Performance Analysis of a Mission-Critical Portable LTE System in Targeted RF Interference

Mission-critical wireless networks are being upgraded to 4G long-term evolution (LTE). These networks require very high reliability and security as well as easy deployment and operation in the field. Wireless communications systems have been vulnerable to jamming, spoofing and other radio frequency (RF) attacks since the early days of analog systems. Although wireless systems have evolved, important security and reliability concerns still exist. This paper presents our methodology for testing 4G LTE operating in harsh signaling environments. We use software-defined radio technology and open-source software to develop a fully configurable protocol-aware interference waveform. We define several test cases that target the entire LTE signal or part of it and evaluate the performance of a mission- critical production LTE system. Our RF experiments show that LTE synchronization signal interference causes significant throughput degradation at low interference power. By dynamically evaluating the performance measurement counters, the k-nearest neighbor classification method can detect the specific RF signaling attack to aid in effective mitigation.

[1]  Yih-Chun Hu,et al.  Cross-Layer Jamming Detection and Mitigation in Wireless Broadcast Networks , 2007, IEEE/ACM Transactions on Networking.

[2]  Peng Ning,et al.  Dynamic Adaptive Anti-Jamming via Mobility Control , 2013 .

[3]  Vuk Marojevic,et al.  Analyzing and enhancing the resilience of LTE/LTE-A systems to RF spoofing , 2015, 2015 IEEE Conference on Standards for Communications and Networking (CSCN).

[4]  Xiaofu Ma,et al.  Next generation public safety networks: A spectrum sharing approach , 2016, IEEE Communications Magazine.

[5]  Jeffrey H. Reed,et al.  Analysis and Mitigation of Interference to the LTE Physical Control Format Indicator Channel , 2014, 2014 IEEE Military Communications Conference.

[6]  Srikanth V. Krishnamurthy,et al.  Denial of Service Attacks in Wireless Networks: The Case of Jammers , 2011, IEEE Communications Surveys & Tutorials.

[7]  Wei Yu,et al.  On simulation studies of jamming threats against LTE networks , 2015, 2015 International Conference on Computing, Networking and Communications (ICNC).

[8]  Hsiao-Chun Wu,et al.  Physical layer security in wireless networks: a tutorial , 2011, IEEE Wireless Communications.

[9]  Sisi Liu,et al.  Mitigating control-channel jamming attacks in multi-channel ad hoc networks , 2009, WiSec '09.

[10]  Gordon L. Stüber,et al.  Resilience of LTE networks against smart jamming attacks , 2014, 2014 IEEE Global Communications Conference.

[11]  Jeffrey H. Reed,et al.  How to enhance the immunity of LTE systems against RF spoofing , 2016, 2016 International Conference on Computing, Networking and Communications (ICNC).

[12]  Roger Piqueras Jover,et al.  LTE/LTE-A jamming, spoofing, and sniffing: threat assessment and mitigation , 2016, IEEE Communications Magazine.

[13]  Jeffrey H. Reed,et al.  Enhancing the Robustness of LTE Systems: Analysis and Evolution of the Cell Selection Process , 2017, IEEE Communications Magazine.

[14]  Bülent Tavli,et al.  Denial-of-Service attacks and countermeasures in IEEE 802.11 wireless networks , 2009, Comput. Stand. Interfaces.