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The bidirectional broadcast channel denotes a broadcast channel with two receivers where each receiver knows the message intended for the other. We consider streaming sources where messages of each user arrive as bit-stream to the encoder. Thus our main quantity of interest is the bit error probability. By extending Sahai's argument to bidirectional broadcast channel, we show that under maximum-likelihood decoding the bit error probability decays exponentially in delay with positive exponent for all the rate pairs inside the capacity region. We also show existence of deterministic codes which achieve exponentially decaying bit error probability with delay., QC 20111216

In this paper we consider the design of semi-static inter-cell interference coordination schemes for LTE networks. In this approach, base stations coordinate the power settings per resource block over long time spans such as seconds. In order to optimize the power settings, one needs to employ models which predict the rate of terminals over the next coordination period under the usage of a given power setting. However, these models are typically quite simple and neglect the impact from fading as well as from dynamic resource allocation performed at the base stations on a millisecond basis. Ignoring such properties of OFDMA networks leads therefore to suboptimal transmit power settings. In this paper, we study the impact from a precise rate prediction model that accurately accounts for fading and dynamic resource allocation. On the down-side, this more precise model leads to a much more involved optimization problem to be solved once per coordination period. We propose two different heuristic methods to deal with this problem. Especially the usage of genetic algorithm results to be promising to counteract the complexity increase. We then study the overall system performance and find precise rate prediction models to be essential for semi-static interference coordination as they provide significant performance improvements in comparison to approaches with simpler models., QC 20130830

In this paper we consider the design of semi-static inter-cell interference coordination schemes for LTE networks. In this approach, base stations coordinate the power settings per resource block over long time spans such as seconds. In order to optimize the power settings, one needs to employ models which predict the rate of terminals over the next coordination period under the usage of a given power setting. However, these models are typically quite simple and neglect the impact from fading as well as from dynamic resource allocation performed at the base stations on a millisecond basis. Ignoring such properties of OFDMA networks leads therefore to suboptimal transmit power settings. In this paper, we study the impact from a precise rate prediction model that accurately accounts for fading and dynamic resource allocation. On the down-side, this more precise model leads to a much more involved optimization problem to be solved once per coordination period. We propose two different heuristic methods to deal with this problem. Especially the usage of genetic algorithm results to be promising to counteract the complexity increase. We then study the overall system performance and find precise rate prediction models to be essential for semi-static interference coordination as they provide significant performance improvements in comparison to approaches with simpler models., QC 20130830

In this paper we consider the design of semi-static inter-cell interference coordination schemes for LTE networks. In this approach, base stations coordinate the power settings per resource block over long time spans such as seconds. In order to optimize the power settings, one needs to employ models which predict the rate of terminals over the next coordination period under the usage of a given power setting. However, these models are typically quite simple and neglect the impact from fading as well as from dynamic resource allocation performed at the base stations on a millisecond basis. Ignoring such properties of OFDMA networks leads therefore to suboptimal transmit power settings. In this paper, we study the impact from a precise rate prediction model that accurately accounts for fading and dynamic resource allocation. On the down-side, this more precise model leads to a much more involved optimization problem to be solved once per coordination period. We propose two different heuristic methods to deal with this problem. Especially the usage of genetic algorithm results to be promising to counteract the complexity increase. We then study the overall system performance and find precise rate prediction models to be essential for semi-static interference coordination as they provide significant performance improvements in comparison to approaches with simpler models., QC 20130830

In this paper we consider the design of semi-static inter-cell interference coordination schemes for LTE networks. In this approach, base stations coordinate the power settings per resource block over long time spans such as seconds. In order to optimize the power settings, one needs to employ models which predict the rate of terminals over the next coordination period under the usage of a given power setting. However, these models are typically quite simple and neglect the impact from fading as well as from dynamic resource allocation performed at the base stations on a millisecond basis. Ignoring such properties of OFDMA networks leads therefore to suboptimal transmit power settings. In this paper, we study the impact from a precise rate prediction model that accurately accounts for fading and dynamic resource allocation. On the down-side, this more precise model leads to a much more involved optimization problem to be solved once per coordination period. We propose two different heuristic methods to deal with this problem. Especially the usage of genetic algorithm results to be promising to counteract the complexity increase. We then study the overall system performance and find precise rate prediction models to be essential for semi-static interference coordination as they provide significant performance improvements in comparison to approaches with simpler models., QC 20130830

