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Bandwidth limitations and energy constraints set severe restrictions on the design of control systems that utilize wireless sensor and actuator networks. It is common in these systems that a sensor node needs not be continuously monitored, but communicates to the controller only at certain instances when it detects a disturbance event. In this paper, such a scenario is studied and particular emphasis is on efficient utilization of the shared communication resources. Encoder-decoder design for an event-based control system with the plant affected by pulse disturbances is considered. A new iterative procedure is proposed which can jointly optimize encoder-decoder pairs for a certainty equivalent controller. The goal is to minimize a design criterion, in particular, a linear quadratic cost over a finite horizon. The algorithm leads to a feasible design of time-varying non-uniform encoder-decoder pairs. Numerical results demonstrate significant improvements in performance compared to a system using uniform quantization., © 2006 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.QC 20101221

Bandwidth limitations and energy constraints set severe restrictions on the design of control systems that utilize wireless sensor and actuator networks. It is common in these systems that a sensor node needs not be continuously monitored, but communicates to the controller only at certain instances when it detects a disturbance event. In this paper, such a scenario is studied and particular emphasis is on efficient utilization of the shared communication resources. Encoder-decoder design for an event-based control system with the plant affected by pulse disturbances is considered. A new iterative procedure is proposed which can jointly optimize encoder-decoder pairs for a certainty equivalent controller. The goal is to minimize a design criterion, in particular, a linear quadratic cost over a finite horizon. The algorithm leads to a feasible design of time-varying non-uniform encoder-decoder pairs. Numerical results demonstrate significant improvements in performance compared to a system using uniform quantization., © 2006 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.QC 20101221

We investigate sink decoding approaches and performance analysis for a network with intermediate node encoding (coded network). The network consists of statistically independent noisy channels. The sink bit error probability (BEP) is the performance measure. First, we investigate soft-decision decoding without statistical information on the upstream channels (the channels not directly connected to the sink). Numerical results show that the decoder cannot significantly improve the performance from a hard-decision decoder. We develop union bounds for analysis. The bounds show the asymptotic (regarding SNR: signal-to-noise ratio) performance of the decoder. Using statistical information about the upstream channels, we can find the error patterns of final hop channels (channels directly connected to sinks).With the error patterns, maximum-likelihood (ML) decoding can be performed, and a significant improvement in the BEP is obtained. To evaluate the union bound for the ML decoder, we use an equivalent point procedure. It is reduced to the least-squares problem with a linear constraint in the medium-to-high SNR region. With deterministic knowledge of the errors in the upstream channels, a genie-aided decoder can further improve the performance. We give the union bound for the genie decoder, which is straightforward to evaluate. By analyzing these decoders, we find that knowledge about the upstream channels is essential for good sink decoding., © 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.QC 20111101. Updated from conference paper to article, VR Project

We investigate sink decoding approaches and performance analysis for a network with intermediate node encoding (coded network). The network consists of statistically independent noisy channels. The sink bit error probability (BEP) is the performance measure. First, we investigate soft-decision decoding without statistical information on the upstream channels (the channels not directly connected to the sink). Numerical results show that the decoder cannot significantly improve the performance from a hard-decision decoder. We develop union bounds for analysis. The bounds show the asymptotic (regarding SNR: signal-to-noise ratio) performance of the decoder. Using statistical information about the upstream channels, we can find the error patterns of final hop channels (channels directly connected to sinks).With the error patterns, maximum-likelihood (ML) decoding can be performed, and a significant improvement in the BEP is obtained. To evaluate the union bound for the ML decoder, we use an equivalent point procedure. It is reduced to the least-squares problem with a linear constraint in the medium-to-high SNR region. With deterministic knowledge of the errors in the upstream channels, a genie-aided decoder can further improve the performance. We give the union bound for the genie decoder, which is straightforward to evaluate. By analyzing these decoders, we find that knowledge about the upstream channels is essential for good sink decoding., © 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.QC 20111101. Updated from conference paper to article, VR Project

