Biblio
With the advent of massive machine type of communications, security protection becomes more important than ever. Efforts have been made to impose security protection capability to physical-layer signal design, so called physical-layer security (PLS). The purpose of this paper is to evaluate the performance of PLS schemes for a multi-input-multi-output (MIMO) systems with space-time block coding (STBC) under imperfect channel estimation. Three PLS schemes for STBC schemes are modeled and their bit error rate (BER) performances are evaluated under various channel estimation error environments, and their performance characteristics are analyzed.
ISSN: 2163-0771
Covert or low probability of detection communication is crucial to protect user privacy and provide a strong security. We analyze the joint impact of imperfect knowledge of the channel gain (channel uncertainty) and noise power (noise uncertainty) on the average probability of detection error at the eavesdropper and the covert throughput in Rayleigh fading channel. We characterize the covert throughput gain provided by the channel uncertainty as well as the covert throughput loss caused by the channel fading as a function of the noise uncertainty. Our result shows that the channel fading is essential to hiding the signal transmission, particularly when the noise uncertainty is below a threshold and/or the receive SNR is above a threshold. The impact of the channel uncertainty on the average probability of detection error and covert throughput is more significant when the noise uncertainty is larger.
This paper considers a pilot spoofing attack scenario in a massive MIMO system. A malicious user tries to disturb the channel estimation process by sending interference symbols to the base-station (BS) via the uplink. Another legitimate user counters by sending random symbols. The BS does not possess any partial channel state information (CSI) and distribution of symbols sent by malicious user a priori. For such scenario, this paper aims to separate the channel directions from the legitimate and malicious users to the BS, respectively. A blind channel separation algorithm based on estimating the characteristic function of the distribution of the signal space vector is proposed. Simulation results show that the proposed algorithm provides good channel separation performance in a typical massive MIMO system.
Successive interference cancellation (SIC) receiver is adopted by power domain non-orthogonal multiple access (NOMA) at the receiver side as the baseline receiver scheme taking the forthcoming expected mobile device evolution into account. Development technologies and advanced techniques are boldly being considered in order to achieve power saving in many networks, to reach sustainability and reliability in communication due to envisioned huge amount of data delivery. In this paper, we propose a novel scheme of NOMA-SIC for the sake of balancing the trade-off between system performance and complexity. In the proposed scheme, each SIC level is comprised by a matching filter (MF), a MF detector and a regenerator. In simulations, the proposed scheme demonstrates the best performance on power saving, of which energy efficiency increases with an increase in the number of NOMA device pairs.
We propose a multi-level CSI quantization and key reconciliation scheme for physical layer security. The noisy wireless channel estimates obtained by the users first run through a transformation, prior to the quantization step. This enables the definition of guard bands around the quantization boundaries, tailored for a specific efficiency and not compromising the uniformity required at the output of the quantizer. Our construction results in an better key disagreement and initial key generation rate trade-off when compared to other level-crossing quantization methods.
Primary user emulation (PUE) attack is one of the main threats affecting cognitive radio (CR) networks. The PUE can forge the same signal as the real primary user (PU) in order to use the licensed channel and cause deny of service (DoS). Therefore, it is important to locate the position of the PUE in order to stop and avoid any further attack. Several techniques have been proposed for localization, including the received signal strength indication RSSI, Triangulation, and Physical Network Layer Coding. However, the area surrounding the real PU is always affected by uncertainty. This uncertainty can be described as a lost (cost) function and conditional probability to be taken into consideration while proclaiming if a PU/PUE is the real PU or not. In this paper, we proposed a combination of a Bayesian model and trilateration technique. In the first part a trilateration technique is used to have a good approximation of the PUE position making use of the RSSI between the anchor nodes and the PU/PUE. In the second part, a Bayesian decision theory is used to claim the legitimacy of the PU based on the lost function and the conditional probability to help to determine the existence of the PUE attacker in the uncertainty area.
