A Survey of Physical Layer Security Techniques for 5G Wireless Networks and Challenges Ahead

Physical layer security which safeguards data confidentiality based on the information-theoretic approaches has received significant research interest recently. The key idea behind physical layer security is to utilize the intrinsic randomness of the transmission channel to guarantee the security in physical layer. The evolution towards 5G wireless communications poses new challenges for physical layer security research. This paper provides a latest survey of the physical layer security research on various promising 5G technologies, including physical layer security coding, massive multiple-input multiple-output, millimeter wave communications, heterogeneous networks, non-orthogonal multiple access, full duplex technology, etc. Technical challenges which remain unresolved at the time of writing are summarized and the future trends of physical layer security in 5G and beyond are discussed.Comment: To appear in IEEE Journal on Selected Areas in Communication

Multi-function RF for Situational Awareness

Radio frequency (RF) communications are an integral part of many situational awareness applications. Sensing data need to be processed in a timely manner, making it imperative to have a robust and reliable RF link for information dissemination. Moreover, there is an increasing need for exploiting RF communication signals directly for sensing, leading to the notion of multi-function RF. In the first part of this dissertation, we investigate the development of a robust Multiple-Input Multiple-Output (MIMO) communication system suitable for airborne platforms.Three majors challenges in realizing MIMO capacity gain in airborne environment are addressed: 1) antenna blockage due largely to the orientation of the antenna array; 2) the presence of unknown interference inherent to the intended application; 3) the lack of channel state information (CSI) at the transmitter. Built on the Diagonal Bell-Labs Layered Space-Time (D-BLAST) MIMO architecture, the system integrates three key design approaches: spatial spreading to counter antenna blockage; temporal spreading to mitigate signal to interference and noise ratio degradation due to intended or unintended interference; and a simple low rate feedback scheme to enable real time adaptation in the absence of full transmitter CSI. Extensive experiment studies using a fully functioning $4\times 4$ MIMO system validate the developed system. In the second part, ambient RF signals are exploited to extract situational awareness information directly. Using WiFi signals as an example, we demonstrate that the CSI obtained at the receiver contains rich information about the propagation environment. Two distinct learning systems are developed for occupancy detection using passive WiFi sensing. The first one is based on deep learning where a parallel convolutional neural network (CNN) architecture is designed to extract useful information from both magnitude and phase of the CSI. Pre-processing steps are carefully designed to preserve human motion induced channel variation while insulating against other impairments and post-processing is applied after CNN to infer presence information for instantaneous motion outputs. To alleviate the need of tedious training efforts involved in deep learning based system, a novel learning problem with contaminated sampling is formulated. This leads to a second learning system: a two-stage solution for motion detection using support vector machines (SVM). A one-class SVM model is first evaluated whose training data are from human free environment only. Decontamination of human presence data using the one-class SVM is done prior to motion detection through a two-class support vector classifier. Extensive experiments using commercial off-the-shelf WiFi devices are conducted for both systems. The results demonstrate that the learning based RF sensing provides a viable and promising alternative for occupancy detection as they are much more sensitive to human motion than passive infrared sensors which are widely deployed in commercial and residential buildings

Secure Communications in Millimeter Wave Ad Hoc Networks

Wireless networks with directional antennas, like millimeter wave (mmWave) networks, have enhanced security. For a large-scale mmWave ad hoc network in which eavesdroppers are randomly located, however, eavesdroppers can still intercept the confidential messages, since they may reside in the signal beam. This paper explores the potential of physical layer security in mmWave ad hoc networks. Specifically, we characterize the impact of mmWave channel characteristics, random blockages, and antenna gains on the secrecy performance. For the special case of uniform linear array (ULA), a tractable approach is proposed to evaluate the average achievable secrecy rate. We also characterize the impact of artificial noise in such networks. Our results reveal that in the low transmit powerregime, the use of low mmWave frequency achieves better secrecy performance, and when increasing transmit power, a transition from low mmWave frequency to high mmWave frequency is demanded for obtaining a higher secrecy rate. More antennas at the transmitting nodes are needed to decrease the antenna gain obtained by the eavesdroppers when using ULA. Eavesdroppers can intercept more information by using a wide beam pattern. Furthermore, the use of artificial noise may be ineffective for enhancing the secrecy rate.Comment: Accepted by IEEE Transactions on Wireless Communication

Millimeter Wave Cellular Networks: A MAC Layer Perspective

The millimeter wave (mmWave) frequency band is seen as a key enabler of multi-gigabit wireless access in future cellular networks. In order to overcome the propagation challenges, mmWave systems use a large number of antenna elements both at the base station and at the user equipment, which lead to high directivity gains, fully-directional communications, and possible noise-limited operations. The fundamental differences between mmWave networks and traditional ones challenge the classical design constraints, objectives, and available degrees of freedom. This paper addresses the implications that highly directional communication has on the design of an efficient medium access control (MAC) layer. The paper discusses key MAC layer issues, such as synchronization, random access, handover, channelization, interference management, scheduling, and association. The paper provides an integrated view on MAC layer issues for cellular networks, identifies new challenges and tradeoffs, and provides novel insights and solution approaches.Comment: 21 pages, 9 figures, 2 tables, to appear in IEEE Transactions on Communication

Hybrid Beamforming via the Kronecker Decomposition for the Millimeter-Wave Massive MIMO Systems

Despite its promising performance gain, the realization of mmWave massive MIMO still faces several practical challenges. In particular, implementing massive MIMO in the digital domain requires hundreds of RF chains matching the number of antennas. Furthermore, designing these components to operate at the mmWave frequencies is challenging and costly. These motivated the recent development of hybrid-beamforming where MIMO processing is divided for separate implementation in the analog and digital domains, called the analog and digital beamforming, respectively. Analog beamforming using a phase array introduces uni-modulus constraints on the beamforming coefficients, rendering the conventional MIMO techniques unsuitable and call for new designs. In this paper, we present a systematic design framework for hybrid beamforming for multi-cell multiuser massive MIMO systems over mmWave channels characterized by sparse propagation paths. The framework relies on the decomposition of analog beamforming vectors and path observation vectors into Kronecker products of factors being uni-modulus vectors. Exploiting properties of Kronecker mixed products, different factors of the analog beamformer are designed for either nulling interference paths or coherently combining data paths. Furthermore, a channel estimation scheme is designed for enabling the proposed hybrid beamforming. The scheme estimates the AoA of data and interference paths by analog beam scanning and data-path gains by analog beam steering. The performance of the channel estimation scheme is analyzed. In particular, the AoA spectrum resulting from beam scanning, which displays the magnitude distribution of paths over the AoA range, is derived in closed-form. It is shown that the inter-cell interference level diminishes inversely with the array size, the square root of pilot sequence length and the spatial separation between paths.Comment: Submitted to IEEE JSAC Special Issue on Millimeter Wave Communications for Future Mobile Networks, minor revisio