Search

In this paper, a method for determining ground plane features in a sequence of images captured by a mobile camera is presented. The hardware of the mobile system consists of a monocular camera that is mounted on an inertial measurement unit (IMU). An image processing procedure is proposed, first to extract image features and match them across consecutive image frames, and second to detect the ground plane features using a two-step algorithm. In the first step, the planar homography of the ground plane is constructed using an IMU-camera motion estimation approach. The obtained homography constraints are used to detect the most likely ground features in the sequence of images. To reject the remaining outliers, as the second step, a new plane normal vector computation approach is proposed. To obtain the normal vector of the ground plane, only three pairs of corresponding features are used for a general camera transformation. The normal-based computation approach generalizes the existing methods that are developed for specific camera transformations. Experimental results on real data validate the reliability of the proposed method., QC 20121107

This work addresses the problem of cooperative spectrum sensing in cognitive radio networks, focusing on the impact of mobility on performance of cooperative sensing. First, a review of the most recent results on cooperative spectrum sensing is provided, resulting in the identification of measurement correlation and frame error rate in the reporting channel as the main parameters influencing the performance of cooperative sensing schemes. Next, the paper discusses the extension of the analysis to the case of mobile sensors, and determines the set of assumptions made in existing literature when taking into account mobility in sensing. The paper moves then to remove some of such assumptions, by presenting simulation results obtained in presence of realistic models for propagation in the considered area, as well as of a realistic mobility model. A comparison between theoretical derivation and simulation results shows that correlation among measurements taken by different sensors and the selected mobility model may significantly affect the sensing performance., QC 20130128

We investigate the design of optimized input distributions for the two-hop Gaussian relay channel under an average power constraint. In our study, the relay is confined to implement an estimate-and-forward strategy. We demonstrate that the rate achievable by an optimized discrete input distribution can significantly outperform that achievable by a Gaussian codebook. The lower bound obtained by the optimized EF scheme is also used to establish an improved lower bound on the rates achievable by compress-and-forward., QC 20130122

This paper proposes two new coding schemes for the discretememoryless two-way relay channel. The main target is to show thebenefits of compress-forward without Wyner-Ziv binning and oflayered relaying in networks wherein a relay is to help multipledestinations, that may have unequal channel quality and/or haveaccess to different side information. Numerical results for aGaussian channel show that the new coding schemes outperformvariants of compress-forward relaying and offer a good trade-offbetween achievable rates and complexity and decoding delay. The ideacan also be applied to other relay networks., QC 20121115

This paper studies linear coding (LC) techniques in the setting of computing functions of correlated memoryless sources. Instead of linear mappings over finite fields, we consider using linear mappings over finite rings as encoders. It is shown that generally the region c×R, where c ≥ 1 is a constant and R is the Slepian-Wolf (SW) region, is achievable with LC over ring (LCoR) when the function to compute is the identity function. c = 1 if the ring used is a field. Hence, LCoR could be suboptimal in terms of achieving the best coding rates (the SW region) for computing the identity function. In spite of that, the ring version shows several advantages. It is demonstrated that there exists a function that is neither linear nor can be linearized over any finite field. Thus, LC over field (LCoF) does not apply directly for computing such a function unless the polynomial approach [1], [2] is used. On the contrary, such a function is linear over some ring. Using LCoR, an achievable region containing the SW region can be obtained for computing this function. In addition, the alphabet sizes of the encoders are strictly smaller than using LCoF. More interestingly, LCoF is not useful if some special requirement is imposed., QC 20130104

The remote stabilization of a first order linear plant over a wireless channel is studied. The plant is assumed to have an arbitrary distributed initial state and the wireless channel between the plant's sensor and the controller is modeled as a white Gaussian channel subject to an external interference signal. In order to combat the interference a dedicated sensor (relay) node is deployed adjacent to the interferer, which relays the interference information to both the plant's sensor and the controller. The sensor and the controller utilize this information to mitigate interference. We use delay-free linear sensing and control scheme in order to derive sufficient conditions for mean square stability. The achievable stability region significantly enlarges with the relay assisted interference cancelation scheme. Moreover the effect of interference can be completely eliminated if the encoder knows all the future values of the interference., QC 20130218