We investigate sink decoding approaches and performance analysis for a network with intermediate node encoding (coded network). The network consists of statistically independent noisy channels. The sink bit error probability (BEP) is the performance measure. First, we investigate soft-decision decoding without statistical information on the upstream channels (the channels not directly connected to the sink). Numerical results show that the decoder cannot significantly improve the performance from a hard-decision decoder. We develop union bounds for analysis. The bounds show the asymptotic (regarding SNR: signal-to-noise ratio) performance of the decoder. Using statistical information about the upstream channels, we can find the error patterns of final hop channels (channels directly connected to sinks).With the error patterns, maximum-likelihood (ML) decoding can be performed, and a significant improvement in the BEP is obtained. To evaluate the union bound for the ML decoder, we use an equivalent point procedure. It is reduced to the least-squares problem with a linear constraint in the medium-to-high SNR region. With deterministic knowledge of the errors in the upstream channels, a genie-aided decoder can further improve the performance. We give the union bound for the genie decoder, which is straightforward to evaluate. By analyzing these decoders, we find that knowledge about the upstream channels is essential for good sink decoding., © 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.QC 20111101. Updated from conference paper to article, VR Project

We investigate sink decoding approaches and performance analysis for a network with intermediate node encoding (coded network). The network consists of statistically independent noisy channels. The sink bit error probability (BEP) is the performance measure. First, we investigate soft-decision decoding without statistical information on the upstream channels (the channels not directly connected to the sink). Numerical results show that the decoder cannot significantly improve the performance from a hard-decision decoder. We develop union bounds for analysis. The bounds show the asymptotic (regarding SNR: signal-to-noise ratio) performance of the decoder. Using statistical information about the upstream channels, we can find the error patterns of final hop channels (channels directly connected to sinks).With the error patterns, maximum-likelihood (ML) decoding can be performed, and a significant improvement in the BEP is obtained. To evaluate the union bound for the ML decoder, we use an equivalent point procedure. It is reduced to the least-squares problem with a linear constraint in the medium-to-high SNR region. With deterministic knowledge of the errors in the upstream channels, a genie-aided decoder can further improve the performance. We give the union bound for the genie decoder, which is straightforward to evaluate. By analyzing these decoders, we find that knowledge about the upstream channels is essential for good sink decoding., © 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.QC 20111101. Updated from conference paper to article, VR Project

We investigate sink decoding approaches and performance analysis for a network with intermediate node encoding (coded network). The network consists of statistically independent noisy channels. The sink bit error probability (BEP) is the performance measure. First, we investigate soft-decision decoding without statistical information on the upstream channels (the channels not directly connected to the sink). Numerical results show that the decoder cannot significantly improve the performance from a hard-decision decoder. We develop union bounds for analysis. The bounds show the asymptotic (regarding SNR: signal-to-noise ratio) performance of the decoder. Using statistical information about the upstream channels, we can find the error patterns of final hop channels (channels directly connected to sinks).With the error patterns, maximum-likelihood (ML) decoding can be performed, and a significant improvement in the BEP is obtained. To evaluate the union bound for the ML decoder, we use an equivalent point procedure. It is reduced to the least-squares problem with a linear constraint in the medium-to-high SNR region. With deterministic knowledge of the errors in the upstream channels, a genie-aided decoder can further improve the performance. We give the union bound for the genie decoder, which is straightforward to evaluate. By analyzing these decoders, we find that knowledge about the upstream channels is essential for good sink decoding., © 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.QC 20111101. Updated from conference paper to article, VR Project

