Physical layer security is an emerging technique to protect the wireless communications in the Internet of Things (IoT). Motivated by the fact that a single IoT terminal usually occupies a very small fraction of feedback resources, we propose a novel secure transmission design with feedback compression to improve the feedback resources utilization for secure communications. Specifically, we first introduce a multiperiod one-feedback (MPOF) scheme to exploit the channel temporal correlation existing in the IoT scenarios, making the IoT terminal convey its channel knowledge to the central controller in a more efficient manner. Under this MPOF scheme, we then put forward a virtual quantizer model and design a generalized fixed-rate secure on-off transmission scheme, where the central controller adaptively adjusts the transmission parameters in one feedback interval. By averaging the total secrecy throughput of one feedback interval over all the coherence periods thereof, we further characterize the secrecy throughput of our proposed transmission scheme and facilitate the joint optimization design of the feedback interval length, the wiretap codes, and the power allocation ratios. To handle this nonconvex problem, we develop an efficient approach involving the block coordinate descent algorithm and the 1-D search method. Numerical results show that when the channel temporal correlation is high, our proposed secure transmission design achieves a significantly higher secrecy throughput than the conventional design constrained by the same amount of feedback resources.
Physical layer security is an emerging technique to protect the wireless communications in the Internet of Things (IoT). Motivated by the fact that a single IoT terminal usually occupies a very small fraction of feedback resources, we propose a novel secure transmission design with feedback compression to improve the feedback resources utilization for secure communications. Specifically, we first introduce a multiperiod one-feedback (MPOF) scheme to exploit the channel temporal correlation existing in the IoT scenarios, making the IoT terminal convey its channel knowledge to the central controller in a more efficient manner. Under this MPOF scheme, we then put forward a virtual quantizer model and design a generalized fixed-rate secure on-off transmission scheme, where the central controller adaptively adjusts the transmission parameters in one feedback interval. By averaging the total secrecy throughput of one feedback interval over all the coherence periods thereof, we further characterize the secrecy throughput of our proposed transmission scheme and facilitate the joint optimization design of the feedback interval length, the wiretap codes, and the power allocation ratios. To handle this nonconvex problem, we develop an efficient approach involving the block coordinate descent algorithm and the 1-D search method. Numerical results show that when the channel temporal correlation is high, our proposed secure transmission design achieves a significantly higher secrecy throughput than the conventional design constrained by the same amount of feedback resources.
Physical layer security is a promising way to secure the wireless communications in the Internet of Things (IoT). Motivated by the fact that the limited feedback resources in the IoT network would degrade the secrecy advantage of the multiple-antenna technique, we attempt to investigate the problem of how many transmit antennas should be utilized to perform secure communications. In particular, we consider the heterogeneous IoT downlink network and design a multiuser secure transmission scheme. In this scheme, the zero-forcing beamforming technique is adopted to serve the IoT legitimate users, and the remaining spatial freedoms are utilized to send artificial noise (AN) for confusing the passive eavesdroppers. Given the secrecy outage constraints, we derive the closed-form expression for the network secrecy throughput and formulate a non-convex optimization problem with multiple parameters, e.g., the number of transmit antennas, the wiretap codes, the feedback bits allocation strategy, and the power allocation ratio between the information bearing signal and the AN. To effectively tackle this problem, we develop an optimization framework involving the block coordinate descent algorithm and the 1-D search method. Simulation results validate the effectiveness of our proposed optimization framework and show that the optimal number of transmit antennas increases as the secrecy outage constraints become stricter, or the feedback resources become scarcer.
Great concerns on the Internet of Things (IoT) security are raised as IoT becomes an emerging paradigm to achieve ubiquitous connectivity. This article studies low-complexity secure transceiver and feedback design with the assistance of a jammer for physical-layer security in multiantenna IoT systems. We consider the general setting where a legitimate multiantenna controller broadcasts confidential messages to multiple multiantenna IoT devices in the presence of a passive external multiantenna eavesdropper. Moreover, there is only quantized downlink channel state information (CSI) at the controller and the jammer through feedback channels. We introduce several secure transceivers for different system setups, all of which employ block-diagonal precoding at the controller and null-space beamforming at the jammer but are with the different receivers at each IoT device. Considering the practical setup of IoT and for the tractability of analysis, we study the secrecy performance of the transceiver with an arbitrarily selected receive matrix independent of the channels of all devices. We derive an approximate lower bound on the ergodic secrecy rate (ESR) of each devicewithoutassuming any asymptotes for system parameters. The obtained result can also be viewed as a lower bound on the ESR performance of any other transceivers. We also optimize this bound to find an adaptive feedback bit allocation to the two feedback channels of each legitimate device. Numerical results are shown to illustrate the obtained analytical ESR lower bound, the feedback bit allocation algorithm, and significant ESR performance gain that results from the proposed feedback bit allocation.
