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See detailDepth Super-Resolution by Enhanced Shift and Add
Al Ismaeil, Kassem UL; Aouada, Djamila UL; Mirbach, Bruno et al

in Computer Analysis of Images and Patterns, 15th International Conference, CAIP 2013, York, UK, August 27-29, 2013, Proceedings, Part II (2013)

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See detailMMSE Performance Analysis of Generalized Multibeam Satellite Channels
Christopoulos, Dimitrios UL; Arnau, Jesus; Chatzinotas, Symeon UL et al

in IEEE Wireless Communications Letters (2013), 17(7), 1332-1335

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See detailCapacity limits and multiplexing gains of MIMO channels with transceiver impairments
Bjornson, Emil; Zetterberg, P.; Bengtsson, M. et al

in IEEE Communications Letters (2013), 1(17), 91-94

The capacity of ideal MIMO channels has a high-SNR slope that equals the minimum of the number of transmit and receive antennas. This letter analyzes if this result holds when there are distortions from ... [more ▼]

The capacity of ideal MIMO channels has a high-SNR slope that equals the minimum of the number of transmit and receive antennas. This letter analyzes if this result holds when there are distortions from physical transceiver impairments. We prove analytically that such physical MIMO channels have a finite upper capacity limit, for any channel distribution and SNR. The high-SNR slope thus collapses to zero. This appears discouraging, but we prove the encouraging result that the relative capacity gain of employing MIMO is at least as large as with ideal transceivers. [less ▲]

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See detailCooperative cognitive networks: Optimal, distributed and low-complexity algorithms
Zheng, Gan UL; Song, Shenghui; Wong, Kai-Kit et al

in IEEE Transactions on Signal Processing (2013), 11(61), 2778-2790

This paper considers the cooperation between a cognitive system and a primary system where multiple cognitive base stations (CBSs) relay the primary user's (PU) signals in exchange for more opportunity to ... [more ▼]

This paper considers the cooperation between a cognitive system and a primary system where multiple cognitive base stations (CBSs) relay the primary user's (PU) signals in exchange for more opportunity to transmit their own signals. The CBSs use amplify-and-forward (AF) relaying and coordinated beamforming to relay the primary signals and transmit their own signals. The objective is to minimize the overall transmit power of the CBSs given the rate requirements of the PU and the cognitive users (CUs). We show that the relaying matrices have unity rank and perform two functions: Matched filter receive beamforming and transmit beamforming. We then develop two efficient algorithms to find the optimal solution. The first one has a linear convergence rate and is suitable for distributed implementation, while the second one enjoys superlinear convergence but requires centralized processing. Further, we derive the beamforming vectors for the linear conventional zero-forcing (CZF) and prior zero-forcing (PZF) schemes, which provide much simpler solutions. Simulation results demonstrate the improvement in terms of outage performance due to the cooperation between the primary and cognitive systems. [less ▲]

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See detailSimultaneous Estimation of Multi-Relay MIMO Channels
Mehrpouyan, H.; Blostein, S.D.; Ottersten, Björn UL

in IEEE Global Telecommunications Conference (GLOBECOM) (2013)

This paper addresses training-based channel estimation in distributed amplify-and-forward (AF) multi-input multi-output (MIMO) multi-relay networks. To reduce channel estimation overhead and delay, a ... [more ▼]

This paper addresses training-based channel estimation in distributed amplify-and-forward (AF) multi-input multi-output (MIMO) multi-relay networks. To reduce channel estimation overhead and delay, a training algorithm that allows for simultaneous estimation of the entire MIMO cooperative network’s channel parameters at the destination node is proposed. The exact Cram´er- Rao lower bound (CRLB) for the problem is presented in closedform. Channel estimators that are capable of estimating the overall source-relay-destination channel parameters at the destination are also derived. Numerical results show that while reducing delay, the proposed channel estimators are close to the derived CRLB over a wide range of signal-to-noise ratio values and outperform existing channel estimation methods. Finally, extensive simulations demonstrate that the proposed training method and channel estimators can be effectively deployed in combination with cooperative optimization algorithms to significantly enhance the performance of AF relaying MIMO systems in terms of average-bit-error-rate. [less ▲]