We consider a problem of constrained multi-stage coding for channels with a rewrite option. It is a natural extension of Weissman's channels with action-dependent states to the multistage coding case where an encoder in each stage observes its own message as well as all previous-stage messages, inputs, and outputs. In addition to decoding all messages at the final stage, the new reconstruction constraint introduced in Sumszyk and Steinberg's information embedding with reversible stegotext is imposed on the problem such that the decoder is required to be able to reconstruct all channel input sequences reliably. The complete characterization of the channel capacity region is given for the two-stage case, while the inner and outer bounds to the capacity regions for the cases of three or more stages are provided. For the two-stage case, a discussion regarding the rate constraint of the message in the second stage is also given in which we can draw a connection to the two-stage coding condition which appears in our previous study on channel with action-dependent state and reversible input., QC 20121119

A pair of secondary (cognitive, unlicensed) users is communicating in the presence of multiple primary (licensed) user pairs. The cognitive transceiver is implementing beamforming and orthogonal space-time block coding in the presence of external interference, induced by the primary system transmission, that has to be properly handled. Moreover, the cognitive link nodes, both the transmitter and the receiver, are supplied with different levels of network side information (NSI), i.e. primary messages and partial channel side information (CSI). We investigate how this side information can be taken into account in the cognitive system design and how interference affects the behaviour of the beamforming solution. Through numerical simulations, we illustrate the impact of partial CSI on system performance and discuss its implications on the feasibility of cognitive systems., QC 20121218

We consider a pair of secondary nodes (SU) coupled, in Z-topology, with multiple pairs of primary nodes (PU). The secondary (cognitive) transmitter is combining beamforming with orthogonal space-time block coding (BOSTBC) and operates under Quality-of-Service (QoS) constraints that must be guaranteed for the primary receivers (PURx). The cognitive link is designed assuming imperfect channel state information (CSI) for all links, available at the SU transmitter (SUTx). Under this premise we characterize the optimal design in terms of CSI quality and interference and evaluate their impact on the performance of BOSTBC transmission in underlay cognitive networks., QC 20130116

Compressive Sampling Matching Pursuit (CoSaMP) is one of the popular greedy methods in the emerging field of Compressed Sensing (CS). In addition to the appealing empirical performance, CoSaMP has also splendid theoretical guarantees for convergence. In this paper, we propose a modification in CoSaMP to adaptively choose the dimension of search space in each iteration, using a threshold based approach. Using Monte Carlo simulations, we show that this modification improves the reconstruction capability of the CoSaMP algorithm in clean as well as noisy measurement cases. From empirical observations, we also propose an optimum value for the threshold to use in applications., QC 20130226

The two-user discrete memoryless state-dependent multiple-access channel with cooperating encoders is considered. It is assumed that the channel is controlled with two independent states such that each of the channel state information is noncausally available at one encoder. Moreover, based on the intrinsic characteristic of wireless networks, it is assumed that each encoder strictly causally receive a noisy version of the transmitted signal of the other encoder. Hence, the encoders can cooperate in transmitting the message to the receiver. An achievable rate region for the channel is derived by use of rate splitting, block Markov encoding and Gelfand-Pinsker multilevel encoding along with partial decoding at the encoders and backward decoding at the receiver. Finally, for a Gaussian channel model the proposed achievable rate region is evaluated and discussed., QC 20130118

This paper studies the asymptotic sum-rate of the primary network within the relay-assisted multi-antenna cognitive radio system performing amplify-and-forward relaying. The achievable sum-rates are derived in the large-system limit by means of the replica method. A closed-form expression for the sum-rate of the primary network is obtained for large antenna arrays as a function of parameters obtained by solving a set of fixed-point equations. Numerical simulations confirm the validity of the results even for systems with only a few antennas at each terminal., QC 20121219

A secret key agreement setup between three users is considered in which each pair of them wishes to agree on a secret key hidden from the remaining user. The three users observe i.i.d. outputs of correlated sources and there is a noiseless public channel from each user for communication to the others. In this setup, inner and outer bounds of the secret key capacity region is derived. Moreover, some special cases are obtained in which the inner bound coincides the explicit outer bound. Also a binary-erasure example is presented through which the results are examined., QC 20130115

