Sina Maleki

Energy-Efficient Distributed Spectrum Sensing for Cognitive Sensor Networks

Reliability and energy consumption in detection are key objectives for distributed spectrum sensing in cognitive sensor networks. In conventional distributed sensing approaches, although the detection performance improves with the number of radios, so does the network energy consumption. We consider a combined sleeping and censoring scheme as an energy efficient spectrum sensing technique for cognitive sensor networks. Our objective is to minimize the energy consumed in distributed sensing subject to constraints on the detection performance, by optimally choosing the sleeping and censoring design parameters. The constraint on the detection performance is given by a minimum target probability of detection and a maximum permissible probability of false alarm. Depending on the availability of prior knowledge about the probability of primary user presence, two cases are considered. The case where a priori knowledge is not available defines the blind setup; otherwise the setup is called knowledge-aided. By considering a sensor network based on IEEE 802.15.4/ZigBee radios, we show that significant energy savings can be achieved by the proposed scheme.

Two-stage spectrum sensing for cognitive radios

We consider a two-stage sensing scheme for cognitive radios where coarse sensing based on energy detection is performed in the first stage and, if required, fine sensing based on cyclostationary detection in the second stage. We design the detection threshold parameters in the two sensing stages so as to maximize the probability of detection, given constraints on the probability of false alarm. We compare this scheme with ones where only energy detection or cyclostationary detection is performed. The performance comparison is made based on the probability of detection, probability of false alarm and mean detection time.

Cognitive spectrum utilization in Ka band multibeam satellite communications

Multibeam satellite networks in Ka band have been designed to accommodate the increasing traffic demands expected in the future. However, these systems are spectrum limited due to the current spectrum allocation policies. This paper investigates the potential of applying cognitive radio techniques in satellite communications (SatCom) in order to increase the spectrum opportunities for future generations of satellite networks without interfering with the operation of incumbent services. These extra spectrum opportunities can potentially amount to 2.4 GHz of bandwidth in the downlink and 2 GHz of bandwidth in the uplink for high density fixed satellite services (HDFSS).

Censored Truncated Sequential Spectrum Sensing for Cognitive Radio Networks

A truncated censored sequential spectrum sensing technique is considered as an energy saving approach for a cooperative spectrum sensing system. In order to design the underlying sensing parameters, the maximum energy consumption per sensor is minimized subject to a lower bounded global probability of detection and an upper bounded false alarm rate. We compare the performance of the proposed scheme with a fixed sample size censoring scheme. It is shown that the truncated censored sensing approach is highly energy efficient, particularly when the sensing cost is high.

Optimization of hard fusion based spectrum sensing for energy-constrained cognitive radio networks

a b s t r a c t The detection reliability of a cognitive radio network improves by employing a cooperative spectrum sensing scheme. However, increasing the number of cognitive radios entails a growth in the cooperation overhead of the system. Such an overhead leads to a throughput degradation of the cognitive radio network. Since current cognitive radio networks consist of low-power radios, the energy consumption is another critical issue. In this paper, throughput optimization of the hard fusion based sensing using the k-out-of-N rule is considered. We maximize the throughput of the cognitive radio network subject to a constraint on the probability of detection and energy consumption per cognitive radio in order to derive the optimal number of users, the optimal k and the best probability of false alarm. The simulation results based on the IEEE 802.15.4/ZigBee standard, show that the majority rule is either optimal or almost optimal in terms of the network throughput.

Energy and throughput efficient strategies for cooperative spectrum sensing in cognitive radios

An efficient cooperative spectrum sensing based cognitive radio network employs a certain number of secondary users to sense the spectrum while satisfying a constraint on the detection performance. We derive the optimal number of cognitive radios under two scenarios: an energy efficient and a throughput optimization setup. In the energy efficient setup, the number of cooperating cognitive radios is minimized for a k-out-of-N fusion rule with a constraint on the probability of detection and false alarm while in the throughput optimization setup, we maximize the throughput of the cognitive radio network, by deriving the optimal reporting time in a sensing time frame which is proportional to the number of cognitive users, subject to a constraint on the probability of detection. It is shown that both problems can be simplified to line search problems. The simulation results show that the OR and the majority rule outperform the AND rule in terms of energy efficiency and that the OR rule gives a higher throughput than the AND rule with a smaller number of users.