Recently, some papers that apply a multi-armed bandit algorithm for channel selection in a cognitive radio system have been reported. In those papers, channel selection based on Upper Confidence Bound (UCB) algorithm has been proposed. However, in those selection, secondary users are not allowed to transmit data over same channels at the same time. Moreover, they do not take security of wireless communication into account. In this paper, we propose secure channel selection methods based on UCB algorithm, taking secrecy capacity into account. In our model, secondary users can share same channel by using transmit time control or transmit power control. Our proposed methods lead to be secure against an eavesdropper compared to conventional channel selections based on only estimated channel availability. By computer simulation, we evaluate average system secrecy capacity. As a result, we show that our proposed channel selections improve average system secrecy capacity compared to conventional channel selection.
The passive radar also known as Green Radar exploits the available commercial communication signals and is useful for target tracking and detection in general. Recent communications standards frequently employ Orthogonal Frequency Division Multiplexing (OFDM) waveforms and wideband for broadcasting. This paper focuses on the recent developments of the target detection algorithms in the OFDM passive radar framework where its channel estimates have been derived using the matched filter concept using the knowledge of the transmitted signals. The MUSIC algorithm, which has been modified to solve this two dimensional delay-Doppler detection problem, is first reviewed. As the target detection problem can be represented as sparse signals, this paper employs compressive sensing to compare with the detection capability of the 2-D MUSIC algorithm. It is found that the previously proposed single time sample compressive sensing cannot significantly reduce the leakage from the direct signal component. Furthermore, this paper proposes the compressive sensing method utilizing multiple time samples, namely l1-SVD, for the detection of multiple targets. In comparison between the MUSIC and compressive sensing, the results show that l1-SVD can decrease the direct signal leakage but its prerequisite of computational resources remains a major issue. This paper also presents the detection performance of these two algorithms for closely spaced targets.
Joint transmission coordinated multi-point (CoMP) is a combination of constructive and destructive superposition of several to potentially many signal components, with the goal to maximize the desired receive-signal and at the same time to minimize mutual interference. Especially the destructive superposition requires accurate alignment of phases and amplitudes. Therefore, a 5G clean slate approach needs to incorporate the following enablers to overcome the challenging limitation for JT CoMP: accurate channel estimation of all relevant channel components, channel prediction for time-aligned precoder design, proper setup of cooperation areas corresponding to user grouping and to limit feedback overhead especially in FDD as well as treatment of out-of-cluster interference (interference floor shaping).
Discrete Cosine Transform (DCT) is used in JPEG compression, image encryption, image watermarking and channel estimation. In this paper, an Application Specific Processor (ASP) for DCT based applications is designed and implemented to Field Programmable Gate Array (FPGA). One dimensional DCT and IDCT hardwares which have fully parallel architecture have been implemented and connected to MicroBlaze softcore processer. To show a basic application of ASP, DCT based image watermarking example is studied in this system.
Wireless security has been an active research area since the last decade. A lot of studies of wireless security use cryptographic tools, but traditional cryptographic tools are normally based on computational assumptions, which may turn out to be invalid in the future. Consequently, it is very desirable to build cryptographic tools that do not rely on computational assumptions. In this paper, we focus on a crucial cryptographic tool, namely 1-out-of-2 oblivious transfer. This tool plays a central role in cryptography because we can build a cryptographic protocol for any polynomial-time computable function using this tool. We present a novel 1-out-of-2 oblivious transfer protocol based on wireless channel characteristics, which does not rely on any computational assumption. We also illustrate the potential broad applications of this protocol by giving two applications, one on private communications and the other on privacy preserving password verification. We have fully implemented this protocol on wireless devices and conducted experiments in real environments to evaluate the protocol. Our experimental results demonstrate that it has reasonable efficiency.
Physical-layer authentication techniques exploit the unique properties of the wireless medium to enhance traditional higher-level authentication procedures. We propose to reduce the higher-level authentication overhead by using a state-of-the-art multi-target tracking technique based on Gaussian processes. The proposed technique has the additional advantage that it is capable of automatically learning the dynamics of the trusted user's channel response and the time-frequency fingerprint of intruders. Numerical simulations show very low intrusion rates, and an experimental validation using a wireless test bed with programmable radios demonstrates the technique's effectiveness.