We consider the source coding problem of computing functions of correlated sources, which is an extension of the Slepian - Wolf coding problem. We observe that all the discrete functions are in fact restrictions of polynomial functions over some finite field. Based on this observation, we demonstrate how to use Elias' Lemma to enlarge the coding rate region (compared to the Slepian - Wolf region) for a certain class of polynomial functions. We present a classification result about polynomial functions regarding this coding problem. The result is conclusive in the two-sources scenario and, in fact, gives another interpretation of a result by Han and Kobayashi [1, Theorem 1]., QC 20121115

In this paper, we improve iterative greedy search algorithms in which atoms are selected serially over iterations, i.e., one-by-one over iterations. For serial atom selection, we devise two new schemes to select an atom from a set of potential atoms in each iteration. The two new schemes lead to two new algorithms. For both the algorithms, in each iteration, the set of potential atoms is found using a standard matched filter. In case of the first scheme, we propose an orthogonal projection strategy that selects an atom from the set of potential atoms. Then, for the second scheme, we propose a look-ahead strategy such that the selection of an atom in the current iteration has an effect on the future iterations. The use of look-ahead strategy requires a higher computational resource. To achieve a tradeoff between performance and complexity, we use the two new schemes in cascade and develop a third new algorithm. Through experimental evaluations, we compare the proposed algorithms with existing greedy search and convex relaxation algorithms., QC 20120227

In this paper, we improve iterative greedy search algorithms in which atoms are selected serially over iterations, i.e., one-by-one over iterations. For serial atom selection, we devise two new schemes to select an atom from a set of potential atoms in each iteration. The two new schemes lead to two new algorithms. For both the algorithms, in each iteration, the set of potential atoms is found using a standard matched filter. In case of the first scheme, we propose an orthogonal projection strategy that selects an atom from the set of potential atoms. Then, for the second scheme, we propose a look-ahead strategy such that the selection of an atom in the current iteration has an effect on the future iterations. The use of look-ahead strategy requires a higher computational resource. To achieve a tradeoff between performance and complexity, we use the two new schemes in cascade and develop a third new algorithm. Through experimental evaluations, we compare the proposed algorithms with existing greedy search and convex relaxation algorithms., QC 20120227

In this paper, we improve iterative greedy search algorithms in which atoms are selected serially over iterations, i.e., one-by-one over iterations. For serial atom selection, we devise two new schemes to select an atom from a set of potential atoms in each iteration. The two new schemes lead to two new algorithms. For both the algorithms, in each iteration, the set of potential atoms is found using a standard matched filter. In case of the first scheme, we propose an orthogonal projection strategy that selects an atom from the set of potential atoms. Then, for the second scheme, we propose a look-ahead strategy such that the selection of an atom in the current iteration has an effect on the future iterations. The use of look-ahead strategy requires a higher computational resource. To achieve a tradeoff between performance and complexity, we use the two new schemes in cascade and develop a third new algorithm. Through experimental evaluations, we compare the proposed algorithms with existing greedy search and convex relaxation algorithms., QC 20120227

In this paper, we improve iterative greedy search algorithms in which atoms are selected serially over iterations, i.e., one-by-one over iterations. For serial atom selection, we devise two new schemes to select an atom from a set of potential atoms in each iteration. The two new schemes lead to two new algorithms. For both the algorithms, in each iteration, the set of potential atoms is found using a standard matched filter. In case of the first scheme, we propose an orthogonal projection strategy that selects an atom from the set of potential atoms. Then, for the second scheme, we propose a look-ahead strategy such that the selection of an atom in the current iteration has an effect on the future iterations. The use of look-ahead strategy requires a higher computational resource. To achieve a tradeoff between performance and complexity, we use the two new schemes in cascade and develop a third new algorithm. Through experimental evaluations, we compare the proposed algorithms with existing greedy search and convex relaxation algorithms., QC 20120227

