Ebtihal H. G. Yousif

Performance analysis of multi-antenna GLRT-based spectrum sensing for cognitive radio

This paper addresses the generalized likelihood ratio test (GLRT) eigenvalue based detector with an arbitrary number of receive antennas. We investigate the optimum decision threshold, the minimum sensing time and the achievable sensing throughput trade-off of the secondary network. First, we derive the generalized asymptotic distributions of the test statistic. Second, we investigate the optimal decision threshold that can minimize the total error rate with constraints. Third, we provide the algorithm to find out the shortest sensing time that enables the minimum total error rate to achieve the target value. Finally, we formulate the achievable sensing throughput trade-off for the secondary network and investigate the optimal sensing time which can maximize the achievable throughput for the GLRT detector with multiple antennas under the absence and presence of the noise uncertainty. The accuracy of the derived theoretical models is supported by simulations. The results have shown that the optimized decision threshold and the minimum sensing time can satisfy the target value of the minimum total error rate speedily while both the interests of primary and secondary users are guaranteed simultaneously. In addition, the chosen optimal sensing time maximizes the throughput with and without noise uncertainty. HighlightsThe performance and the optimality of the multi-antenna GLRT detector are studied.We derive the generalized expressions of P fa and P d for the GLRT detector.The optimal decision threshold is investigated to minimize the total error rate.The minimum sensing time is studied to accelerate the spectrum sensing.The optimal sensing time is obtained to maximize the achievable throughput.

A new LSA-based approach for spectral coexistence of MIMO radar and wireless communications systems

Recently, the new concept of Licensed Shared Access/Authorized Shared Access (LSA/ASA) has emerged as a feasible commercial version of dynamic spectrum reuse based on Cognitive Radio (CR) technologies, e.g., via spectrum sensing or by exploiting geo-location information. This paper considers the problem of effective spectrum sharing between a colocated Multiple-Input-Multiple-Output (MIMO) radar that monitors the existence of a target and a wireless communications system. More specifically, the investigated scenario considers the downlink of a communications system represented by a Base Station (BS) trying to reuse the spectrum allocated for a colocated MIMO radar in order to communicate with an assigned terminal, in the vicinity of the radar system. We present an accurate model for the operation of the wireless system in the downlink, while the MIMO radar tries to maintain an acceptable detectability level of a target in the far field. The target detection problem is reformulated using a sensing approach based on energy detection, while the BS applies beamforming to null the interference created at the radar receiver. Based on the theory of Hermitian quadratic forms and with the aid of the Linearly Constrained Minimum Variance (LCMV) beamforming solution, the performance of target detection, when the MIMO radar coexists with the data transmission is quantified and numerical results show that spectral coexistence is feasible.

A Frequency Domain Approach to Eigenvalue-Based Detection With Diversity Reception and Spectrum Estimation

In this paper, we investigate a frequency domain approach for eigenvalue-based detection of a primary user, based on equal gain combining (EGC) and spectrum estimation with Bartletts method. This paper considers two techniques for eigenvalue detection which are Maximum Eigenvalue Detection (MED) and the Maximum-Minimum Eigenvalue (MME) detector. We exploit the eigenvalues that are associated with the Hermitian form representation of Bartletts estimate to assess the performance of the aforementioned eigenvalue techniques in the frequency domain. For each case, we quantify the performance based on the probabilities of false alarm and missed detection over Rayleigh and Rician fading. A bivariate Mellin transform approach is employed to obtain the probability distribution function for the ratio of the extreme eigenvalues under each hypothesis. All obtained formulas are validated via Monte-Carlo simulations, and the results give a clear insight into the performance of the investigated methods. In frequency domain, MED outperforms both the MME detector and Periodogram-based energy detection even in a worst case scenario of noise uncertainty, while the MME detector exhibits heavy-tailed statistical characteristics and thus its receiver operating characteristics tend to stay on the line of no-discrimination. The performance of MED is further enhanced by careful choice of combinations of the total length of the sensing frame and number of sub-slots.

Modeling and Performance Analysis of Multitaper Detection Using Phase-Type Distributions Over MIMO Fading Channels

This paper presents modeling and analysis of two variations of the multitaper detector namely multiple antenna detection of a single-user multiple-input-multiple-output (MIMO) node, and the multitaper method (MTM) combined with singular value decomposition (SVD), which is known as the MTM-SVD processor. Motivated by the reputation of the MTM as the best nonparametric power spectral density (PSD) estimator and after reviewing the limited previous research attempts, which focus on single-input-single-output (SISO) multitapering, we present the exact analytical models for the two considered derivatives of the multitaper method over fading channels by making use of the theory of Hermitian forms and Phase-Type distributions. In addition, using the Neyman-Pearson Approach (NPA), the performance of both detectors is optimized over Nakagami fading. For both multitaper variations, we accurately derive the eigenvalues of the Hermitian form of each detector, where the eigenvalues identify the Phase-Type distribution parameters. This yields generalized expressions for the probabilities of false alarm and missed detection when arbitrary multitaper weights are used. Finally, we investigate the impact of noise uncertainty on the performance of MIMO-MTM. The results show that performance of both detectors is dependent on the total number of discrete prolate spheriodal sequences (DPSSs), while for the MTM-SVD processor the performance is also dependent on the number of cooperating users and the employed frequency resolution. It is also shown that MIMO-MTM is robust under noise uncertainty. The obtained analytical models are proven to be accurate and enables further investigations on the multitaper detector.

