On the Secure DoF of the Single-Antenna MAC

A new achievability rate region for the secure discrete memoryless Multiple-Access-Channel (MAC) is presented. Thereafter, a novel secure coding scheme is proposed to achieve a positive Secure Degrees-of-Freedom (S-DoF) in the single-antenna MAC. This scheme converts the single-antenna system into a multiple-dimension system with fractional dimensions. The achievability scheme is based on the alignment of signals into a small sub-space at the eavesdropper, and the simultaneous separation of the signals at the intended receiver. Tools from the field of Diophantine Approximation in number theory are used to analyze the probability of error in the coding scheme.Comment: 5 Pages, Submitted to ISIT 201

Principles of Physical Layer Security in Multiuser Wireless Networks: A Survey

This paper provides a comprehensive review of the domain of physical layer security in multiuser wireless networks. The essential premise of physical-layer security is to enable the exchange of confidential messages over a wireless medium in the presence of unauthorized eavesdroppers without relying on higher-layer encryption. This can be achieved primarily in two ways: without the need for a secret key by intelligently designing transmit coding strategies, or by exploiting the wireless communication medium to develop secret keys over public channels. The survey begins with an overview of the foundations dating back to the pioneering work of Shannon and Wyner on information-theoretic security. We then describe the evolution of secure transmission strategies from point-to-point channels to multiple-antenna systems, followed by generalizations to multiuser broadcast, multiple-access, interference, and relay networks. Secret-key generation and establishment protocols based on physical layer mechanisms are subsequently covered. Approaches for secrecy based on channel coding design are then examined, along with a description of inter-disciplinary approaches based on game theory and stochastic geometry. The associated problem of physical-layer message authentication is also introduced briefly. The survey concludes with observations on potential research directions in this area.Comment: 23 pages, 10 figures, 303 refs. arXiv admin note: text overlap with arXiv:1303.1609 by other authors. IEEE Communications Surveys and Tutorials, 201

How MIMO cross-layer design enables QoS while detecting non-cooperative nodes in wireless multi-hop networks

In Journal of Network and Computer Applications (JNCA). DOI: 10.1016/j.jnca.2014.07.011International audienceWireless Multi-hop Networks (WMNs) are based on the cooperation between nodes. The non-cooperative (selfish) nodes can affect the quality of services (QoS) delivered by the network. The solutions proposed in literature are based on the monitoring mechanism to detect non-cooperative nodes. However, the monitoring mechanism has to tackle a significant false alarm rate. The origin of these issues is mainly related to the interferences and the costs of the monitoring mechanism. In WMNs based on Single-Input Single-Output (SISO) technology, the interferences at the monitor (detector) node can affect the assessment and the accuracy of the monitor node's observation. In this paper, we use Multi-Input and Multi-Output (MIMO) technology to tackle these drawbacks and to perform the monitoring mechanism without affecting the QoS. We propose a new MAC protocol based on the well-known SPACE-MAC protocol, named MIMODog. The collision at the monitor node can be avoided by tuning the antennas' weights. Therefore, the signal coming from other nodes than the monitored one can be nullified. Thus, this solution allows an important improvement of the accuracy of the monitor node's observation. Moreover, we propose a monitoring capacity analysis using graph theory particularly Conflict Graph (CG), and asymptotic study. We illustrate that the capacity consumed in the case of MIMODog is costly compared to SPACE-MAC, but the accuracy of the observation is better. We demonstrate that the number of monitor nodes is $\Theta(\frac{M}{\sqrt{n\ln n}})$ for a MIMO network with randomly located nodes n, each equipped with M antennas. Indeed, numerical results nlnn illustrate that by using MIMODog, the network can have a constant improvement M on an asymptotic number of monitor nodes compared to SISO 802.11 DCF MAC