In this paper, we improve iterative greedy search algorithms in which atoms are selected serially over iterations, i.e., one-by-one over iterations. For serial atom selection, we devise two new schemes to select an atom from a set of potential atoms in each iteration. The two new schemes lead to two new algorithms. For both the algorithms, in each iteration, the set of potential atoms is found using a standard matched filter. In case of the first scheme, we propose an orthogonal projection strategy that selects an atom from the set of potential atoms. Then, for the second scheme, we propose a look-ahead strategy such that the selection of an atom in the current iteration has an effect on the future iterations. The use of look-ahead strategy requires a higher computational resource. To achieve a tradeoff between performance and complexity, we use the two new schemes in cascade and develop a third new algorithm. Through experimental evaluations, we compare the proposed algorithms with existing greedy search and convex relaxation algorithms., QC 20120227

For compressive sensing, we endeavor to improve the atom selection strategy of the existing orthogonal matching pursuit (OMP) algorithm. To achieve a better estimate of the underlying support set progressively through iterations, we use a least squares solution based atom selection method. From a set of promising atoms, the choice of an atom is performed through a new method that uses orthogonal projection along-with a standard matched filter. Through experimental evaluations, the effect of projection based atom selection strategy is shown to provide a significant improvement for the support set recovery performance, in turn, the compressive sensing recovery., QC 20120803

In this work the multiantenna bidirectional broadcast channel under channel uncertainty is studied. This problem is motivated by the broadcast phase of the decode-and-forward bidirectional relaying protocol, where a relay node establishes a bidirectional communication between two other nodes while having only imperfect channel state information available. Different uncertainty models are investigated, where the nominal channels experience either a multiplicative or additive perturbation based on a spectral norm constraint. For these uncertainty models the corresponding capacity regions of the multiantenna bidirectional broadcast channel are analyzed. Further, robust transmit strategies are characterized and worst-case perturbations are identified., QC 20120625

A secret key agreement setup between three users is considered in which each of the users 1 and 2 intends to share a secret key with user 3 and users 1 and 2 are eavesdroppers with respect to each other. The three users observe i.i.d. outputs of correlated sources and there is a generalized discrete memoryless multiple access channel (GDMMAC) from users 1 and 2 to user 3 for communication between the users. The secret key agreement is established using the correlated sources and the GDMMAC. In this setup, inner and outer bounds of the secret key capacity region are investigated. Moreover, for a special case where the channel inputs and outputs and the sources form Markov chains in some order, the secret key capacity region is derived. Also a Gaussian case is considered in this setup., QC 20130115

We study secret-key agreement over a non-coherent block-fading multiple input multiple output (MIMO) wiretap channel. We give an achievable scheme based on training and source emulation and analyze the rate in the high SNR regime. Based on this analysis we find the optimal number of antennas to use for training. Our main result is that if the sum of the number of antennas at Alice and Bob is larger than the coherence time of the channel, the achievable rate does not depend on the number of antennas at Eve. In this case source emulation is not needed, and using only training is optimal. We also consider the case when there is no public channel available. In this case we show that secret-key agreement is still possible by using the wireless channel for discussion, giving the same number of secure degrees of freedom as in the case with a public channel., QC 20130220

We consider a lossless multi-terminal source coding problem with one transmitter, two receivers and side information. The achievable rate region of the problem is not well understood. In this paper, we characterise the rate region when the side information at one receiver is conditionally less noisy than the side information at the other, given this other receiver's desired source. The conditionally less noisy definition includes degraded side information and a common message as special cases, and it is motivated by the concept of less noisy broadcast channels. The key contribution of the paper is a new converse theorem employing a telescoping identity and the Csiszár sum identity., QC 20130219

We consider a lossless multi-terminal source coding problem with one transmitter, two receivers and side information. The achievable rate region of the problem is not well understood. In this paper, we characterise the rate region when the side information at one receiver is conditionally less noisy than the side information at the other, given this other receiver's desired source. The conditionally less noisy definition includes degraded side information and a common message as special cases, and it is motivated by the concept of less noisy broadcast channels. The key contribution of the paper is a new converse theorem employing a telescoping identity and the Csiszár sum identity., QC 20130219

