Abstract:
In this thesis, we investigate the scheme to improve the group secret key generation
efficiency in 5G mmWave Massive MIMO networks by enhancing the efficiency of channel
probing for group key generation. A new channel probing strategy for star-topology networks
group key generation is proposed, which focuses on multiplexing of downlink probing
signals to perform the downlink channel probing concurrently. The hybrid precoder has
been considered in this scenario to mitigate the inter-group interference, which includes a
analog precoder and baseband precoder. To further balance the group key rates, a genetic
algorithm (GA) based power allocation algorithm is developed to allocate more power to the
nodes with unfavorable channel conditions. What’s more, we propose a scheme to estimate
group key rates based on the maximum likelihood estimator (MLE) so that we can estimate
the group key rates based on the probing samples. Various numerical results are provided
including the group key rates and bits disagreement ratio (BDR). 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.