In this paper we consider the design of semi-static inter-cell interference coordination schemes for LTE networks. In this approach, base stations coordinate the power settings per resource block over long time spans such as seconds. In order to optimize the power settings, one needs to employ models which predict the rate of terminals over the next coordination period under the usage of a given power setting. However, these models are typically quite simple and neglect the impact from fading as well as from dynamic resource allocation performed at the base stations on a millisecond basis. Ignoring such properties of OFDMA networks leads therefore to suboptimal transmit power settings. In this paper, we study the impact from a precise rate prediction model that accurately accounts for fading and dynamic resource allocation. On the down-side, this more precise model leads to a much more involved optimization problem to be solved once per coordination period. We propose two different heuristic methods to deal with this problem. Especially the usage of genetic algorithm results to be promising to counteract the complexity increase. We then study the overall system performance and find precise rate prediction models to be essential for semi-static interference coordination as they provide significant performance improvements in comparison to approaches with simpler models., QC 20130830

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

Dynamic decode-and-forward (DDF) is an improved decode-and-forward (DF) protocol under which the relay decides based on its received channel-state information (CSI) when to switch from listening mode to transmission mode without knowing the CSI of other links. In this paper we propose to apply rate-compatible LDPC convolutional (RC-LDPCC) codes to the DDF relay channel. The RC-LDPCC codes are constructed by successive graph extensions, and they have been proved analytically to be capacity achieving over the binary erasure channel. In this paper we show that the RC-LDPCC codes fit well with the DDF relaying, and the regularity of degree distributions simplifies the code optimization. Numerical results in terms of bit erasure rate and achievable rate are provided to evaluate the performance of the system. The results show that the RC-LDPCC codes are able to provide high achievable rates for the DDF relay channel., QC 20120831

In this paper we consider the coexistence of a single-input single-output (SISO) primary link with a multiple-input single-output (MISO) secondary user pair that has non-causal knowledge of the primary message. We study an achievable rate region that exploits this knowledge by combining selfless relaying to maintain the rate supported by the primary link with dirty paper coding to pre-cancel the interference at the secondary receiver. We find the optimal choice of power allocation between these operating modes at the secondary transmitter as well as the optimal beamforming vectors. Moreover, we address the robustness of the solution to uncertainties in the channel knowledge. Finally, we show by numerical evaluation the gains obtained due to the additional knowledge of the primary message., QC 20120905

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

In the present paper we study the power allocation for multi-hop underlay cognitive radio networks (CRNs) with line topology. That is, we consider a scenario, where a CRN operates in parallel to the primary network provided that the interference created to the primary network is limited by an acceptable threshold. The CNR is assumed to be a multi-hop relay network and hence before reaching the destination information from the source node may pass several hops from node to node. At each hop, the information is decoded and forwarded to the following node. It is further assumed that transmissions can be overheard by neighboring nodes, thereby creating interference. The power at each node can be optimally adjusted so that the end-to-end throughput of the CRN is maximized, while the constraint on interference towards the primary network is satisfied. In this paper, we show that for line CRNs the optimal power allocation is achieved when capacities of all intermediate links are equal and the interference constraint of the most disturbed primary user is fulfilled with equality. To simplify the computation of the optimal power allocation we derive two approximate solutions as well as several distributed power allocation schemes. The numerical results illustrate the interplay between the proposed solutions and the optimal power allocation., QC 20130111

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

In this paper we consider the coexistence of a single-input single-output (SISO) primary link with a multiple-input single-output (MISO) secondary user pair that has non-causal knowledge of the primary message. We study an achievable rate region that exploits this knowledge by combining selfless relaying to maintain the rate supported by the primary link with dirty paper coding to pre-cancel the interference at the secondary receiver. We find the optimal choice of power allocation between these operating modes at the secondary transmitter as well as the optimal beamforming vectors. Moreover, we address the robustness of the solution to uncertainties in the channel knowledge. Finally, we show by numerical evaluation the gains obtained due to the additional knowledge of the primary message., QC 20120905

In this paper we consider the coexistence of a single-input single-output (SISO) primary link with a multiple-input single-output (MISO) secondary user pair that has non-causal knowledge of the primary message. We study an achievable rate region that exploits this knowledge by combining selfless relaying to maintain the rate supported by the primary link with dirty paper coding to pre-cancel the interference at the secondary receiver. We find the optimal choice of power allocation between these operating modes at the secondary transmitter as well as the optimal beamforming vectors. Moreover, we address the robustness of the solution to uncertainties in the channel knowledge. Finally, we show by numerical evaluation the gains obtained due to the additional knowledge of the primary message., QC 20120905