We consider a lossless multi-terminal source coding problem with one transmitter, two receivers and side information. The achievable rate region of the problem is not well understood. In this paper, we characterise the rate region when the side information at one receiver is conditionally less noisy than the side information at the other, given this other receiver's desired source. The conditionally less noisy definition includes degraded side information and a common message as special cases, and it is motivated by the concept of less noisy broadcast channels. The key contribution of the paper is a new converse theorem employing a telescoping identity and the Csiszár sum identity., QC 20130219

We consider a lossless multi-terminal source coding problem with one transmitter, two receivers and side information. The achievable rate region of the problem is not well understood. In this paper, we characterise the rate region when the side information at one receiver is conditionally less noisy than the side information at the other, given this other receiver's desired source. The conditionally less noisy definition includes degraded side information and a common message as special cases, and it is motivated by the concept of less noisy broadcast channels. The key contribution of the paper is a new converse theorem employing a telescoping identity and the Csiszár sum identity., QC 20130219

We consider a lossless multi-terminal source coding problem with one transmitter, two receivers and side information. The achievable rate region of the problem is not well understood. In this paper, we characterise the rate region when the side information at one receiver is conditionally less noisy than the side information at the other, given this other receiver's desired source. The conditionally less noisy definition includes degraded side information and a common message as special cases, and it is motivated by the concept of less noisy broadcast channels. The key contribution of the paper is a new converse theorem employing a telescoping identity and the Csiszár sum identity., QC 20130219

Orthogonal Matching Pursuit (OMP) is a popular greedy pursuit algorithm widely used for sparse signal recovery from an undersampled measurement system. However, one of the main shortcomings of OMP is its irreversible selection procedure of columns of measurement matrix. i.e., OMP does not allow removal of the columns wrongly estimated in any of the previous iterations. In this paper, we propose a modification in OMP, using the well known Subspace Pursuit (SP), to refine the subspace estimated by OMP at any iteration and hence boost the sparse signal recovery performance of OMP. Using simulations we show that the proposed scheme improves the performance of OMP in clean and noisy measurement cases., QC 20130226

We propose a new unequal error protection (UEP) scheme for Luby Transform (LT) codes over additive white Gaussian noise (AWGN) channels. In contrast to the state-of-the-art UEP scheme for LT codes where the effective code rates are exploited for UEP, we characterize the variable-node degree distribution to achieve UEP for LT codes. For performance analysis, we compare the lower bounds on bit error rate for our proposed scheme and a conventional UEP-based LT codes over AWGN channels for various parameters. Moreover, it is demonstrated through numerical examples that our proposed UEP scheme has better performance than the conventional UEP-based LT codes over a wide range of code rates and channel conditions., QC 20130116

Well-known standard hybrid coding techniques utilize the concept of motion-compensated predictive coding in a closed-loop. The resulting coding dependencies are a major challenge for packet-based networks like the Internet. On the other hand, subband coding techniques avoid the dependencies of predictive coding and are able to generate video streams that better match packet-based networks. An interesting class for subband coding is the so-called motion-compensated orthogonal transform. It generates orthogonal subband coefficients for arbitrary underlying motion fields. In this paper, a theoretical signal model based on Gaussian distributions is discussed to construct a cost function for efficient rate allocation. Additionally, a rate-distortion efficient video coding scheme is developed that takes advantage of motion-compensated orthogonal transforms. The scheme combines multiple types of motion-compensated orthogonal transforms, variable block sizes, and half-pel accurate motion compensation. The experimental results show that this adaptive scheme outperforms individual motion-compensated orthogonal transforms by up to 2 dB., QC 20120807

Various system tasks like interference coordination, handover decisions, admission control etc. in upcoming cellular networks require precise mid-term (spanning over a few seconds) performance models. Due to channel-dependent scheduling at the base station, these performance models are not simple to obtain. Furthermore, upcoming cellular systems will be interference-limited, hence, the way interference is modeled is crucial for the accuracy. In this paper we present an analytical model for the SINR distribution of the scheduled subcarriers of an OFDMA system with proportional fair scheduling. The model takes the precise SINR distribution into account. We furthermore refine our model with respect to uniform modulation and coding, as applied in LTE networks. The derived models are validated by means of simulations. In additon, we show that our models are approximate estimators for the performance of rate-based proportional fair scheduling, while they outperform some simpler prediction models from related work significantly., QC 20140102

