Biblio

Physical-layer security (PLS) for an underlay cognitive radio network (CRN)-based simultaneous wireless information and power transfer (SWIPT) over cascaded κ-µ fading channels is investigated. The network is composed of a pair of secondary users (SUs), a primary user (PU) receiver, and an eavesdropper attempting to intercept the data shared by the SUs. To improve the SUs’ data transmission security, we assume a full-duplex (FD) SU destination, which employs energy harvesting (EH) to extract the power required for generating jamming signals to be emitted to confound the eavesdropper. Two scenarios are presented and compared; harvesting and non-harvesting eavesdropper. Moreover, a trade-off between the system’s secrecy and reliability is explored. PLS is studied in terms of the probability of non-zero secrecy capacity and the intercept probability, whereas the reliability is studied in terms of the outage probability. Results reveal the great impact of jamming over the improvement of the SUs’ secrecy. Additionally, our work indicates that studying the system’s secrecy over cascaded channels has an influence on the system’s PLS that cannot be neglected.

In this work we present a novel technique for physical layer security in the Internet-of-Things (IoT) networks. In the proposed architecture, each IoT node generates a phase-modulated random key/data and transmits it to a master node in the presence of an eavesdropper, referred to as Eve. The master node, simultaneously, broadcasts a high power signal using an omni-directional antenna, which is received as interference by Eve. This interference masks the generated key by the IoT node and will result in a higher bit-error rate in the data received by Eve. The two legitimate intended nodes communicate in a full-duplex manner and, consequently, subtract their transmitted signals, as a known reference, from the received signal (self-interference cancellation). We compare our proposed method with a conventional approach to physical layer security based on directional antennas. In particular, we show, using theoretical and measurement results, that our proposed approach provides significantly better security measures, in terms bit error rate (BER) at Eve's location. Also, it is proven that in our novel system, the possible eavesdropping region, defined by the region with BER \textbackslashtextless; 10-1, is always smaller than the reliable communication region with BER \textbackslashtextless; 10-3.

Although beamforming optimization problems in full-duplex communication systems can be optimally solved with the semidefinite relaxation (SDR) approach, its computational complexity increases rapidly when the problem size increases. In order to circumvent this issue, in this paper, we propose an alternating direction of multiplier method (ADMM) which minimizes the augmented Lagrangian of the dual of the SDR and handles the inequality constraints with the use of slack variables. The proposed ADMM is then applied for optimizing the relay beamformer to maximize the secrecy rate. Simulation results show that the proposed ADMM performs as good as the SDR approach.

Edge caching has received much attention as a promising technique to overcome the stringent latency and data hungry challenges in the future generation wireless networks. Meanwhile, full-duplex (FD) transmission can potentially double the spectral efficiency by allowing a node to receive and transmit simultaneously. In this paper, we study a cache-aided FD system via delivery time analysis and optimization. In the considered system, an edge node (EN) operates in FD mode and serves users via wireless channels. Two optimization problems are formulated to minimize the largest delivery time based on the two popular linear beamforming zero-forcing and minimum mean square error designs. Since the formulated problems are non-convex due to the self-interference at the EN, we propose two iterative optimization algorithms based on the inner approximation method. The convergence of the proposed iterative algorithms is analytically guaranteed. Finally, the impacts of caching and the advantages of the FD system over the half-duplex (HD) counterpart are demonstrated via numerical results.

We consider an underlay cognitive network with secondary users that support full-duplex communication. In this context, we propose the application of antenna selection at the secondary destination node to improve the secondary user secrecy performance. Antenna selection rules for cases where exact and average knowledge of the eavesdropping channels are investigated. The secrecy outage probabilities for the secondary eavesdropping network are analyzed, and it is shown that the secrecy performance improvement due to antenna selection is due to coding gain rather than diversity gain. This is very different from classical antenna selection for data transmission, which usually leads to a higher diversity gain. Numerical simulations are included to verify the performance of the proposed scheme.

A full-duplex radio can transmit and receive simultaneously, and, hence, is a natural fit for realizing an in-band relay system. Most of existing full-duplex relay designs, however, simply forward an amplified version of the received signal without decoding it, and, thereby, also amplify the noise at the relay, offsetting throughput gains of full-duplex relaying. To overcome this issue, we explore an alternative: demodulate-and-forward. This paper presents the design and implementation of DelayForward (DF), a practical system that fully extracts the relay gains of full-duplex demodulate-and-forward mechanism. DF allows a relay to remove its noise from the signal it receives via demodulation and forward the clean signal to destination with a small delay. While such delay-and-forward mechanism avoids forwarding the noise at the relay, the half-duplex destination, however, now receives the combination of the direct signal from a source and the delayed signal from a relay. Unlike previous theoretical work, which mainly focuses on deriving the capacity of demodulate-and-forward relaying, we observe that such combined signals have a structure similar to the convolutional code, and, hence, propose a novel viterbi-type decoder to recover data from those combined signals in practice. Another challenge is that the performance of full-duplex relay is inherently bounded by the minimum of the relay's SNR and the destination's SNR. To break this limitation, we further develop a power allocation scheme to optimize the capacity of DF. We have built a prototype of DF using USRP software radios. Experimental results show that our power-adaptive DF delivers the throughput gain of 1.25×, on average, over the state-of-the-art full-duplex relay design. The gain is as high as 2.03× for the more challenged clients.