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See detailCost sensitive credit card fraud detection using bayes minimum risk
Bahnsen, A. C.; Stojanovic, Aleksandar UL; Aouada, D. et al

in Proceedings - 2013 12th International Conference on Machine Learning and Applications, ICMLA 2013 (2013), 1

Credit card fraud is a growing problem that affects card holders around the world. Fraud detection has been an interesting topic in machine learning. Nevertheless, current state of the art credit card ... [more ▼]

Credit card fraud is a growing problem that affects card holders around the world. Fraud detection has been an interesting topic in machine learning. Nevertheless, current state of the art credit card fraud detection algorithms miss to include the real costs of credit card fraud as a measure to evaluate algorithms. In this paper a new comparison measure that realistically represents the monetary gains and losses due to fraud detection is proposed. Moreover, using the proposed cost measure a cost sensitive method based on Bayes minimum risk is presented. This method is compared with state of the art algorithms and shows improvements up to 23% measured by cost. The results of this paper are based on real life transactional data provided by a large European card processing company. © 2013 IEEE. [less ▲]

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See detailReal-time depth enhancement by fusion for RGB-D cameras
Garcia Becerro, Frederic UL; Aouada, Djamila UL; Solignac, Thomas et al

in IET Computer Vision (2013), 7(5), 335345

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See detailConstructive Interference in Linear Precoding Systems: Power Allocation and User Selection
Christopoulos, Dimitrios; Chatzinotas, Symeon UL; Krikidis, Ioannis et al

in IEEE GlobeCom (2013)

The exploitation of interference in a constructive manner has recently been proposed for the downlink of multiuser, multi-antenna transmitters. This novel linear precoding technique, herein referred to as ... [more ▼]

The exploitation of interference in a constructive manner has recently been proposed for the downlink of multiuser, multi-antenna transmitters. This novel linear precoding technique, herein referred to as constructive interference zero forcing (CIZF) precoding, has exhibited substantial gains over conventional approaches; the concept is to cancel, on a symbol-by-symbol basis, only the interfering users that do not add to the intended signal power. In this paper, the power allocation problem towards maximizing the performance of a CIZF system with respect to some metric (throughput or fairness) is investigated. What is more, it is shown that the performance of the novel precoding scheme can be further boosted by choosing some of the constructive multiuser interference terms in the precoder design. Finally, motivated by the significant effect of user selection on conventional, zero forcing (ZF) precoding, the problem of user selection for the novel precoding method is tackled. A new iterative, low complexity algorithm for user selection in CIZF is developed. Simulation results are provided to display the gains of the algorithm compared to known user selection approaches. [less ▲]

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See detailMulti-frame super-resolution by enhanced shift & add
Al Ismaeil, Kassem UL; Aouada, D.; Ottersten, Björn UL et al

in International Symposium on Image and Signal Processing and Analysis, ISPA (2013)

A critical step in multi-frame super-resolution is the registration of frames based on their motion. We improve the performance of current state-of-the-art super-resolution techniques by proposing a more ... [more ▼]

A critical step in multi-frame super-resolution is the registration of frames based on their motion. We improve the performance of current state-of-the-art super-resolution techniques by proposing a more robust and accurate registration as early as in the initialization stage of the high resolution estimate. Indeed, we solve the limitations on scale and motion inherent to the classical Shift & Add approach by upsampling the low resolution frames up to the super-resolution factor prior to estimating motion or to median filtering. This is followed by an appropriate selective optimization, leading to an enhanced Shift & Add. Quantitative and qualitative evaluations have been conducted at two levels; the initial estimation and the final optimized superresolution. Results show that the proposed algorithm outperforms existing state-of-art methods. © 2013 University of Trieste and University of Zagreb. [less ▲]

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See detailSparse conjoint analysis through maximum likelihood estimation
Tsakonas, Efthymios; Jalden, J.; Sidiropoulos, N.D et al

in IEEE Transactions on Signal Processing (2013), 22

Conjoint analysis (CA) is a classical tool used in preference assessment, where the objective is to estimate the utility function of an individual, or a group of individuals, based on expressed preference ... [more ▼]