In this paper we consider the coexistence of a single-input single-output (SISO) primary link with a multiple-input single-output (MISO) secondary user pair that has non-causal knowledge of the primary message. We study an achievable rate region that exploits this knowledge by combining selfless relaying to maintain the rate supported by the primary link with dirty paper coding to pre-cancel the interference at the secondary receiver. We find the optimal choice of power allocation between these operating modes at the secondary transmitter as well as the optimal beamforming vectors. Moreover, we address the robustness of the solution to uncertainties in the channel knowledge. Finally, we show by numerical evaluation the gains obtained due to the additional knowledge of the primary message., QC 20120905

In this paper we consider the coexistence of a single-input single-output (SISO) primary link with a multiple-input single-output (MISO) secondary user pair that has non-causal knowledge of the primary message. We study an achievable rate region that exploits this knowledge by combining selfless relaying to maintain the rate supported by the primary link with dirty paper coding to pre-cancel the interference at the secondary receiver. We find the optimal choice of power allocation between these operating modes at the secondary transmitter as well as the optimal beamforming vectors. Moreover, we address the robustness of the solution to uncertainties in the channel knowledge. Finally, we show by numerical evaluation the gains obtained due to the additional knowledge of the primary message., QC 20120905

In this paper, we study the design of causal anytime codes for transmission over symmetric discrete memoryless channel. In our earlier work, we proposed an anytime transmission scheme which is based on unequal error protection using Luby transform codes (UEP-LT) and sequential belief propagation (BP) decoding. In this paper we extend our previous result by providing an analysis on the proposed scheme. In particular, an upperbound on the end-to-end distortion of the anytime transmission scheme is derived., QC 20111213

The original compress-and-forward relaying scheme uses the technique of random binning at the relay node and successive decoding at the destination node. Recently, a scheme (termed the quantize-and-forward scheme in this paper) without binning and using joint decoding at the destination node has been proposed, which has been shown to achieve the same rate as the original compress-and-forward scheme. Since the previous work focuses on the so-called full duplex relay network, in this paper, an adaption of it for relay networks with a half-duplex relay is provided. Coding schemes and achievable rate results are presented for discrete memoryless half-duplex relay channels and half-duplex additive white Gaussian noise (AWGN) relay channels. Moreover, slow fading channels are considered, for which outage-related performance measures are evaluated. Specifically, the outage probability and the expected rate of the quantize-and-forward scheme are derived and compared with other well-known schemes. Furthermore, the diversity-multiplexing tradeoff is derived. It is shown that the quantize-and-forward scheme is a more suitable scheme than the compress-and-forward scheme over slow fading channels and it achieves the optimal diversity-multiplexing trade-off of a half-duplex relay channel., QC 20120131

In this paper, we study the design of causal anytime codes for transmission over symmetric discrete memoryless channel. In our earlier work, we proposed an anytime transmission scheme which is based on unequal error protection using Luby transform codes (UEP-LT) and sequential belief propagation (BP) decoding. In this paper we extend our previous result by providing an analysis on the proposed scheme. In particular, an upperbound on the end-to-end distortion of the anytime transmission scheme is derived., QC 20111213

In this paper, we study the design of causal anytime codes for transmission over symmetric discrete memoryless channel. In our earlier work, we proposed an anytime transmission scheme which is based on unequal error protection using Luby transform codes (UEP-LT) and sequential belief propagation (BP) decoding. In this paper we extend our previous result by providing an analysis on the proposed scheme. In particular, an upperbound on the end-to-end distortion of the anytime transmission scheme is derived., QC 20111213

In this paper, we study the design of causal anytime codes for transmission over symmetric discrete memoryless channel. In our earlier work, we proposed an anytime transmission scheme which is based on unequal error protection using Luby transform codes (UEP-LT) and sequential belief propagation (BP) decoding. In this paper we extend our previous result by providing an analysis on the proposed scheme. In particular, an upperbound on the end-to-end distortion of the anytime transmission scheme is derived., QC 20111213

