Anti-eavesdropping Proportional Fairness Access Control for 5G Networks

Due to the open access nature, communication over unlicensed band, suffers from security threats like eavesdropping. Eavesdroppers are unwanted nodes, attempting to overhear the signal transmitted between two legitimate mobile terminals (MTs), often for malicious purposes. Apart from security issues, it results in significant degradation of secrecy throughput, i.e., the throughput achieved by a legitimate user without being overheard by eavesdroppers. Since with the present technology, it is quite difficult to identify the eavesdroppers even in 5G, the average throughput of the legitimate MTs decreases when the serving base station schedules the eavesdroppers as well, based on the channel condition only. So far, the issue of eavesdropping has rarely been considered in the context of scheduling. In this paper, we propose an anti-eavesdropping proportional fairness (APF) mechanism considering the possibility of eavesdroppers. Our proposed APF technique first estimates a set of suspected eavesdroppers based on sleep mode information, and then reduces the possibility of scheduling these eavesdroppers by imposing penalties. Penalty assignments are based on past average throughput, current channel conditions and modulation/coding schemes. Both Hidden Markov model based analysis and simulations confirm that the proposed APF technique outperforms the traditional proportional fairness protocol in terms of anti-eavesdropping efficiency and secrecy throughput.