In this article, a general framework for enhancing the physical layer security (PLS) in the Internet of Things (IoT) systems via channel feedback is established. To be specific, first, we study the compound wiretap channel (WTC) with feedback, which can be viewed as an ideal model for enhancing the PLS in the downlink transmission of IoT systems via feedback. A novel feedback strategy is proposed and a corresponding lower bound on the secrecy capacity is constructed for this ideal model. Next, we generalize the ideal model (i.e., the compound WTC with feedback) by considering channel states and feedback delay, and this generalized model is called the finite state compound WTC with delayed feedback. The lower bounds on the secrecy capacities of this generalized model with or without delayed channel output feedback are provided, and they are constructed according to variations of the previously proposed feedback scheme for the ideal model. Finally, from a Gaussian fading example, we show that the delayed channel output feedback enhances the achievable secrecy rate of the finite state compound WTC with only delayed state feedback, which implies that feedback helps to enhance the PLS in the downlink transmission of the IoT systems.
We design a novel artificial-noise-aided secure ON-OFF transmission scheme in a wiretap channel. We consider a practical scenario, where the multi-antenna transmitter only obtains partial channel knowledge from the single-antenna receiver through limited training and feedback but has no channel knowledge about the single-antenna eavesdropper. In the design, we first propose a three-period block transmission protocol to capture the practical training and quantization features. We then characterize the statistics of the received signal-to-noise ratios at the receiver and the eavesdropper. Under the secrecy outage constraint, we exploit the ON-OFF scheme to perform secure transmission and derive a closed-form expression for the secrecy throughput. Moreover, we investigate the optimization problem of maximizing the secrecy throughput by proposing an iterative algorithm to determine the optimal power allocation between the information signal and artificial noise, as well as the optimal codeword transmission rate. Furthermore, we define the net secrecy throughput (NST), which takes the signaling overhead into account and address the problem of optimally allocating the block resource to the training and feedback overhead. Numerical results clearly demonstrate how the optimal signaling overhead changes with the number of transmit antennas, and there exists an optimal number of antennas that maximizes the NST.
Physical layer security (PLS) in the down-link transmission of Internet of Things (IoT) systems is modeled as the compound wiretap channel (C-WTC). Recently, it has been shown that channel feedback helps to enhance the secrecy capacity of the C-WTC, where the channel feedback is used to generate secret keys protecting the transmitted message from being eavesdropped by the eavesdropper. In this paper, we show that for the Gaussian compound wiretap channel (GC-WTC), a hybrid feedback scheme that combines the existing secret-key type feedback and a variation of the classical Schalkwijk-Kailath (SK) type feedback scheme, performs better than the already existing one in the literature. The study of this paper offers a new option for the enhancement of the PLS in IoT systems.
In this article, we consider physical-layer security (PLS) of the Internet-of-Things (IoT) communications based on hybrid automatic repeat request (HARQ) protocols in multiple-input single-output single-eavesdropper (MISOSE) channels. Owing to the reciprocity of wireless channels, a negative acknowledge frame can be used to obtain the channel state information (CSI) from a source with multiple antennas to an IoT destination device, and this CSI of a legitimate link is used for beamforming for the next transmission round (TR). Therefore, a higher secrecy rate can be expected from retransmissions with beamforming based on the CSI as compared to the first TR without CSI. To evaluate the secrecy throughput under time-invariant and time-varying channels, connection and secrecy outage probabilities (OPs) are derived. By exploiting the characteristics of the OPs, we suggest an approximated secrecy throughput. We then consider the optimization of the approximated secrecy throughput considering the rate parameters for legitimate and eavesdropping links. With an alternating optimization approach, an algorithm to find convergent system parameters, i.e., the rates for legitimate and eavesdropping links, is proposed. Moreover, an asymptotic analysis with the large number of transmit antennas indicates an interesting behavior of the secrecy rate with regard to the number of TRs. The analytical results are verified by rigorous numerical simulations and they can serve as a useful guideline to those involved in the design of secure IoT communication systems with HARQ in MISOSE channels.