In this paper, we study the design of causal anytime codes for transmission over symmetric discrete memoryless channel. In our earlier work, we proposed an anytime transmission scheme which is based on unequal error protection using Luby transform codes (UEP-LT) and sequential belief propagation (BP) decoding. In this paper we extend our previous result by providing an analysis on the proposed scheme. In particular, an upperbound on the end-to-end distortion of the anytime transmission scheme is derived., QC 20111213

In this paper, we study the iterative optimization of the encoder-controller pair for closed-loop control of a multi-dimensional plant over a noisy discrete memoryless channel. With the objective to minimize the expected linear quadratic cost over a finite horizon, we propose a joint design of the sensor measurement quantization, channel error protection, and optimal controller actuation. It was shown in our previous work that despite this optimization problem is known to be hard in general, an iterative design procedure can be derived to obtain a local optimal solution. However, in the vector case, optimizing the encoder for a fixed controller is in general not practically feasible due to the curse of dimensionality. In this paper, we propose a novel approach that uses the approximate dynamic programming (ADP) to implement a computationally feasible encoder updating policy with promising performance. Especially, we introduce encoder updating rules adopting the rollout approach. Numerical experiments are carried out to demonstrate the performance obtained by employing the proposed iterative design procedure and to compare it with other relevant schemes., QC 20111205

In this paper, it is shown that the achievable throughput capacity of wireless networks suffers from a fundamental limitation under finite node resource constraints. It is shown that this reduction results from a fundamental lower bound on the error performance of the wireless-channel model. In particular, the problem is addressed for the classic parallel-unicast problem introduced by Gupta-Kumar (2000). Under an AWGN channel-model assumption and for a pathloss exponent of α > 2, it is shown that the best available scheme for this setup achieves a throughput-capacity scaling of only Θ(n-1/2(log n)-1) per node. This is significant since an upper bound on asymptotic throughput capacity, scaling as Θ(n-1/2), was earlier shown to have been achieved by a scheme introduced by Franceschetti et. al. in 2006. The gap between achievability and the upper bound did not figure in past work on this problem, mainly due to transmission models that implicitly assume wireless nodes to have unlimited storage and encoding/decoding capabilities. Under the assumption of finite node memory, it is shown that such transmission models are unjustified in a strict information-theoretic sense. The new reduction in capacity scaling occurs from a necessity to modify the schemes used for showing achievability, in order to ensure that the failure probability is arbitrarily small. The analysis presented in this paper employs well-known sphere-packing bounds on the error probability of any block code in terms of the channel-error exponent. The result shows that for wireless networks with resource-constrained nodes, (a) the tightness of the best-known upper bound on capacity scaling still needs to be investigated, and (b) perhaps a better scheme that achieves higher capacity-scaling can be devised, but it is still an open problem., QC 20120124

In this paper, we consider the problem of the joint optimization of encoder-controller for closed-loop control with state feedback over a binary-input Gaussian channel (BGC). The objective is to minimize the expected linear quadratic cost over a finite horizon. Thisencoder-controller optimization problem is hard in general, mostly because of the curse of dimensionality. The result of this paper is a synthesis technique for a computationally feasible suboptimal controller which exploits both the soft and hard information of thechannel outputs. The proposed controller is efficient in the sense that it embraces measurement quantization, error protection and control over a finite-input infinite-output noisy channel. How to effectively implement this controller is also addressed in the paper. In particular, this is done by using Hadamard techniques. Numerical experiments are carried out to verify the promising gain offered by the combined controller, in comparison to the hard-information-based controller., QC 20120124

This paper considers a discrete memoryless four-node network where two nodes want to send three independent messages to the other two nodes. The two receiving nodes are allowed to cooperate by means of a unidirectional noiseless link with finite capacity. A coding scheme is proposed which combines rate splitting, block Markov multi-level superposition coding with binning and joint decoding. The general achievable rates are then specialized to degraded channel and Gaussian channel, where it is shown that the sum capacity for the Gaussian channel is achieved under certain conditions. Results in this paper recover and unify previously known results for the discrete memoryless Z channel without cooperation, and results for the Gaussian Z-interference channel with a digital relay link., QC 20111114

In this paper, an energy flow control strategy to reduce the smart meter privacy leakage is studied. The considered smart grid is equipped with an energy storage device. The privacy leakage is modeled as optimal Bayesian detections on the behaviors of the consumer made by an authorized adversary. To evaluate the privacy risk, a Bayesian detection-operational privacy leakage metric is proposed. The design of an optimal privacy-preserving energy control strategy can be formulated as a belief state MDP problem. Therefore, standard methods and algorithms can be utilized to obtain or to approximate the optimal control strategy. A simplified problem to design an instantaneous optimal privacy-preserving control strategy is also considered. It is shown that the problem of the instantaneous optimal control strategy design can be formulated as a set of linear programmings., QC 20160401

