Efficient Physical Layer Group Key Generation in 5G Wireless Networks

摘要

We investigate group secret key generation in 5G mmWave Massive MIMO networks and intend to improve the efficiency of channel probing for group key generation. In this paper, a new channel probing strategy for star-topology networks is proposed, which relies on the multiplexing of downlink probing signals, enabled by the hybrid precoding. To improve the group key rates per channel probing, a genetic algorithm (GA) based power allocation algorithm is also proposed. What’s more, to estimate the group key rates based on the probing samples, we propose a scheme for the estimation of group key rates based on the maximum likelihood estimator (MLE). The performance of the proposed scheme on group key rates and bits disagreement ratio (BDR) are provided. The numerical results show that the GA-based downlink channel probing scheme can increase the efficiency of channel probing and have higher group key rates compared with the existing channel probing schemes. When the SNR is 25dB, the key rates of GA-based power allocation scheme are 20% higher than the scheme with the conventional channel probing strategy.