Physical Layer Service Integration in 5G: Potentials and Challenges

High transmission rate and secure communication have been identified as the key targets that need to be effectively addressed by fifth generation (5G) wireless systems. In this context, the concept of physical-layer security becomes attractive, as it can establish perfect security using only the characteristics of wireless medium. Nonetheless, to further increase the spectral efficiency, an emerging concept, termed physical-layer service integration (PHY-SI), has been recognized as an effective means. Its basic idea is to combine multiple coexisting services, i.e., multicast/broadcast service and confidential service, into one integral service for one-time transmission at the transmitter side. This article first provides a tutorial on typical PHY-SI models. Furthermore, we propose some state-of-the-art solutions to improve the overall performance of PHY-SI in certain important communication scenarios. In particular, we highlight the extension of several concepts borrowed from conventional single-service communications, such as artificial noise (AN), eigenmode transmission etc., to the scenario of PHY-SI. These techniques are shown to be effective in the design of reliable and robust PHY-SI schemes. Finally, several potential research directions are identified for future work.Comment: 12 pages, 7 figure

A collaborative physical layer security scheme

High level of security is essential in wireless 5G communications. The last few years there has been an increase in research interest in the potential of the radio channel’s physical properties to provide communications security. These research efforts investigate fading, interference, and path diversity to develop security techniques for implementation in 5G New Radio (NR). In this paper, we propose a collaborative scheme to existing physical layer security schemes, taking advantage of the characteristics of the OFDM technique. An OFDM symbol includes the pilot subcarriers, typically essential for the pilot channel estimation process performed at the legitimate receiver. In this work we propose the positions of the subcarriers to change on every OFDM symbol following a probability distribution known only to the legitimate transmitter and legitimate receiver. An eavesdropper, does not have access to the information of the pilot subcarriers positions so, it performs blind channel estimation. The theoretical analysis is based on the information theoretic problem formulation and is confirmed by simulations. The performance metrics used are the secrecy capacity and the outage probability. The proposed scheme is very simple and robust, strengthening security in multimedia applications

A Semiblind Two-Way Training Method for Discriminatory Channel Estimation in MIMO Systems

Discriminatory channel estimation (DCE) is a recently developed strategy to enlarge the performance difference between a legitimate receiver (LR) and an unauthorized receiver (UR) in a multiple-input multiple-output (MIMO) wireless system. Specifically, it makes use of properly designed training signals to degrade channel estimation at the UR which in turn limits the UR's eavesdropping capability during data transmission. In this paper, we propose a new two-way training scheme for DCE through exploiting a whitening-rotation (WR) based semiblind method. To characterize the performance of DCE, a closed-form expression of the normalized mean squared error (NMSE) of the channel estimation is derived for both the LR and the UR. Furthermore, the developed analytical results on NMSE are utilized to perform optimal power allocation between the training signal and artificial noise (AN). The advantages of our proposed DCE scheme are two folds: 1) compared to the existing DCE scheme based on the linear minimum mean square error (LMMSE) channel estimator, the proposed scheme adopts a semiblind approach and achieves better DCE performance; 2) the proposed scheme is robust against active eavesdropping with the pilot contamination attack, whereas the existing scheme fails under such an attack.Comment: accepted for publication in IEEE Transactions on Communication

Waveform-Defined Security: A Low-Cost Framework for Secure Communications

Communication security could be enhanced at physical layer but at the cost of complex algorithms and redundant hardware, which would render traditional physical layer security (PLS) techniques unsuitable for use with resource-constrained communication systems. This work investigates a waveform-defined security (WDS) framework, which differs fundamentally from traditional PLS techniques used in today’s systems. The framework is not dependent on channel conditions such as signal power advantage and channel state information (CSI). Therefore, the framework is more reliable than channel dependent beamforming and artificial noise (AN) techniques. In addition, the framework is more than just increasing the cost of eavesdropping. By intentionally tuning waveform patterns to weaken signal feature diversity and enhance feature similarity, eavesdroppers will not be able to identify correctly signal formats. The wrong classification of signal formats would result in subsequent detection errors even when an eavesdropper uses brute-force detection techniques. To get a robust WDS framework, three impact factors, namely training data feature, oversampling factor and bandwidth compression factor (BCF) offset, are investigated. An optimal WDS waveform pattern is obtained at the end after a joint study of the three factors. To ensure a valid eavesdropping model, artificial intelligence (AI) dependent signal classifiers are designed followed by optimal performance achievable signal detectors. To show the compatibility in available communication systems, the WDS framework is successfully integrated in IEEE 802.11a with nearly no adding computational complexity. Finally, a low-cost software-defined radio (SDR) experiment is designed to verify the feasibility of the WDS framework in resource-constrained communications