We study a multi-user up-link scenario where an attacker tries to impersonate the legitimate transmitters. We present a new framework for deriving a posteriori attack probabilities from the channel observations at the access point, which enables fast intrusion detection and authentication at the physical layer and can be exploited to reduce the security overhead by offtoading higher-layer authentication schemes. This is highly relevant for delay-sensitive applications that are targeted in 5G where the security overhead may limit the real-time performance. We take a factor-graph approach that can easily be extended to take into account other features, channel models, and radio access schemes. While related works only consider single-link scenarios, the multi-user approach in this paper allows us to exploit the cross-channel correlation of the large-scale fading parameters that is due to the propagation environment for improving the detection performance. As numerical results show, especially for slowly changing channels with high correlation our approach provides significant performance gains., QC 20161209, CERCES

The purpose of the work is to produce jointly coded frames for efficient video coding. We use motion-adaptive transforms in the temporal domain to generate the temporal subbands. The motion information is used to form graphs for transform construction. In our previous work, the motion-adaptive transform allows only one reference pixel to be the lowband coefficient. In this paper, we extend the motion-adaptive transform such that it permits multiple references and produces multiple lowband coefficients, which can be used in the case of bidirectional or multihypothesis motion estimation. The multi-reference motion-adaptive transform (MRMAT) is always orthonormal, thus, the energy is preserved by the transform. We compare MRMAT and the motion-compensated orthogonal transform (MCOT) [1], while HEVC intra coding is used to encode the temporal subbands. The experimental results show that MRMAT outperforms MCOT by about 0.6dB., QC 20170228

In this paper, we consider stabilization of multi-dimensional linear systems driven by Gaussian noise controlled over parallel Gaussian channels. For such systems, it has been recognized that for stabilization in the sense of asymptotic stationarity or stability in probability, Shannon capacity of a channel is an appropriate measure on characterizing whether a system can be made stable when controlled over the channel. However, this is in general not the case for quadratic stabilization. On a related problem of joint-source channel coding, in the information theory literature, the source-channel matching principle has been shown to lead to optimality of uncoded or analog transmission and when such matching conditions occur, it has been shown that capacity is also a relevant figure of merit for quadratic stabilization. A special case of this result is applicable to a scalar LQG system controlled over a scalar Gaussian channel. In this paper, we show that even in the absence of source-channel matching, to achieve quadratic stability, it may suffice that information capacity (in Shannon’s sense) is greater than the sum of the logarithm of unstable eigenvalue magnitudes. In particular, we show that periodic linear time varying coding policies are optimal in the sense of obtaining a finite second moment for the state of the system with minimum transmit power requirements for a large class of vector Gaussian channels. Our findings also extend the literature which has considered noise-free systems., QC 20160126

In this paper, an energy flow control strategy to reduce the smart meter privacy leakage is studied. The considered smart grid is equipped with an energy storage device. The privacy leakage is modeled as optimal Bayesian detections on the behaviors of the consumer made by an authorized adversary. To evaluate the privacy risk, a Bayesian detection-operational privacy leakage metric is proposed. The design of an optimal privacy-preserving energy control strategy can be formulated as a belief state MDP problem. Therefore, standard methods and algorithms can be utilized to obtain or to approximate the optimal control strategy. A simplified problem to design an instantaneous optimal privacy-preserving control strategy is also considered. It is shown that the problem of the instantaneous optimal control strategy design can be formulated as a set of linear programmings., QC 20160401

Provision of high data rates with always-onconnectivity to high mobility users is one of the motivations for design of fifth generation (5G) systems. High system capacity can be achieved by coordination between large number of antennas, which is done using the cloud radio access network (CRAN) design in 5G systems. In terms of baseband processing, allocation of appropriate resources to the users is necessary to achieve high system capacity, for which the state of the art uses the users' channel state information (CSI); however, they do not take into account the associated overhead, which poses a major bottleneck for the effective system performance. In contrast to this approach, this paper proposes the use of machine learning for allocating resources to high mobility users using only their position estimates. Specifically, the 'random forest' algorithm, a supervised machine learning technique, is used to design a learning-based resource allocation scheme by exploiting the relationships between the system parameters and the users' position estimates. In this way, the overhead for CSI acquisition is avoided by using the position estimates instead, with better spectrum utilization. While the initial numerical investigations, with minimum number of users in the system, show that the proposed learning-based scheme achieves 86% of the efficiency achieved by the perfect CSI-based scheme, if the effect of overhead is factored in, the proposed scheme performs better than the CSI-based approach. In a realistic scenario, with multiple users in the system, the significant increase in overhead for the CSI-based scheme leads to a performance gain of 100%, or more, by using the proposed scheme, and thus proving the proposed scheme to be more efficient in terms of system performance., QC 20170314