Various system tasks like interference coordination, handover decisions, admission control etc. in upcoming cellular networks require precise mid-term (spanning over a few seconds) performance models. Due to channel-dependent scheduling at the base station, these performance models are not simple to obtain. Furthermore, upcoming cellular systems will be interference-limited, hence, the way interference is modeled is crucial for the accuracy. In this paper we present an analytical model for the SINR distribution of the scheduled subcarriers of an OFDMA system with proportional fair scheduling. The model takes the precise SINR distribution into account. We furthermore refine our model with respect to uniform modulation and coding, as applied in LTE networks. The derived models are validated by means of simulations. In additon, we show that our models are approximate estimators for the performance of rate-based proportional fair scheduling, while they outperform some simpler prediction models from related work significantly., QC 20140102

Various system tasks like interference coordination, handover decisions, admission control etc. in upcoming cellular networks require precise mid-term (spanning over a few seconds) performance models. Due to channel-dependent scheduling at the base station, these performance models are not simple to obtain. Furthermore, upcoming cellular systems will be interference-limited, hence, the way interference is modeled is crucial for the accuracy. In this paper we present an analytical model for the SINR distribution of the scheduled subcarriers of an OFDMA system with proportional fair scheduling. The model takes the precise SINR distribution into account. We furthermore refine our model with respect to uniform modulation and coding, as applied in LTE networks. The derived models are validated by means of simulations. In additon, we show that our models are approximate estimators for the performance of rate-based proportional fair scheduling, while they outperform some simpler prediction models from related work significantly., QC 20140102

Various system tasks like interference coordination, handover decisions, admission control etc. in upcoming cellular networks require precise mid-term (spanning over a few seconds) performance models. Due to channel-dependent scheduling at the base station, these performance models are not simple to obtain. Furthermore, upcoming cellular systems will be interference-limited, hence, the way interference is modeled is crucial for the accuracy. In this paper we present an analytical model for the SINR distribution of the scheduled subcarriers of an OFDMA system with proportional fair scheduling. The model takes the precise SINR distribution into account. We furthermore refine our model with respect to uniform modulation and coding, as applied in LTE networks. The derived models are validated by means of simulations. In additon, we show that our models are approximate estimators for the performance of rate-based proportional fair scheduling, while they outperform some simpler prediction models from related work significantly., QC 20140102

Various system tasks like interference coordination, handover decisions, admission control etc. in upcoming cellular networks require precise mid-term (spanning over a few seconds) performance models. Due to channel-dependent scheduling at the base station, these performance models are not simple to obtain. Furthermore, upcoming cellular systems will be interference-limited, hence, the way interference is modeled is crucial for the accuracy. In this paper we present an analytical model for the SINR distribution of the scheduled subcarriers of an OFDMA system with proportional fair scheduling. The model takes the precise SINR distribution into account. We furthermore refine our model with respect to uniform modulation and coding, as applied in LTE networks. The derived models are validated by means of simulations. In additon, we show that our models are approximate estimators for the performance of rate-based proportional fair scheduling, while they outperform some simpler prediction models from related work significantly., QC 20140102

Bidirectional wireless communication between two multi-antenna terminals that operate in a full-duplex mode is considered. The effects of loopback self-interference and transmit-side noise due to radio front-end imperfections are analyzed in the asymptotic regime where the number of antennas at both terminals grows large. The study compares two transparent mitigation schemes by which conventional spatial multiplexing can operate without being aware of the self-interference issue: spatial-domain null-space projection and time-domain subtractive cancellation. Both schemes eliminate the information-bearing part of the self-interference perfectly, but due to transmitter noise, the subtractive cancellation suffers from residual self-interference. The receive-side null-space projection, on the other hand, suppresses also the transmit-side noise, but at the cost of reduction in the degrees of freedom available for data reception. The results indicate that suppression becomes preferred when the level of transmit-side noise increases and the receiver does not have instantaneous knowledge about the spatial structure of the self-interference. Exhaustive Monte Carlo simulations also show that the asymptotic analytical results are useful for evaluating the performance of practical not-so-large systems., QC 20140217