Conjoint analysis (CA) is a classical tool used in preference assessment, where the objective is to estimate the utility function of an individual, or a group of individuals, based on expressed preference data. An example is choice-based CA for consumer profiling, i.e., unveiling consumer utility functions based solely on choices between products. A statistical model for choice-based CA is investigated in this paper. Unlike recent classification-based approaches, a sparsity-aware Gaussian maximum likelihood (ML) formulation is proposed to estimate the model parameters. Drawing from related robust parsimonious modeling approaches, the model uses sparsity constraints to account for outliers and to detect the salient features that influence decisions. Contributions include conditions for statistical identifiability, derivation of the pertinent Cramér-Rao Lower Bound (CRLB), and ML consistency conditions for the proposed sparse nonlinear model. The proposed ML approach lends itself naturally to ℓ1-type convex relaxations which are well-suited for distributed implementation, based on the alternating direction method of multipliers (ADMM). A particular decomposition is advocated which bypasses the apparent need for outlier communication, thus maintaining scalability. The performance of the proposed ML approach is demonstrated by comparing against the associated CRLB and prior state-of-the-art using both synthetic and real data sets. [less ▲]

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See detailImproving Physical Layer Secrecy Using Full-Duplex Jamming Receivers
Zheng, Gan UL; Krikidis, Ioannis; Jiangyuan, Li et al

in IEEE Transactions on Signal Processing (2013), 20(61), 4962-4974

This paper studies secrecy rate optimization in a wireless network with a single-antenna source, a multi-antenna destination and a multi-antenna eavesdropper. This is an unfavorable scenario for secrecy ... [more ▼]

This paper studies secrecy rate optimization in a wireless network with a single-antenna source, a multi-antenna destination and a multi-antenna eavesdropper. This is an unfavorable scenario for secrecy performance as the system is interference-limited. In the literature, assuming that the receiver operates in half duplex (HD) mode, the aforementioned problem has been addressed via use of cooperating nodes who act as jammers to confound the eavesdropper. This paper investigates an alternative solution, which assumes the availability of a full duplex (FD) receiver. In particular, while receiving data, the receiver transmits jamming noise to degrade the eavesdropper channel. The proposed self-protection scheme eliminates the need for external helpers and provides system robustness. For the case in which global channel state information is available, we aim to design the optimal jamming covariance matrix that maximizes the secrecy rate and mitigates loop interference associated with the FD operation. We consider both fixed and optimal linear receiver design at the destination, and show that the optimal jamming covariance matrix is rank-1, and can be found via an efficient 1-D search. For the case in which only statistical information on the eavesdropper channel is available, the optimal power allocation is studied in terms of ergodic and outage secrecy rates. Simulation results verify the analysis and demonstrate substantial performance gain over conventional HD operation at the destination. [less ▲]

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See detailBeamformer designs for MISO broadcast channels with zero-forcing dirty paper coding
Le-Nam, Tran; Juntti, M.; Bengtsson, M. et al

in IEEE Transactions on Wireless Communications (2013), 3(12), 1173-1185

We consider the beamformer design for multiple-input multiple-output (MISO) broadcast channels (MISO BCs) using zero-forcing dirty paper coding (ZF-DPC). Assuming a sum power constraint (SPC), most ... [more ▼]

We consider the beamformer design for multiple-input multiple-output (MISO) broadcast channels (MISO BCs) using zero-forcing dirty paper coding (ZF-DPC). Assuming a sum power constraint (SPC), most previously proposed beamformer designs are based on the QR decomposition (QRD), which is a natural choice to satisfy the ZF constraints. However, the optimality of the QRD-based design for ZF-DPC has remained unknown. In this paper, first, we analytically establish that the QRD-based design is indeed optimal for any performance measure under a SPC. Then, we propose an optimal beamformer design method for ZF-DPC with per-antenna power constraints (PAPCs), using a convex optimization framework. The beamformer design is first formulated as a rank-1-constrained optimization problem. Exploiting the special structure of the ZF-DPC scheme, we prove that the rank constraint can be relaxed and still provide the same solution. In addition, we propose a fast converging algorithm to the beamformer design problem, under the duality framework between the BCs and multiple access channels (MACs). More specifically, we show that a BC with ZF-DPC has the dual MAC with ZF-based successive interference cancellation (ZF-SIC). In this way, the beamformer design for ZF-DPC is transformed into a power allocation problem for ZF-SIC, which can be solved more efficiently. [less ▲]