In this paper, an energy flow control strategy to reduce the smart meter privacy leakage is studied. The considered smart grid is equipped with an energy storage device. The privacy leakage is modeled as optimal Bayesian detections on the behaviors of the consumer made by an authorized adversary. To evaluate the privacy risk, a Bayesian detection-operational privacy leakage metric is proposed. The design of an optimal privacy-preserving energy control strategy can be formulated as a belief state MDP problem. Therefore, standard methods and algorithms can be utilized to obtain or to approximate the optimal control strategy. A simplified problem to design an instantaneous optimal privacy-preserving control strategy is also considered. It is shown that the problem of the instantaneous optimal control strategy design can be formulated as a set of linear programmings., QC 20160401

In this paper, an energy flow control strategy to reduce the smart meter privacy leakage is studied. The considered smart grid is equipped with an energy storage device. The privacy leakage is modeled as optimal Bayesian detections on the behaviors of the consumer made by an authorized adversary. To evaluate the privacy risk, a Bayesian detection-operational privacy leakage metric is proposed. The design of an optimal privacy-preserving energy control strategy can be formulated as a belief state MDP problem. Therefore, standard methods and algorithms can be utilized to obtain or to approximate the optimal control strategy. A simplified problem to design an instantaneous optimal privacy-preserving control strategy is also considered. It is shown that the problem of the instantaneous optimal control strategy design can be formulated as a set of linear programmings., QC 20160401

In this paper, an energy flow control strategy to reduce the smart meter privacy leakage is studied. The considered smart grid is equipped with an energy storage device. The privacy leakage is modeled as optimal Bayesian detections on the behaviors of the consumer made by an authorized adversary. To evaluate the privacy risk, a Bayesian detection-operational privacy leakage metric is proposed. The design of an optimal privacy-preserving energy control strategy can be formulated as a belief state MDP problem. Therefore, standard methods and algorithms can be utilized to obtain or to approximate the optimal control strategy. A simplified problem to design an instantaneous optimal privacy-preserving control strategy is also considered. It is shown that the problem of the instantaneous optimal control strategy design can be formulated as a set of linear programmings., QC 20160401

In this paper, we investigate receivers for vehicle-to- vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. Vehicular channels are characterized by multiple paths and time variations, which introduce challenges in the design of receivers. We propose an algorithm for IEEE 802.11p-compliant receivers, based on orthogonal frequency-division multiplexing (OFDM). We employ iterative structures in the receiver as a way to estimate the channel despite variations within a frame. The channel estimator is based on factor graphs (FGs), which allow the design of soft iterative receivers while keeping acceptable computational complexity. Throughout this paper, we focus on designing a receiver that offers a good complexity-performance tradeoff. Moreover, we propose a scalable algorithm to be able to tune the tradeoff, depending on the channel conditions. Our algorithm allows reliable communications while offering a considerable decrease in computational complexity. In particular, numerical results show the tradeoff between complexity and performance measured in computational time and bit error rate (BER), as well as frame error rate (FER) achieved by various interpolation lengths used by the estimator, which both outperform by decades the standard least squares (LS) solution. Furthermore, our adaptive algorithm shows a considerable improvement in terms of computational time and complexity against state-of-the-art and classical receptors while showing acceptable BER and FER performance., QC 20151021