Resource Allocation for Cognitive Satellite Communications With Incumbent Terrestrial Networks

The lack of available unlicensed spectrum together with the increasing spectrum demand by multimedia applications has resulted in a spectrum scarcity problem, which affects satellite communications (SatCom) as well as terrestrial systems. The goal of this paper is to propose resource allocation (RA) techniques, i.e., carrier, power, and bandwidth allocation, for a cognitive spectrum utilization scenario where the satellite system aims at exploiting the spectrum allocated to terrestrial networks as the incumbent users without imposing harmful interference to them. In particular, we focus on the microwave frequency bands 17.7-19.7 GHz for the cognitive satellite downlink and 27.5-29.5 GHz for the cognitive satellite uplink, although the proposed techniques can be easily extended to other bands. In the first case, assuming that the satellite terminals are equipped with multiple low block noise converters (LNB), we propose a joint beamforming and carrier allocation scheme to enable cognitive space-to-Earth communications in the shared spectrum where fixed service (FS) microwave links have priority of operation. In the second case, however, the cognitive satellite uplink should not cause harmful interference to the incumbent FS system. For the latter, we propose a joint power and carrier allocation (JPCA) strategy followed by a bandwidth allocation scheme, which guarantees protection of the terrestrial FS system while maximizing the satellite total throughput. The proposed cognitive satellite exploitation techniques are validated with numerical simulations considering realistic system parameters. It is shown that the proposed cognitive exploitation framework represents a promising approach for enhancing the throughput of conventional satellite systems.

Directional Modulation Via Symbol-Level Precoding: A Way to Enhance Security

Wireless communication provides a wide coverage at the cost of exposing information to unintended users. As an information-theoretic paradigm, secrecy rate derives bounds for secure transmission when the channel to the eavesdropper is known. However, such bounds are shown to be restrictive in practice and may require exploitation of specialized coding schemes. In this paper, we employ the concept of directional modulation and follow a signal processing approach to enhance the security of multiuser multi-input multioutput (MIMO) communication systems when a multiantenna eavesdropper is present. Security enhancement is accomplished by increasing the symbol error rate at the eavesdropper. Unlike the information-theoretic secrecy rate paradigm, we assume that the legitimate transmitter is not aware of its channel to the eavesdropper, which is a more realistic assumption. We examine the applicability of MIMO receiving algorithms at the eavesdropper. Using the channel knowledge and the intended symbols for the users, we design security enhancing symbol-level precoders for different transmitter and eavesdropper antenna configurations. We transform each design problem to a linearly constrained quadratic program and propose two solutions, namely the iterative algorithm and one based on nonnegative least squares, at each scenario for a computationally efficient modulation. Simulation results verify the analysis and show that the designed precoders outperform the benchmark scheme in terms of both power efficiency and security enhancement.

Joint Power Control in Wiretap Interference Channels

Interference in wireless networks degrades the signal quality at the terminals. However, it can potentially enhance the secrecy rate. This paper investigates the secrecy rate in a two-user interference network where one of the users, namely user 1, needs to establish a confidential connection. User 1 wants to prevent an unintended user of the network from decoding its transmission. User 1 has to transmit such that its secrecy rate is maximized while the quality of service at the destination of the other user, user 2, is satisfied, and both users power limits are taken into account. We consider two scenarios: 1) user 2 changes its power in favor of user 1, an altruistic scenario, and 2) user 2 is selfish and only aims to maintain the minimum quality of service at its destination, an egoistic scenario. It is shown that there is a threshold for user 2s transmission power that only below or above which, depending on the channel qualities, user 1 can achieve a positive secrecy rate. Closed-form solutions are obtained to perform joint optimal power control. Further, a new metric called secrecy energy efficiency is introduced. We show that in general, the secrecy energy efficiency of user 1 in an interference channel scenario is higher than that of an interference-free channel.

Optimal hard fusion strategies for cognitive radio networks

Optimization of hard fusion spectrum sensing using the k-out-of-N rule is considered. Two different setups are used to derive the optimal k. A throughput optimization setup is defined by minimizing the probability of false alarm subject to a probability of detection constraint representing the interference of a cognitive radio with the primary user, and an interference management setup is considered by maximizing the probability of detection subject to a false alarm rate constraint. It is shown that the underlying problems can be simplified to equality constrained optimization problems and an algorithm to solve them is presented. We show the throughput optimization and interference management setups are dual. The simulation results show the majority rule is optimal or near optimal for the desirable range of false alarm and detection rates for a cognitive radio network. Furthermore, an energy efficient setup is considered where the number of cognitive radios is to be minimized for the AND and the OR rule and a certain probability of detection and false alarm constraint. The simulation results show that the OR rule outperforms the AND rule in terms of energy efficiency.