3.3CVJun 7, 2020
Finger Texture Biometric Characteristic: a SurveyRaid R. O. Al-Nima, Tingting Han, Taolue Chen et al.
\begin{abstract} In recent years, the Finger Texture (FT) has attracted considerable attention as a biometric characteristic. It can provide efficient human recognition performance, because it has different human-specific features of apparent lines, wrinkles and ridges distributed along the inner surface of all fingers. Also, such pattern structures are reliable, unique and remain stable throughout a human's life. Efficient biometric systems can be established based only on FTs. In this paper, a comprehensive survey of the relevant FT studies is presented. We also summarise the main drawbacks and obstacles of employing the FT as a biometric characteristic, and provide useful suggestions to further improve the work on FT. \end{abstract}
1.2ITApr 23, 2019
Optimal Downlink Transmission for Cell Free SWIPT Massive MIMO Systems with Active EavesdroppingMahmoud Alageli, Aissa Ikhlef, Fahad Alsifiany et al.
This paper considers secure simultaneous wireless information and power transfer (SWIPT) in cell-free massive multiple-input multiple-output (MIMO) systems. The system consists of a large number of randomly (Poisson-distributed) located access points (APs) serving multiple information users (IUs) and an information-untrusted dual-antenna active energy harvester (EH). The active EH uses one antenna to legitimately harvest energy and the other antenna to eavesdrop information. The APs are networked by a centralized infinite backhaul which allows the APs to synchronize and cooperate via a central processing unit (CPU). Closed-form expressions for the average harvested energy (AHE) and a tight lower bound on the ergodic secrecy rate (ESR) are derived. The obtained lower bound on the ESR takes into account the IUs' knowledge attained by downlink effective precoded-channel training. Since the transmit power constraint is per AP, the ESR is nonlinear in terms of the transmit power elements of the APs and that imposes new challenges in formulating a convex power control problem for the downlink transmission. To deal with these nonlinearities, a new method of balancing the transmit power among the APs via relaxed semidefinite programming (SDP) which is proved to be rank-one globally optimal is derived. A fair comparison between the proposed cell-free and the colocated massive MIMO systems shows that the cell-free MIMO outperforms the colocated MIMO over the interval in which the AHE constraint is low and vice versa. Also, the cell-free MIMO is found to be more immune to the increase in the active eavesdropping power than the colocated MIMO.
1.2ITJul 6, 2017
On Differential Modulation in Downlink Multiuser MIMO SystemsFahad Alsifiany, Aissa Ikhlef, Jonathon Chambers
In this paper, we consider a space time block coded multiuser multiple-input multiple-output (MU-MIMO) system with downlink transmission. Specifically, we propose to use downlink precoding combined with differential modulation (DM) to shift the complexity from the receivers to the transmitter. The block diagonalization (BD) precoding scheme is used to cancel co-channel interference (CCI) in addition to exploiting its advantage of enhancing diversity. Since the BD scheme requires channel knowledge at the transmitter, we propose to use downlink spreading along with DM, which does not require channel knowledge neither at the transmitter nor at the receivers. The orthogonal spreading (OS) scheme is employed in order to separate the data streams of different users. As a space time block code, we use the Alamouti code that can be encoded/decoded using DM thereby eliminating the need for channel knowledge at the receiver. The proposed schemes yield low complexity transceivers while providing good performance. Monte Carlo simulation results demonstrate the effectiveness of the proposed schemes.
3.5CVMar 14, 2014
Spontaneous expression classification in the encrypted domainSegun Aina, Yogachandran Rahulamathavan, Raphael C. -W. Phan et al.
To date, most facial expression analysis have been based on posed image databases and is carried out without being able to protect the identity of the subjects whose expressions are being recognised. In this paper, we propose and implement a system for classifying facial expressions of images in the encrypted domain based on a Paillier cryptosystem implementation of Fisher Linear Discriminant Analysis and k-nearest neighbour (FLDA + kNN). We present results of experiments carried out on a recently developed natural visible and infrared facial expression (NVIE) database of spontaneous images. To the best of our knowledge, this is the first system that will allow the recog-nition of encrypted spontaneous facial expressions by a remote server on behalf of a client.