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See detailRobust MIMO Precoding for the Schatten Norm Based Channel Uncertainty Set
Wang, J.; Bengtsson, M.; Ottersten, Björn UL et al

in Signal Processing, IEEE Transactions on (2013)

The full potential of multi-input multi-output (MIMO) communication systems relies on exploiting channel state information at the transmitter (CSIT), which is, however, often subject to some uncertainty ... [more ▼]

The full potential of multi-input multi-output (MIMO) communication systems relies on exploiting channel state information at the transmitter (CSIT), which is, however, often subject to some uncertainty. In this paper, following the worst-case robust philosophy, we consider a robust MIMO precoding design with deterministic imperfect CSIT, formulated as a maximin problem, to maximize the worst-case received signal-to-noise ratio or minimize the worst-case error probability. Given different types of imperfect CSIT in practice, a unified framework is lacking in the literature to tackle various channel uncertainty. In this paper, we address this open problem by considering several classes of uncertainty sets that include most deterministic imperfect CSIT as special cases. We show that, for general convex uncertainty sets, the robust precoder, as the solution to the maximin problem, can be efficiently computed by solving a single convex optimization problem. Furthermore, when it comes to unitarily-invariant convex uncertainty sets, we prove the optimality of a channel-diagonalizing structure and simplify the complex-matrix problem to a real-vector power allocation problem, which is then analytically solved in a waterfilling manner. Finally, for uncertainty sets defined by a generic matrix norm, called the Schatten norm, we provide a fully closed-form solution to the robust precoding design, based on which the robustness of beamforming and uniform-power transmission is investigated. [less ▲]

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See detailWeighted sum rate maximization for MIMO broadcast channels using dirty paper coding and zero-forcing methods
Le-Nam, Tran; Juntti, M.; Bengtsson, M. et al

in IEEE Transactions on Communications (2013), 6(61), 2362-2373

We consider precoder design for maximizing the weighted sum rate (WSR) of successive zero-forcing dirty paper coding (SZF-DPC). For this problem, the existing precoder designs often assume a sum power ... [more ▼]

We consider precoder design for maximizing the weighted sum rate (WSR) of successive zero-forcing dirty paper coding (SZF-DPC). For this problem, the existing precoder designs often assume a sum power constraint (SPC) and rely on the singular value decomposition (SVD). The SVD-based designs are known to be optimal but require high complexity. We first propose a low-complexity optimal precoder design for SZF-DPC under SPC, using the QR decomposition. Then, we propose an efficient numerical algorithm to find the optimal precoders subject to per-antenna power constraints (PAPCs). To this end, the precoder design for PAPCs is formulated as an optimization problem with a rank constraint on the covariance matrices. A well-known approach to solve this problem is to relax the rank constraints and solve the relaxed problem. Interestingly, for SZF-DPC, we are able to prove that the rank relaxation is tight. Consequently, the optimal precoder design for PAPCs is computed by solving the relaxed problem, for which we propose a customized interior-point method that exhibits a superlinear convergence rate. Two suboptimal precoder designs are also presented and compared to the optimal ones. We also show that the proposed numerical method is applicable for finding the optimal precoders for block diagonalization scheme. [less ▲]

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See detailConnections between sparse estimation and robust statistical learning
Tsakonas, Efthymios; Jalden, J.; Sidiropoulos, N.D. et al

in Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on (2013)

Recent literature on robust statistical inference suggests that promising outlier rejection schemes can be based on accounting explicitly for sparse gross errors in the modeling, and then relying on ... [more ▼]