We consider downlink transmission in multi-cell wireless networks where in each cell one base station is serving multiple mobile terminals. There is no a priori channel state information (CSI) available at base stations and mobile terminals. We propose a low-complexity pilot-assisted opportunistic user scheduling (PAOUS) scheme. The proposed scheme operates in four subsequent phases: channel training; feedback transmission; user scheduling; and data transmission. We deploy an orthogonal pilot-assisted channel training scheme for acquiring CST at mobile terminals. Consequently, each mobile terminal obtains a noisy estimation of the corresponding local CST (i.e. channel gains from base stations to the mobile terminal). Then, it makes a local decision based on the estimated channel gains of the interfering links (i.e. the links between base stations in neighboring cells and the mobile terminal) and sends a one-bit feedback signal to the base station of the corresponding cell. Each base station schedules one mobile terminal for communication. We compute the achievable rate region and the achievable degrees of freedom (DoF) of the proposed transmission scheme. Our results show that in a multi-cell network with K base stations and coherence time T, the total DoF K-opt (1 - K-opt/T) is achievable given that the number of mobile terminals in each cell scales proportional to signal-to-noise-ratio. Since limited radio resources are available, only a subset of base stations should be activated, where the optimum number of active base stations is K-opt = min {K, T/2}. This recommends that in large networks (K > T/2), select only a subset of the base stations to be active and perform the PAOUS scheme within the cells associated to these base stations. Our results reveal that, even with single antenna at base stations and no a priori CSI at terminals, a non-trivial DoF gain can be achieved. We also investigate the power allocation between channel training and data transmission, QC 20160923

In this work, we address the problem of channel estimation and precoding / combining for the so-called hybrid millimeter wave (mmWave) MIMO architecture. Our proposed channel estimation scheme exploits channel reciprocity in TDD MIMO systems, by using echoing, thereby allowing us to implement Krylov subspace methods in a fully distributed way. The latter results in estimating the right (resp. left) singular subspace of the channel at the transmitter (resp. receiver). Moreover, we also tackle the problem of subspace decomposition whereby the estimated right (resp. left) singular subspaces are approximated by a cascade of analog and digital precoder (resp. combiner), using an iterative method. Finally we compare our scheme with an equivalent fully digital case and conclude that a relatively similar performance can be achieved, however, with a drastically reduced number of RF chains - 4 ~ 8 times less (i.e., massive savings in cost and power consumption)., QC 20151217

In this work, we address the problem of channel estimation and precoding / combining for the so-called hybrid millimeter wave (mmWave) MIMO architecture. Our proposed channel estimation scheme exploits channel reciprocity in TDD MIMO systems, by using echoing, thereby allowing us to implement Krylov subspace methods in a fully distributed way. The latter results in estimating the right (resp. left) singular subspace of the channel at the transmitter (resp. receiver). Moreover, we also tackle the problem of subspace decomposition whereby the estimated right (resp. left) singular subspaces are approximated by a cascade of analog and digital precoder (resp. combiner), using an iterative method. Finally we compare our scheme with an equivalent fully digital case and conclude that a relatively similar performance can be achieved, however, with a drastically reduced number of RF chains - 4 ~ 8 times less (i.e., massive savings in cost and power consumption)., QC 20151217

In this work, we address the problem of channel estimation and precoding / combining for the so-called hybrid millimeter wave (mmWave) MIMO architecture. Our proposed channel estimation scheme exploits channel reciprocity in TDD MIMO systems, by using echoing, thereby allowing us to implement Krylov subspace methods in a fully distributed way. The latter results in estimating the right (resp. left) singular subspace of the channel at the transmitter (resp. receiver). Moreover, we also tackle the problem of subspace decomposition whereby the estimated right (resp. left) singular subspaces are approximated by a cascade of analog and digital precoder (resp. combiner), using an iterative method. Finally we compare our scheme with an equivalent fully digital case and conclude that a relatively similar performance can be achieved, however, with a drastically reduced number of RF chains - 4 ~ 8 times less (i.e., massive savings in cost and power consumption)., QC 20151217

