The upcoming fifth generation (5G) system is expected to support a variety of different devices and applications, such as ultra-reliable and low latency communications, Internet of Things (IoT) and mobile cloud computing. Reliable and effective communications lie in the core of the 5G system design. This dissertation is focused on the design and evaluation of robust 5G systems under both benign and malicious environments, with considerations on both the physical layer and higher layers. For the physical layer, we study secure and efficient 5G transceiver under hostile jamming. We propose a securely precoded OFDM (SP-OFDM) system for efficient and reliable transmission under disguised jamming, a serious threat to 5G, where the jammer intentionally confuses the receiver by mimicking the characteristics of the authorized signal, and causes complete communication failure. We bring off a dynamic constellation by introducing secure randomness between the legitimate transmitter and receiver, and hence break the symmetricity between the authorized signal and the disguised jamming. It is shown that due to the secure randomness shared between the authorized transmitter and receiver, SP-OFDM can achieve a positive channel capacity under disguised jamming. The robustness of the proposed SP-OFDM scheme under disguised jamming is demonstrated through both theoretic and numerical analyses. We further address the problem of finding the worst jamming distribution in terms of channel capacity for the SP-OFDM system. We consider a practical communication scenario, where the transmitting symbols are uniformly distributed over a discrete and finite alphabet, and the jamming interference is subject to an average power constraint, but may or may not have a peak power constraint. Using tools in functional analysis and complex analysis, first, we prove the existence and uniqueness of the worst jamming distribution. Second, by analyzing the Kuhn-Tucker conditions for the worst jamming, we prove that the worst jamming distribution is discrete in amplitude with a finite number of mass points. For the higher layers, we start with the modeling of 5G high-density heterogeneous networks. We investigate the effect of relay randomness on the end-to-end throughput in multi-hop wireless networks using stochastic geometry. We model the nodes as Poisson Point Processes and calculate the spatial average of the throughput over all potential geometrical patterns of the nodes. More specifically, for problem tractability, we first consider the simple nearest neighbor (NN) routing protocol, and analyze the end-to-end throughput so as to obtain a performance benchmark. Next, note that the ideal equal-distance routing is generally not realizable due to the randomness in relay distribution, we propose a quasi-equal-distance (QED) routing protocol. We derive the range for the optimal hop distance, and analyze the end-to-end throughput both with and without intra-route resource reuse. It is shown that the proposed QED routing protocol achieves a significant performance gain over NN routing. Finally, we consider the malicious link detection in multi-hop wireless sensor networks (WSNs), which is an important application of 5G multi-hop wireless networks. Existing work on malicious link detection generally requires that the detection process being performed at the intermediate nodes, leading to considerable overhead in system design, as well as unstable detection accuracy due to limited resources and the uncertainty in the loyalty of the intermediate nodes themselves. We propose an efficient and robust malicious link detection scheme by exploiting the statistics of packet delivery rates only at the base stations. More specifically, first, we present a secure packet transmission protocol to ensure that except the base stations, any intermediate nodes on the route cannot access the contents and routing paths of the packets. Second, we design a malicious link detection algorithm that can effectively detect the irregular dropout at every hop (or link) along the routing path with guaranteed false alarm rate and low miss detection rate.
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