Recent literature on robust statistical inference suggests that promising outlier rejection schemes can be based on accounting explicitly for sparse gross errors in the modeling, and then relying on compressed sensing ideas to perform the outlier detection. In this paper, we consider two models for recovering a sparse signal from noisy measurements, possibly also contaminated with outliers. The models considered here are a linear regression model, and its natural one-bit counterpart where measurements are additionally quantized to a single bit. Our contributions can be summarized as follows: We start by providing conditions for identification and the Cramér-Rao Lower Bounds (CRLBs) for these two models. Then, focusing on the one-bit model, we derive conditions for consistency of the associated Maximum Likelihood estimator, and show the performance of relevant ℓ1-based relaxation strategies by comparing against the theoretical CRLB. [less ▲]

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See detailRobust MIMO precoding for several classes of channel uncertainty
Wang, J.; Bengtsson, M.; Ottersten, Björn UL et al

in IEEE Transactions on Signal Processing (2013), 12(61), 3056-3070

The full potential of multi-input multi-output (MIMO) communication systems relies on exploiting channel state information at the transmitter (CSIT), which is, however, often subject to some uncertainty ... [more ▼]

The full potential of multi-input multi-output (MIMO) communication systems relies on exploiting channel state information at the transmitter (CSIT), which is, however, often subject to some uncertainty. In this paper, following the worst-case robust philosophy, we consider a robust MIMO precoding design with deterministic imperfect CSIT, formulated as a maximin problem, to maximize the worst-case received signal-to-noise ratio or minimize the worst-case error probability. Given different types of imperfect CSIT in practice, a unified framework is lacking in the literature to tackle various channel uncertainty. In this paper, we address this open problem by considering several classes of uncertainty sets that include most deterministic imperfect CSIT as special cases. We show that, for general convex uncertainty sets, the robust precoder, as the solution to the maximin problem, can be efficiently computed by solving a single convex optimization problem. Furthermore, when it comes to unitarily-invariant convex uncertainty sets, we prove the optimality of a channel-diagonalizing structure and simplify the complex-matrix problem to a real-vector power allocation problem, which is then analytically solved in a waterfilling manner. Finally, for uncertainty sets defined by a generic matrix norm, called the Schatten norm, we provide a fully closed-form solution to the robust precoding design, based on which the robustness of beamforming and uniform-power transmission is investigated. [less ▲]

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See detailTransceiver design for distributed STBC based AF cooperative networks in the presence of timing and frequency offsets
Nasir, A.A.; Mehrpouyan, H.; Durrani, S. et al

in IEEE Transactions on Signal Processing (2013), 12(61), 3143-3158

In multi-relay cooperative systems, the signal at the destination is affected by impairments such as multiple channel gains, multiple timing offsets (MTOs), and multiple carrier frequency offsets (MCFOs ... [more ▼]

In multi-relay cooperative systems, the signal at the destination is affected by impairments such as multiple channel gains, multiple timing offsets (MTOs), and multiple carrier frequency offsets (MCFOs). In this paper we account for all these impairments and propose a new transceiver structure at the relays and a novel receiver design at the destination in distributed space-time block code (DSTBC) based amplify-and-forward (AF) cooperative networks. The Cramér-Rao lower bounds and a least squares (LS) estimator for the multi-parameter estimation problem are derived. In order to significantly reduce the receiver complexity at the destination, a differential evolution (DE) based estimation algorithm is applied and the initialization and constraints for the convergence of the proposed DE algorithm are investigated. In order to detect the signal from multiple relays in the presence of unknown channels, MTOs, and MCFOs, novel optimal and sub-optimal minimum mean-square error receiver designs at the destination node are proposed. Simulation results show that the proposed estimation and compensation methods achieve full diversity gain in the presence of channel and synchronization impairments in multi-relay AF cooperative networks. [less ▲]