In this work, we address the problem of channel estimation and precoding / combining for the so-called hybrid millimeter wave (mmWave) MIMO architecture. Our proposed channel estimation scheme exploits channel reciprocity in TDD MIMO systems, by using echoing, thereby allowing us to implement Krylov subspace methods in a fully distributed way. The latter results in estimating the right (resp. left) singular subspace of the channel at the transmitter (resp. receiver). Moreover, we also tackle the problem of subspace decomposition whereby the estimated right (resp. left) singular subspaces are approximated by a cascade of analog and digital precoder (resp. combiner), using an iterative method. Finally we compare our scheme with an equivalent fully digital case and conclude that a relatively similar performance can be achieved, however, with a drastically reduced number of RF chains - 4 ~ 8 times less (i.e., massive savings in cost and power consumption)., QC 20151217

In this work, we address the problem of channel estimation and precoding / combining for the so-called hybrid millimeter wave (mmWave) MIMO architecture. Our proposed channel estimation scheme exploits channel reciprocity in TDD MIMO systems, by using echoing, thereby allowing us to implement Krylov subspace methods in a fully distributed way. The latter results in estimating the right (resp. left) singular subspace of the channel at the transmitter (resp. receiver). Moreover, we also tackle the problem of subspace decomposition whereby the estimated right (resp. left) singular subspaces are approximated by a cascade of analog and digital precoder (resp. combiner), using an iterative method. Finally we compare our scheme with an equivalent fully digital case and conclude that a relatively similar performance can be achieved, however, with a drastically reduced number of RF chains - 4 ~ 8 times less (i.e., massive savings in cost and power consumption)., QC 20151217

We consider a scenario consisting of a primary and asecondary system, each represented by a pair of a transmitter anda receiver. The secondary transmitter assists in the retransmission of the primary message, which prevents the primary performance from being degraded by allowing the secondary system to access the transmission resources. Two network coding schemes applied in retransmission phase are investigated, the stationary network coding (SNC) scheme and the adaptive network coding(ANC) scheme. For each scheme we derive analytical results on packet throughput and infer that the ANC scheme outperforms the SNC scheme. We then provide a numerical performance comparison and a numerical optimization of the secondary packet throughput. Our main result shows cooperation can provide a significant performance improvement through effective network coding., QC 20150410

A lossy source coding problem with secrecy constraints is considered where a remote information source should be transmitted to a single destination via multiple agents in the presence of an eavesdropper. The agents observe noisy versions of the source and independently encode and transmit their observations to the destination via noiseless rate-limited links. Unbeknownst to the agents, an eavesdropper intercepts one of the links from the agents to the destination to learn as much as possible about the source. The destination should estimate the remote source subject to a mean distortion threshold. This problem can be viewed as the CEO problem with addition of secrecy constraints. We establish inner and outer bounds on the rate-distortion-equivocation region. In addition, we provide the optimal rate-distortion-equivocation region for the quadratic Gaussian case when the eavesdropper has no side information., QC 20150227

Luby transform (LT) codes are a class of rateless codes that automatically adapt their rate to the quality of the communication channel. In the original LT codes, fixed check-node degree distributions are used to combine variable nodes uniformly at random to extend the code graph and produce code bits. Here we propose a different approach: we design a sequence of rate-compatible degree distributions, and develop an algorithm that produces code bits in a manner such that the resulting degree distributions follow the designed sequence. Using this new design framework, we develop low-complexity LT codes suitable for time-varying noisy channels. Performance and complexity of the proposed LT codes are measured in terms of bit error rate and average number of edges per information and coded bit, respectively. Numerical examples illustrate the resulting trade-off between performance and complexity of the designed LT codes., QC 20150227

We consider the problem of lossy source coding with side information under a privacy constraint that the reconstruction sequence at a decoder should be kept secret to a certain extent from another terminal such as an eavesdropper, a sender, or a helper. We are interested in how the reconstruction privacy constraint at a particular terminal affects the rate-distortion tradeoff. In this work, we allow the decoder to use a random mapping, and give inner and outer bounds to the rate-distortion-equivocation region for different cases. In the case where each reconstruction symbol depends only on the source description and current side information symbol, the complete rate-distortion-equivocation region is provided. A binary example illustrating a new tradeoff due to the new privacy constraint, and a gain from the use of randomized decoder is given., QC 20150227