Optimal decision threshold for eigenvalue-based spectrum sensing techniques

This paper investigates optimization of the sensing threshold that minimizes the total error rate (i.e., the sum of the probabilities of false alarm and missed detection) of eigenvalue-based spectrum sensing techniques for multiple-antenna cognitive radio networks. Four techniques are investigated, which are maximum eigenvalue detection (MED), maximum minimum eigenvalue (MME) detection, energy with minimum eigenvalue (EME) detection, and the generalized likelihood ratio test (GLRT) detection. The contribution of this paper is of four parts. Firstly, we present the derivative of the matrix-variate confluent hypergeometric function, which is required for the MED case. Secondly, we derive the probabilities of false alarm for both cases MME and EME detection. Thirdly, we derive the probability of missed detection for the GLRT detector. Finally, we provide the exact expressions required to obtain the optimal sensing thresholds for all cases. The simulation results reveal that for all the investigated cases the chosen optimal sensing thresholds achieve the minimum total error rate.

Optimization of multi-antenna GLRT-based spectrum sensing for cognitive radio

This paper investigates the optimization of the generalized likelihood ratio test (GLRT) eigenvalue-based spectrum sensing detector in terms of decision thresholds and sensing time. In order to guarantee the interests of primary and secondary users simultaneously, the sensing performance is assessed using the total error rate, i.e., the summation of probabilities of false alarm and missed detection. Therefore, the generalized statistical distributions of the test statistic are derived under the absence and presence of primary users, assuming an arbitrary number of receive antennas. These distributions are necessary for the analyses of the total error rate performance and the optimization. The optimization consists of two parts. Firstly, the optimal decision threshold is numerically obtained, which can minimize the total error rate under the constraints of target probabilities of false alarm and missed detection. Secondly, the optimal sensing time is obtained when a target total error rate is guaranteed, so that the spectrum sensing process can be accelerated without the loss of sensing accuracy. Furthermore, the simulation and theoretical results reveal that the chosen optimal decision thresholds benefit the primary and secondary users simultaneously and the chosen optimal sensing time improves the speed of spectrum sensing.

On the spectral coexistence of colocated MIMO radars and wireless communications systems

The Licensed Shared Access (LSA) approach has emerged as a viable solution to provide dynamic spectrum access by allowing the primary users (incumbents) to temporarily lease the access to their spectrum to third parties (licensees). Recently, there have been proposals in Europe and USA to share radar bands (2.3 GHz in Europe, 3.5 GHz in USA) for commercial broadband use. This paper studies the problem of coexistence between MIMO-radars (incumbent) and wireless communications systems (licensee). We first present a model for the operation of the downlink wireless system coexisting with MIMO-radar that maintains correct detectability of a target in the far field. The main objective of the wireless communication system is to dynamically reuse the radars spectrum through maximizing the throughput of the user equipment (UE) while minimizing the total probability of sensing errors at the MIMO-radars side. To facilitate coexistence, we employ a multi-objective optimization approach using evolutionary algorithm that guarantees to satisfy the operational objectives of both the MIMO-radar and the wireless communications system. It is shown that the derived models are accurate and the multi-objective problem can be solved using a variant of the Non-dominated Sorting Genetic Algorithm II (NSGA-II), which is considered as a fast elitist multi-objective evolutionary algorithm.

A new approach for multi-dimensional signal processing and modelling for signals from gel electrophoresis

In this paper, a multi-channel multi-dimensional approach is investigated for modeling of signals obtained from DNA gel electrophoresis. Related applications include DNA fingerprinting and crime scene investigations. In order to improve resolution and accuracy of modeling, a novel approach is employed based on using equidistant multi-capture data frames obtained over an extended span of time. The multidimensional signal is rescaled and aligned which improves resolution, then the signal is modeled as a surface that varies with both the time index and separation size. The overall approach is tested on a number of datasets. The simulation results show that the proposed approach can be used as a starting multi-dimensional time series model for raw signals obtained from gel electrophoresis.

MIMO-based Multitaper detection over Nakagami channels for dynamic spectrum access devices

The multitaper estimator is considered as the most powerful nonparametric method for reconstructing the power spectrum of a signal. The multitaper detector has been strongly recommended to be used for spectrum sensing in cognitive radio systems. In this paper we provide a new and accurate model for the Multitaper detector assuming that both the transmitting and detecting nodes are employing single-user multiple-input-multiple-output (MIMO) structures. We present closed form mathematical expressions for the performance of the decision variable within the hypotheses testing context. We model the decision variable using the Phase-Type distribution, where we derive the exact distribution parameters for both the null and the alternate hypotheses. Furthermore, we accurately bound the average probability of detection over Nakagami fading channels. Finally, the average probability of detection is maximized to yield a predetermined probability of false alarm. The results show that the obtained analytical models are accurate. As a generic trend, it is found that adjusting the length of observed sequences has no effect on the detector performance. On the other hand, it is found that increasing the number of receiving branches provides a significant enhancement for the MIMO-Multitaper method.

On the design and throughput analysis of a new MME detector using Bartlett's method

Detection of primary users is a very crucial task for cognitive radio networks. On the other hand, the choice of the spectrum sensing algorithm affects the achievable throughput of the secondary network when the cognitive radios employ the interweave approach. Focusing on the eigenvalue-based detector, it can be seen that most proposed methods are based on time domain. Therefore, in this paper we present and analyse a new class of eigenvalue detectors in frequency domain (FD). The major contributions of this paper are of two parts. First, we introduce a new minimum-maximum eigenvalue (MME) spectrum sensing method based on Bartletts method of estimation. By making use of the eigenvalues of the diagonalized quadratic form representation of Bartletts estimate, the distribution of the ratio of extreme eigenvalues is studied, and then the performance of the detector is addressed and accurate expressions where obtained for the probabilities of false alarm and detection. Second, assuming that the secondary network employs an interweave approach we study the average achievable throughput. All obtained formulas are verified through Monte Carlo simulations. The obtained results gives an insight into the validity of using MME detection in FD.