An inference-based multiview depth image enhancement algorithm is introduced and investigated in this paper. Multiview depth imagery plays a pivotal role in free-viewpoint television. This technology requires high-quality virtual view synthesis to enable viewers to move freely in a dynamic real world scene. Depth imagery of different viewpoints is used to synthesize an arbitrary number of novel views. Usually, the depth imagery is estimated individually by stereo-matching algorithms and, hence, shows inter-view inconsistency. This inconsistency affects the quality of view synthesis negatively. This paper enhances the multiview depth imagery at multiple viewpoints by probabilistic weighting of each depth pixel. First, our approach classifies the color pixels in the multiview color imagery. Second, using the resulting color clusters, we classify the corresponding depth values in the multiview depth imagery. Each clustered depth image is subject to further subclustering. Clustering based on generative models is used for assigning probabilistic weights to each depth pixel. Finally, these probabilistic weights are used to enhance the depth imagery at multiple viewpoints. Experiments show that our approach consistently improves the quality of virtual views by 0.2 dB to 1.6 dB, depending on the quality of the input multiview depth imagery., QC 20150402

In this paper we study cognitive radio networks with secrecy constraints on the primary transmission. In particular we consider several transmission schemes for the secondary transmitter, namely interference neutralization (IN) and cooperative jamming with and without clean relaying (CR). We derive and analyze the achievable secondary rate performance of the schemes. Furthermore we thoroughly investigate the advantages and shortcomings of these schemes through numerical simulations in a geometric model where we highlight the impact of the users' locations and show the important difference in all schemes depending on the topology. Our results show that the secondary transmitter can successfully adapt its transmission scheme (and parameters), i.e., either IN or CR, depending on its location to maximize its rate while insuring perfect secrecy of the primary transmission., QC 20160314

Peaky and non-peaky signaling schemes have long been considered species apart in non-coherent wideband fading channels, as the first approaches asymptotically the linear-in-power capacity of a wideband AWGN channel with the same SNR, whereas the second reaches a nearly power-limited peak rate at some finite critical bandwidth and then falls to zero as bandwidth grows to infinity. In this paper it is shown that this distinction is in fact an artifact of the limited attention paid in the past to the product between the bandwidth and the fraction of time it is in use. This fundamental quantity, that is termed bandwidth occupancy, measures average bandwidth usage over time. The two types of signaling in the literature are harmonized to show that, for any type of signals, there is a fundamental limit - a critical bandwidth occupancy. All signaling schemes with the same bandwidth occupancy approach the capacity of wideband AWGN channels with the same asymptotic behavior as the bandwidth occupancy grows to its critical value. For a bandwidth occupancy above the critical, rate decreases to zero as the bandwidth occupancy goes to infinity., QC 20161115

In this paper, we investigate receivers for vehicle-to- vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. Vehicular channels are characterized by multiple paths and time variations, which introduce challenges in the design of receivers. We propose an algorithm for IEEE 802.11p-compliant receivers, based on orthogonal frequency-division multiplexing (OFDM). We employ iterative structures in the receiver as a way to estimate the channel despite variations within a frame. The channel estimator is based on factor graphs (FGs), which allow the design of soft iterative receivers while keeping acceptable computational complexity. Throughout this paper, we focus on designing a receiver that offers a good complexity-performance tradeoff. Moreover, we propose a scalable algorithm to be able to tune the tradeoff, depending on the channel conditions. Our algorithm allows reliable communications while offering a considerable decrease in computational complexity. In particular, numerical results show the tradeoff between complexity and performance measured in computational time and bit error rate (BER), as well as frame error rate (FER) achieved by various interpolation lengths used by the estimator, which both outperform by decades the standard least squares (LS) solution. Furthermore, our adaptive algorithm shows a considerable improvement in terms of computational time and complexity against state-of-the-art and classical receptors while showing acceptable BER and FER performance., QC 20151021

Data transmission over multiple-hop networks is impaired by random deleterious events, and characterizing the probability of error for the end-to-end transmission is challenging as the size of networks grows. Adams et al. showed that, when re-encoding at intermediate nodes is enabled, coded transmission over tandem/parallel links can be reduced to a single equivalent link with a specified probability function. Although iterative application of the tandem/parallel reduction techniques in alternation can simplify the task, they are generally not sufficient to reduce an arbitrary network to a single link. In this paper, we propose upper- and lower- bounding processes to bound the end-to-end probability distribution of a network by combining the parallel/tandem link reduction with the structure of flows over the network. We evaluate the performance of the proposed bounding methods at the 99% success rate of end-to-end data transmission over randomly generated acyclic networks. The numerical results demonstrate that our bounding approaches enable us to characterize a network by a single probability function to a very good precision., QC 20160216, QC 20160421

