, robustness and security.Thirdly, this thesis uses distributed source coding to solve the key negotiation problem. In the process of key negotiation, based on the distributed source coding model, we put forward a key negotiation algorithm based on compression perception to solve the key negotiation problem in MIMO channel estimation, which includes using the sparsity feature of the initial key difference to generate negotiation information, using Compressed Sensing recovery algorithm to restore information and error correction. Simulation results show that the key negotiation algorithm based on compression perception using the observation matrix to compress the original key, can remove the correlation between public information and initial key and use very little public information to generate a long length negotiation key and has a higher probability of negotiation.