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Romero-Zurita N.,University of Leeds | McLernon D.,University of Leeds | Ghogho M.,University of Leeds | Ghogho M.,International University of Rabat | Swami A.,U.S. Army
IEEE Signal Processing Letters

We address physical layer security in multiple-input-multiple-output (MISO) communications in the presence of an unknown passive eavesdropper. Beamforming and artificial noise broadcasting are chosen to increase communications security. We first study the effect of a close eavesdropper on security and then we define a 'Protected Zone' in the transmitter's vicinity. We present an optimisation strategy that intelligently sets the transmission power and the size of the protected zone to probabilistically achieve secrecy at a specified target secrecy rate. The results show that this strategy can achieve a high probability of secrecy by efficiently prioritising the use of the available resources. © 1994-2012 IEEE. Source

Romero-Zurita N.,University of Leeds | Ghogho M.,University of Leeds | Ghogho M.,International University of Rabat | McLernon D.,University of Leeds
Physical Communication

In this paper we address physical layer security in multiple-input-multiple-output (MIMO) frequency selective wireless channels in the presence of a passive eavesdropper, i.e., the associated channel is unknown to the transmitter. Signalling is based on orthogonal frequency division multiplexing (OFDM). Spatial beamforming and artificial noise broadcasting are chosen as the strategy for secure transmission. The contribution of channel frequency selectivity to improve secrecy is presented by performance and probabilistic analysis. Moreover, we investigate the capability of the eavesdropper to jeopardize the security of the system (defined as the SNR difference between the intended receiver and the eavesdropper) by mitigating the interfering effect of the artificial noise using zero forcing as a receive beamforming strategy. The results show that although zero forcing is not the optimal strategy to maximize the SNR, it offers (from the eavesdropper's perspective) a better performance than MMSE for MIMO frequency selective channels and thus threatens the overall security of the system. © 2011 Elsevier B.V. Source

Cardenas-Juarez M.,University of Leeds | Ghogho M.,University of Leeds | Ghogho M.,International University of Rabat
IEEE Communications Letters

The spectrum sensing duration and the secondary user's achievable throughput trade-off is optimized under outage constraints in a cooperative cognitive radio network over Nakagami fading conditions. The optimum trade-off depends not only on the maximum outage probability allowed by the primary user and the number of cognitive users involved in the sensing but also on the fading operational conditions of the cognitive radio. The parameters of the Nakagami fading distribution can be adjusted to fit different fading environments. The fading parameter (also called shape parameter) of the Nakagami distribution affects the optimum sensing time, which increases when the fading conditions are worse than Rayleigh fading. For the energy detector, the expression for the probability of false alarm is obtained in terms of a new threshold, which is derived considering an outage constraint on the channel-dependent probability of detection. Then, the optimization problem is formulated. Simulation results quantify the effects of different fading parameters on the optimum spectrum sensing duration. © 2006 IEEE. Source

Waqar O.,University of Leeds | Ghogho M.,University of Leeds | Ghogho M.,International University of Rabat | McLernon D.,University of Leeds
IEEE Communications Letters

Since a closed-form expression for the exact ergodic capacity of dual-hop fixed-gain relay networks is not mathematically tractable, thus we will present tight closed-form bounds for the ergodic capacity in Rayleigh fading channels. First we express the exact ergodic capacity in terms of a Lommel function and a single integral and then we apply integral inequalities to present one upper bound and two lower bounds on the ergodic capacity. We also show that our closed-form bounds match perfectly with Monte-Carlo simulations, particularly for moderate and high average signal-to-noise ratio (SNR) of the first hop. © 2011 IEEE. Source

Salman N.,University of Leeds | Ghogho M.,University of Leeds | Ghogho M.,International University of Rabat | Kemp A.H.,University of Leeds
IEEE Sensors Journal

Localization of sensor nodes in wireless sensor networks (WSNs) promotes many new applications. A longer life time is imperative for WSNs, this requirement constrains the energy consumption and computation power of the nodes. To locate sensors at a low cost, the received signal strength (RSS)-based localization is favored by many researchers. RSS positioning does not require any additional hardware on the sensors and does not consume extra power. A low complexity solution to RSS localization is the linear least squares (LLS) method. In this paper, we analyze and improve the performance of this technique. First, a weighted least squares (WLS) algorithm is proposed, which considerably improves the location estimation accuracy. Second, reference anchor optimization using a technique based on the minimization of the theoretical mean square error is also proposed to further improve performance of LLS and WLS algorithms. Finally, to realistically bound the performance of any unbiased RSS location estimator based on the linear model, the linear Cramer-Rao bound (CRB) is derived. It is shown via simulations that employment of the optimal reference anchor selection technique considerably improves system performance, while the WLS algorithm pushes the estimation performance closer to the linear CRB. Finally, it is also shown that the linear CRB has larger error than the exact CRB, which is the expected outcome. © 2001-2012 IEEE. Source

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