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See detailOptimal training sequences for joint timing synchronization and channel estimation in distributed communication networks
Nasir, Ali A.; Mehrpouyan, Hani; Durrani, Salman et al

in IEEE Transactions on Communications (2013), 7(61), 3002-3015

For distributed multi-user and multi-relay cooperative networks, the received signal may be affected by multiple timing offsets (MTOs) and multiple channels that need to be jointly estimated for ... [more ▼]

For distributed multi-user and multi-relay cooperative networks, the received signal may be affected by multiple timing offsets (MTOs) and multiple channels that need to be jointly estimated for successful decoding at the receiver. This paper addresses the design of optimal training sequences for efficient estimation of MTOs and multiple channel parameters. A new hybrid Cramer-Rao lower bound (HCRB) for joint estimation of MTOs and channels is derived. Subsequently, by minimizing the derived HCRB as a function of training sequences, three training sequence design guidelines are derived and according to these guidelines, two training sequences are proposed. In order to show that the proposed design guidelines also improve estimation accuracy, the conditional Cramer-Rao lower bound (ECRB), which is a tighter lower bound on the estimation accuracy compared to the HCRB, is also derived. Numerical results show that the proposed training sequence design guidelines not only lower the HCRB, but they also lower the ECRB and the mean-square error of the proposed maximum a posteriori estimator. Moreover, extensive simulations demonstrate that application of the proposed training sequences significantly lowers the bit-error rate performance of multi-relay cooperative networks when compared to training sequences that violate these design guidelines. [less ▲]

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See detailDSTBC based DF cooperative networks in the presence of timing and frequency offsets
Nasir, A.A.; Mehrpouyan, H.; Durrani, S. et al

in Signal Processing Advances in Wireless Communications (SPAWC), 2013 IEEE 14th Workshop on (2013)

In decode-and-forward (DF) relaying networks, the received signal at the destination may be affected by multiple impairments such as multiple channel gains, multiple timing offsets (MTOs), and multiple ... [more ▼]

In decode-and-forward (DF) relaying networks, the received signal at the destination may be affected by multiple impairments such as multiple channel gains, multiple timing offsets (MTOs), and multiple carrier frequency offsets (MCFOs). This paper proposes novel optimal and sub-optimal minimum mean-square error (MMSE) receiver designs at the destination node to detect the signal in the presence of these impairments. Distributed space-time block codes (DSTBCs) are used at the relays to achieve spatial diversity. The proposed sub-optimal receiver uses the estimated values of multiple channel gains, MTOs, and MCFOs, while the optimal receiver assumes perfect knowledge of these impairments at the destination and serves as a benchmark performance measure. To achieve robustness to estimation errors, the estimates statistical properties are exploited at the destination. Simulation results show that the proposed optimal and sub-optimal MMSE compensation receivers achieve full diversity gain in the presence of channel and synchronization impairments in DSTBC based DF cooperative networks. [less ▲]

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See detailSpectrum Sensing in Dual Polarized Fading Channels for Cognitive SatComs
Sharma, Shree Krishna UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in Proceedings of IEEE Globecom Conference 2012 (2012, December)

Next generation networks are moving towards the convergence of mobile, fixed and broadcasting services in one standard platform, which requires the co-existence of satellite and terrestrial networks in ... [more ▼]

Next generation networks are moving towards the convergence of mobile, fixed and broadcasting services in one standard platform, which requires the co-existence of satellite and terrestrial networks in the same spectrum. This framework has motivated the concept of cognitive Satellite Communication (SatComs). In this aspect, the problem of exploiting Spectrum Sensing (SS) techniques for a dual polarized fading channel is considered. In this paper, the performance of Energy Detection (ED) technique is evaluated in the context of a co-existence scenario of a satellite and a terrestrial link. Diversity combining techniques such as Equal Gain Combining (EGC) and Selection Combining (SC) are considered to enhance the SS efficiency. Furthermore, analytical expressions for probability of detection (Pd) and probability of false alarm (Pf ) are presented for these techniques in the considered fading channel and the sensing performance is studied through analytical and simulation results. Moreover, the effect of Cross Polar Discrimination (XPD) on the sensing performance is presented and it is shown that SS efficiency improves for low XPD. [less ▲]

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