Decision Fusion with Unknown Sensor Detection Probability

In this correspondence we study the problem of channel-aware decision fusion when the sensor detection probability is not known at the decision fusion center. Several alternatives proposed in the literature are compared and new fusion rules (namely 'ideal sensors' and 'locally-optimum detection') are proposed, showing attractive performance and linear complexity. Simulations are provided to compare the performance of the aforementioned rules.Comment: To appear in IEEE Signal Processing Letter

Performance Analysis and Design of Maximum Ratio Combining in Channel-Aware MIMO Decision Fusion

In this paper we present a theoretical performance analysis of the maximum ratio combining (MRC) rule for channel-aware decision fusion over multiple-input multiple-output (MIMO) channels for (conditionally) dependent and independent local decisions. The system probabilities of false alarm and detection conditioned on the channel realization are derived in closed form and an approximated threshold choice is given. Furthermore, the channel-averaged (CA) performances are evaluated in terms of the CA system probabilities of false alarm and detection and the area under the receiver operating characteristic (ROC) through the closed form of the conditional moment generating function (MGF) of the MRC statistic, along with Gauss-Chebyshev (GC) quadrature rules. Furthermore, we derive the deflection coefficients in closed form, which are used for sensor threshold design. Finally, all the results are confirmed through Monte Carlo simulations.Comment: To appear in IEEE Transactions on Wireless Communication

Rician MIMO Channel- and Jamming-Aware Decision Fusion

In this manuscript we study channel-aware decision fusion (DF) in a wireless sensor network (WSN) where: (i) the sensors transmit their decisions simultaneously for spectral efficiency purposes and the DF center (DFC) is equipped with multiple antennas; (ii) each sensor-DFC channel is described via a Rician model. As opposed to the existing literature, in order to account for stringent energy constraints in the WSN, only statistical channel information is assumed for the non-line-of sight (scattered) fading terms. For such a scenario, sub-optimal fusion rules are developed in order to deal with the exponential complexity of the likelihood ratio test (LRT) and impractical (complete) system knowledge. Furthermore, the considered model is extended to the case of (partially unknown) jamming-originated interference. Then the obtained fusion rules are modified with the use of composite hypothesis testing framework and generalized LRT. Coincidence and statistical equivalence among them are also investigated under some relevant simplified scenarios. Numerical results compare the proposed rules and highlight their jammingsuppression capability.Comment: Accepted in IEEE Transactions on Signal Processing 201

Optimality of received energy in decision fusion over Rayleigh fading diversity MAC with non-identical sensors

Abstract—Received-energy test for non-coherent decision fusion over a Rayleigh fading multiple access channel (MAC) without diversity was recently shown to be optimum in the case of conditionally mutually independent and identically distributed (i.i.d.) sensor decisions under specifi

Power optimization, network coding and decision fusion in multi-access relay networks

Multi-access relay (MAR) assisted communication appears in various applications such as hierarchical wireless sensor networks (WSN), two-way relay channels (TWRC) etc. since it provides a high speed and reliable communication with considerably large coverage. In this thesis, we develop the optimal power allocation, network coding and information fusion techniques to improve the performance of MAR channel by considering certain criterion (e.g., minimizing the average symbol error rate (SER) or maximizing the average sum-rate. For this purpose, we first derive optimal information fusion rules for hierarchical WSNs with the use of complete channel state information (CSI) and the partial CSI using channel statistics (CS) with the exact phase information. Later, we investigate the optimization of the MAR channel that employs complex field network coding (CFNC), where we have used two different metrics during the optimization: achievable sum rate and SER bound of the network under the assumption of receiver CSI. After that, we formulate the optimal power allocation problem to maximize the achievable sum rate of the MAR with decode and forward relaying while considering fairness among users in terms of their average achievable information rates under the constraints on the total power and network geometry. We show that this problem is non-convex and nonlinear, and obtain an analytical solution by properly dividing parameter space into four regions. Then, we derive an average SER bound for the CFNC coded MAR channel and aim to jointly optimize the CFNC and the relay power by minimizing SER bound under the total power constraint, which we prove as a convex program that cannot be solved analytically since the Karush-Khun-Tucker (KKT) conditions result in highly nonlinearity equations. Following that, we devise an iterative method to obtain SER optimal solutions which uses the information theoretical rate optimal analytical solution during the initialization and we show that this speeds up the convergence of the iterative method as compared to equal power allocation scheme. Next, we integrate CFNC into WSNs that operate over non-orthogonal communication channel, and derive optimal fusion rule accordingly, combine the SER bound minimization and the average rate-fairness ideas to come up with an approximate analytical method to jointly optimize CFNC and the relay power. Simulation results show that the proposed methods outperform the conventional methods in terms of the detection probability, achievable average sum-rate or average SER

IEEE Transactions on Signal Processing : Vol. 61, No. 1,2,3,4, January - February 2013

1. Robust Blind Pairwise Kalman Algorithms Using QR Decompositions / Valerian Nemesin, Stephane Derrode 2. Single-Site Emitter Localization via Multipath Fingerprinting / Evgeny Kupeshtein, Mati Wax, Israel Cohen 3. Optimality of Received Energy in Decision Fusion Over Rayleigh Fading Diversity MAC with Non-Identical Sensors / Domenico Ciuonzo, Gianmarco Romano, Pierluigi Salvo Rossi 4. Fast FIR Algorithms for the Continuous Wavelet Transform from Constrained Least Squares / George M. Leigh 5. Off-Grid Direction of Arrival Estimation Using Sparse Bayesian Inference / Zai Ynag, Lihua Xie, Cishen Zhang 6. Performance of Two Low-Rank STAP Filters in a Heterogeneous Noise / Gullaume Ginolhac, et al. 7. Progressive Linear Precorder Optimization for ARQ Packet Retransmissions in Nonregenerative MIMO Relay Systems / Zhengyu Zhang, Ling Qiu, Jie Xu 8. Jamming Games in the MIMO Wiretap Channel with an Active Eavesdropper / Amitav Mukherjee, A. Lee Swindlehurst 9. Bounds on the Optimal Performance for Jump Markov Linear Gaussian Systems / Carsten Fritsche, Fredrick Gustafsson 10. Concentration of Measure Inequalities for Toeplitz Matrices with Applications / Borhan M. Sanandaji, Tyrone L. Vincent, Michael B. Wakin 11. OFDM Radar Space-Time Adaptive Processing Exploiting Spatio-Temporal Sparsity / Satyabrata Sen 12. the Kalman-Like Practicle Filter: optimal estimation with quantized innovations/measurements / Ravi Teja Sukhavasi, Babak Hassibi 13. MMSE Estimation of Sparse Levy Processes / Ulugbek S. Kamilov, et al. 14. Quaternion VAR Modelling and Estimation / P. Ginzberg, A.T. Walden 15. Competing for Secrecy in the MISO Interference Channel / S. Ali A. Fakoorian, A. Lee Swidlehurst etc