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.
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.
Exploiting the randomness embedded in wireless channels, the physical-layer security techniques can provide additional security robustness against malicious eavesdropping at the physical layer of communication systems. To further this line of study, this thesis focuses on developing advanced multi-antenna transmission strategies for enhancing the secrecy performance of wireless communication systems. Assuming perfect channel feedback from the desired receiver and none from the eavesdropper, we consider beamforming with smartly injected artificial noise, aiming to confuse the eavesdropper whilst leaving the desired receiver unaffected. The system parameters are either chosen to be fixed for all transmissions, or adaptively adjusted based on the channel feedback from the desired receiver. For both cases, we provide novel and explicit design solutions for achieving the maximum throughput subject to a secrecy outage constraint. We then derive accurate approximations for the maximum throughput, and give new insights into the additional power cost for achieving a higher security level and the throughput gain of adaptive transmission over non-adaptive transmission. Having investigated the perfect feedback scenario, we then relax the feedback assumption and consider practical effects imposed by limited feedback constraints on the channel from the desired receiver to the transmitter. To deal with quantization error due to limited feedback whilst also accounting for unknown channel of the eavesdropper, we specify a connection outage constraint to guarantee the reliability of desired communication and a secrecy outage constraint to guard against malicious eavesdropping. Under dual outage constraints, we derive a novel optimized rate-adaptive transmission design to maximize the average secrecy throughput. New insights regarding the optimal power/feedback allocation and the number of feedback bits required for efficient quantization are obtained through our analysis. Our preceding study focused on isolated point-to-point transmission without any interference. However, the performance of contemporary wireless networks is often limited by interference from concurrent transmissions. To characterize the impact of interference on secure communication, we consider an interference-limited large-scale network. To confuse the malicious eavesdroppers, in addition to information-bearing signals, the transmitters are designed to generate artificial noise through either beamforming or antenna sectoring in a distributed manner. For both cases, using tools from stochastic geometry, we provide a statistical characterization of the reliability performance of desired communication and the secrecy performance against eavesdropping. We then investigate the networkwide secrecy throughput performance and optimize the transmit power allocation. Our analysis reveals interesting differences between the beamforming and sectoring approaches in terms of the optimal power allocation and the maximum networkwide secrecy throughput.
As Internet of Things (IoT) has boomed in recent years, many security issues have also been exposed. Focusing on physical layer security in wireless Internet of Things network communication, a series of security methods have been widely studied. Nevertheless, cooperative jamming methods in physical layer security to fight against collusive eavesdroppers have not been thoroughly studied yet. In this article, we study a cooperative-jamming-based physical layer secure transmission scheme for Internet of Things wireless networks in the presence of collusive eavesdroppers. We design a cooperative jamming strategy without knowing the channel state information of eavesdroppers. Considering the cooperation of multiple nodes with multiple antennas, this strategy can maximize the signal-to-interference-plus-noise ratio at an actuator (legitimate receiver). Meanwhile, the generated cooperative jamming signals can reduce the signal-to-interference-plus-noise ratio at eavesdroppers. To explore the theoretical security performance of our strategy, we perform a secrecy outage probability analysis and an asymptotic analysis. In the cases of cooperative jamming and without cooperative jamming, the closed-form expressions of the secrecy outage probability are deduced, and the influence of system parameters on the secrecy outage probability becomes more intuitive through a strict mathematical asymptotic behavior analysis. In addition, considering the energy limitation of Internet of Things devices, we propose a power allocation algorithm to minimize the total transmission power given the security requirements. The numerical results show the effectiveness of our schemes and are consistent with the theoretical analysis.
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.
Wireless communication is particularly susceptible to eavesdropping due to its broadcast nature. Security and privacy issues have become increasingly critical for wireless networks. This paper considers the problem of secret communication in the multiuser downlink eavesdropped by a passive eavesdropper (EVE). The well-known zero-forcing preceding is adopted at the transmitter to produce concurrent data streams to the users, and at the same time an artificial noise (AN) is generated to prevent EVE from intercepting the information. We first derive an analytical closed-form expression for the secrecy sum-rate in the large system limit. We then use it as the objective function to optimize the power allocation (PA) between the information signals and the AN to maximize the secrecy sum-rate. A simple analytical expression of the optimal PA is derived in the high transmit power regime, which proves to be a near-optimal and generic strategy. The large system results are quite accurate for finite-size systems and thus can provide useful insights into system analysis and design. Our analytical and simulation results show that the AN assisted strategy achieves the same multiplexing gain as in the multiuser downlink without eavesdropping. Moreover, more power should be allocated to AN when the system serves fewer users and EVE has more antennas.
The Internet of Things (IoT) depicts a bright future, where any devices having sensorial and computing capabilities can interact with each other. Among all existing technologies, the techniques for the fifth generation (5G) systems are the main driving force for the actualization of IoT concept. However, due to the heterogeneous environment in 5G networks and the broadcast nature of radio propagation, the security assurance against eavesdropping is a vital yet challenging task. In this paper, we focus on the transmission design for secure relay communications in IoT networks, where the communication is exposed to eavesdroppers with unknown number and locations. The randomize-and-forward relay strategy specially designed for secure multi-hop communications is employed in our transmission protocol. First, we consider a single-antenna scenario, where all the devices in the network are equipped with the single antenna. We derive the expression for the secrecy outage probability of the two-hop transmission. Following this, a secrecy-rate-maximization problem subject to a secrecy-outage-probability constraint is formulated. The optimal power allocation and codeword rate design are obtained. Furthermore, we generalize the above analyses to a more generic scenario, where the relay and eavesdroppers are equipped with multiple antennas. Numerical results show that the proper use of relay transmission can enhance the secrecy throughput and extend the secure coverage range.
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.