This paper studies a new model for cooperative communication, the interfering relay channels. We show that thehash-forward scheme introduced by Kim for the primitive relay channel is capacity achieving for a class of semideterministic interfering relay channels. The obtained capacity result generalizes and unifies earlier capacity results for a class of primitive relay channels and a class of deterministic interference channels., QC 20140225

We consider a distributed detection problem where two nodes, or decision makers, observe a common source and aim to decide on one of several hypotheses. Before making their individual decisions, the nodes are allowed to communicate over rate-constrained links, through a bidirectional relay. We show that if the rate of the common relay-to-node link is greater than or equal to the rate of the individual node-to-relay links, and the individual decisions are not coupled by the cost metric, then network coding at the relay allows the overall problem to decouple into two separate two-node distributed detection problems over serial networks; and the two serial networks can be designed independently. However, if the rate of the relay-to-node link is strictly less than the node-to-relay links, no such decoupling can be assumed in general, and the overall detection network needs to be jointly designed., QC 20131210

A transmission scheme for mean square stabilization of two linear systems over a Gaussian interference relay channel is studied. A delay-free linear sensing and control strategy is proposed and an achievable stability region is derived. It shows that the stability region can be significantly enlarged by deploying a relay node in such a multi-user Gaussian channels. Furthermore we observe that the separation structure between estimation and control is inadequate in high interference regime., QC 20140121

In this paper, we propose two algorithms to construct motion-adaptive transforms that are based on vertex-weighted graphs. The graphs are constructed by motion vector information. The weights of the vertices are given by scale factors that are used to accommodate proper concentration of energy in transforms. The vertex-weighted graph defines a one dimensional linear subspace. Thus, our transform basis is subspace constrained. We propose two algorithms. The first is based on the Gram-Schmidt orthonormalization of the discrete cosine transform (DCT) basis. The second combines the rotation of the DCT basis and the Gram-Schmidt orthonormalization. We assess both algorithms in terms of energy compaction. Moreover, we compare to prior work on graph-based rotation of the DCT basis and on so-called motion-compensated orthogonal transforms (MCOT). In our experiments, both algorithms outperform MCOT in terms of energy compaction. However, their performance is similar to that of graph-based rotation of the DCT basis., QC 20140312

This paper investigates amplify-and-forward (AF) relaying for secrecy in quasi-static Rayleigh fading channels. We consider a four-node network where a helping node intends to enhance secrecy of the transmission between the source and the destination in presence of a passive eavesdropper. In this scenario, the common assumption of full CSI on the eavesdropper's channels is not realistic, and thus, we study the performance of cooperation from an outage perspective. Starting from the secrecy outage probability, we introduce a novel measure, the conditional secrecy outage probability to analyze the performance of AF. In particular, we derive closed-form expressions for AF for these two secrecy measures under a high SNR assumption. Moreover, we use numerical examples to illustrate our results and to characterize the effect of the nodes' geometry. We also show numerically how AF improves the secrecy performance in comparison to direct transmission in terms of outage probability and secure throughput., QC 20131112

In this work, we study the so-called leakage minimization problem, within the context of interference alignment (IA). For that purpose, we propose a novel approach based on controlled perturbations of the leakage function, and show how the latter can be used as a mechanism to control the algorithm's convergence (and thus tradeoff convergence speed for reliability). Although the proposed scheme falls under the broad category of stochastic optimization, we show through simulations that it has a quasi-deterministic convergence that we exploit to improve on the worst case performance of its predecessor, resulting in significantly better sum-rate capacity and average cost function value., QC 20140602, METIS

In this work, we study the so-called leakage minimization problem, within the context of interference alignment (IA). For that purpose, we propose a novel approach based on controlled perturbations of the leakage function, and show how the latter can be used as a mechanism to control the algorithm's convergence (and thus tradeoff convergence speed for reliability). Although the proposed scheme falls under the broad category of stochastic optimization, we show through simulations that it has a quasi-deterministic convergence that we exploit to improve on the worst case performance of its predecessor, resulting in significantly better sum-rate capacity and average cost function value., QC 20140602, METIS