Hardware non-idealities in wireless transmitter electronics cause distortion that is not captured by conventional linear channel models; in fact, error-vector magnitude (EVM) measurements in conformance testing conceptually reduce their collective effect to an additive noise component at each subcarrier. Motivated by the EVM, the present paper considers a 'binoisy' multiple-input multiple-output (MIMO) channel model where the additional non-idealities manifest themselves as an additive distortion noise term at the transmit side. Through this extended MIMO relation, the effects of hardware impairments on the achievable rates of different digital modulation schemes are studied via large system analysis. The numerical results illustrate how tolerable EVM levels depend non-trivially on various factors, including the signal-to-noise ratio, modulation order and the level of asymmetry in antenna array configurations., QC 20160216, QC 20160421

In this paper, we study the problem of privacy information leakage in a smart grid. The privacy risk is assumed to be caused by an unauthorized binary hypothesis testing of the consumer's behaviour based on the smart meter readings of energy supplies from the energy provider. Another energy supplies are produced by an alternative energy source. A controller equipped with an energy storage device manages the energy inflows to satisfy the energy demand of the consumer. We study the optimal energy control strategy which minimizes the asymptotic exponential decay rate of the minimum Type II error probability in the unauthorized hypothesis testing to suppress the privacy risk. Our study shows that the cardinality of the energy supplies from the energy provider for the optimal control strategy is no more than two. This result implies a simple objective of the optimal energy control strategy. When additional side information is available for the adversary, the optimal control strategy and privacy risk are compared with the case of leaking smart meter readings to the adversary only., QC 20160121

In this paper we study secure communications with weak secrecy constraint in a cognitive radio channel, where the secondary receiver is treated as a potential eavesdropper with respect to the primary transmission. The primary's secrecy rate and the transmission scheme should be kept unchanged whether the secondary users transmit or not. We derive the achievable rate of the discrete memoryless multi-phase cognitive channel. To against the information leakage due to the use of Gelfand-Pinsker coding at the secondary transmitter, we derive the corresponding constraints to guarantee the primary's secure transmission. We then specialize the results to the additive white Gaussian noise channels. Numerical results show the advantages of using the proposed multiple-phase transmission scheme over the traditional ones without the additional phase., QC 20160314

Security issues in wireless networks have become a subject of growing interest in recent years due to the broadcast nature of wireless channels. In this paper, we investigate secure communication over a multi-antenna wiretap channel in the presence of randomly distributed eavesdroppers. In the fast fading environment, the overall performance of this channel is traditionally characterized by the ergodic secrecy capacity, which, in general, cannot be derived explicitly. Nevertheless, based on the assumption that the numbers of antennas at legitimate terminals and the number of eavesdroppers grow large without bound, we derive a deterministic approximation of an achievable ergodic secrecy rate for arbitrary inputs. In addition, we characterize the secrecy rates for practically relevant separate-decoding scheme at the receiver. We validate the proposed large-system approximation through numerical simulations and observe a good match with the actual secrecy rates. Finally, we also analyze some interesting behavior of the secrecy rates in the given scenario depending on the geometry of the nodes., QC 20160229

In this paper a successive refinement problem is considered where decoders can access only distributed storage nodes, subject to an additional constraint on the loss of information if failures happen. We characterize the optimal tradeoff for a given a distortion tuple and an equivocation constraint between storage nodes. A binary example is provided to illustrate the trade-off between the loss of information constraint and the corresponding achievable rate region., QC 20161102

In this paper we investigate secrecy games in cognitive radio networks with multiple secondary pairs and secrecy constraints. We consider the cognitive channel model with multiple secondary pairs where the secondary receivers are treated as eavesdroppers with respect to the primary transmission. For this novel network model, we derive achievable rate regions when secondary pairs are allowed to use the channel simultaneously. We then investigate the spectrum sharing mechanisms using several game theoretic models, namely 1) a single-leader multiple-follower Stackelberg game with the primary transmitter as the leader and the secondary transmitters as followers; 2) a non-cooperative power control game between the secondary transmitters if they can access the channel simultaneously; and 3) an auction between a primary auctioneer and secondary bidders which allows the primary transmitter to exploit the competitive interaction between the secondary transmitters. We illustrate through numerical simulations the equilibrium outcomes of the analyzed games and the impact of the competition between the secondary transmitters on the utility performance of every node in the cognitive radio network., QC 20160926

In this paper, the pessimistic multi letter common randomness assisted secrecy capacity for the Arbitrarily Varying Wiretap Channel (AVWC) under input and state constraints is derived., QC 20160926