In this work, we study the so-called leakage minimization problem, within the context of interference alignment (IA). For that purpose, we propose a novel approach based on controlled perturbations of the leakage function, and show how the latter can be used as a mechanism to control the algorithm's convergence (and thus tradeoff convergence speed for reliability). Although the proposed scheme falls under the broad category of stochastic optimization, we show through simulations that it has a quasi-deterministic convergence that we exploit to improve on the worst case performance of its predecessor, resulting in significantly better sum-rate capacity and average cost function value., QC 20140602, METIS

In this work, we study the so-called leakage minimization problem, within the context of interference alignment (IA). For that purpose, we propose a novel approach based on controlled perturbations of the leakage function, and show how the latter can be used as a mechanism to control the algorithm's convergence (and thus tradeoff convergence speed for reliability). Although the proposed scheme falls under the broad category of stochastic optimization, we show through simulations that it has a quasi-deterministic convergence that we exploit to improve on the worst case performance of its predecessor, resulting in significantly better sum-rate capacity and average cost function value., QC 20140602, METIS

In this work, we study the so-called leakage minimization problem, within the context of interference alignment (IA). For that purpose, we propose a novel approach based on controlled perturbations of the leakage function, and show how the latter can be used as a mechanism to control the algorithm's convergence (and thus tradeoff convergence speed for reliability). Although the proposed scheme falls under the broad category of stochastic optimization, we show through simulations that it has a quasi-deterministic convergence that we exploit to improve on the worst case performance of its predecessor, resulting in significantly better sum-rate capacity and average cost function value., QC 20140602, METIS

Operation-intensive exhaustive checking is the unique optimal method for performing joint maximum-likelihood (JML) data and channel estimation. Thus, several suboptimal methods incorporating conventional maximum-likelihood sequence estimation (MLSE) or its extensions have been proposed in order to reduce complexity. However, most of them suffer from either long convergence delay or unsatisfactory performance. Therefore, based on a two-phase MLSE algorithm designed for partially coherent receivers, we propose a novel low-complexity and low-latency batch algorithm for JML process. The proposed algorithm first searches for several of the best candidate training sequences using priority-first search, and then applies the training sequences to the two-phase MLSEs to obtain the maximum-likelihood data sequence. Simulation results show that when the candidate training sequence length is adequate, the proposed algorithm can achieve the performance of optimal exhaustive checking., QC 20140121

Base station cooperation in cellular networks has been recently recognized as a key technology for mitigating interference, providing thus significant improvements in the system performance. In this paper, we consider a simple scenario consisting of two one-dimensional cells, where the base stations have fixed locations, while the user terminals are randomly distributed on a line. Exploiting the replica method from statistical physics, we derive the ergodic sum-rate under arbitrary signaling for both cooperative and non-cooperative scenarios, when the system size grows large. The obtained results are analytically tractable and can be used to optimize the system parameters in a simple manner. The numerical examples show that the analysis provides good approximations for finite-sized systems., QC 20140131

High quality view synthesis is a prerequisite for future free-viewpointtelevision. It will enable viewers to move freely in a dynamicreal world scene. Depth image based rendering algorithms willplay a pivotal role when synthesizing an arbitrary number of novelviews by using a subset of captured views and corresponding depthmaps only. Usually, each depth map is estimated individually bystereo-matching algorithms and, hence, shows lack of inter-viewconsistency. This inconsistency affects the quality of view synthesis negatively. This paper enhances the inter-view consistency ofmultiview depth imagery. First, our approach classifies the colorinformation in the multiview color imagery by modeling color witha mixture of Dirichlet distributions where the model parameters areestimated in a Bayesian framework with variational inference. Second, using the resulting color clusters, we classify the correspondingdepth values in the multiview depth imagery. Each clustered depthimage is subject to further sub-clustering. Finally, the resultingmean of each sub-cluster is used to enhance the depth imagery atmultiple viewpoints. Experiments show that our approach improvesthe average quality of virtual views by up to 0.8 dB when comparedto views synthesized by using conventionally estimated depth maps., QC 20140224