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

We consider a secure source coding problem with side informations at the decoder and the eavesdropper. The encoder has a source that it wishes to describe with limited distortion through a rate-limited link to a legitimate decoder. The message sent is also observed by the eavesdropper. The encoder aims to minimize both the distortion incurred by the legitimate decoder; and the information leakage rate at the eavesdropper. When the encoder has access to the side information (S.I.) at the decoder, we characterize the rate-distortion-information leakage rate (R.D.I.) region under a Markov chain assumption and when S.I. at the encoder does not improve the rate-distortion region as compared to the case when S.I. is absent. We then extend our setting to consider the case where the encoder and decoder obtain coded S.I. through a rate-limited helper, and characterize the R.D.I. region for several special cases under logarithmic loss distortion (log-loss). Finally, we consider the case of list or entropy constraints at the decoder and show that the R.D.I. region coincides with R.D.I. region under log-loss., QC 20140312

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

We study the achievable sum degrees of freedom(DoF) in a class of wireless single-antenna multi-hop half-duplexrelay networks. The networks contain Ms information sources, Md information destinations, and arbitrary layers of relays, each with 2K (K ≥ max{Ms,Md}) half-duplex relays, in between. A cluster successive relaying transmission scheme is applied to conduct the communication: We divide the relays in each layer into two equal-size clusters and activate them successively to efficiently use the available channel. It is shown that in a time-varying fading environment this scheme asymptotically achieves the sum DoF min{MsK/(Ms+K) , MdK/(Md+K−1)}, which is irrelevant to the number of hops the source messages have to pass through. This result also implies that, when the number of relays in each layeris infinitely large, the available DoF (i.e. the optimally achievable sum DoF) of the considered networks is min{Ms,Md}. Neither distributed signal processing nor multiple layers of half-duplex relay operation negatively affects the system DoF performance., QC 20130903

The problem of feedback stabilization of LTI plants over a Gaussian interference channel is considered. Two plants with arbitrary distributed initial states are monitored by two separate sensors which communicate their measurements to two separate controllers over a Gaussian interference channel under average transmit power constraints. The necessary conditions for mean square-stabilization over a memoryless symmetric Gaussian interference channel are derived. These conditions are shown to be tight for some system parameters. Further it is shown that linear memoryless sensing and control schemes are optimal for stabilization in some special cases., QC 20140128

We study the low SNR scaling of the non-coherent secret-key agreement capacity over a reciprocal, block-fading channel. For the restricted class of strategies, where one of the nodes is constrained to transmit pilot-only symbols, we show that the secret-key capacity scales as SNR ·log T if T ≤ 1/SNR, where T denotes the coherence period, and as SNR·log(1/SNR) otherwise. Our upper bound is inspired by the genie-aided argument of Borade and Zheng (IT-Trans 2010). Our lower bound is based on bursty communication, channel training, and secret message transmission., QC 20140121

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

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

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

Reconstruction fidelity of sparse signals contaminated by sparse noise is considered. Statistical mechanics inspired tools are used to show that the l(1)-norm based convex optimization algorithm exhibits a phase transition between the possibility of perfect and imperfect reconstruction. Conditions characterizing this threshold are derived and the mean square error of the estimate is obtained for the case when perfect reconstruction is not possible. Detailed calculations are provided to expose the mathematical tools to a wide audience., QC 20140625

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

We analyze the traffic carrying capacity of a single-input single-output system for a given delay guarantee at the flow level. A continuous time ON/OFF data source is considered as the traffic model while the wireless channel is modeled using the Gilbert-Elliot model. We study the impact of the delay bound violation probability, traffic burstiness, channel memory and the delay requirements at the network layer on the throughput under different signal strength., QC 20130111

We develop a greedy pursuit algorithm for solving the distributed compressed sensing problem in a connected network. This algorithm is based on subspace pursuit and uses the mixed support-setsignal model. Through experimental evaluation, we show that the distributed algorithm performs significantly better than the standalone (disconnected) solution and close to a centralized (fully connected to a central point) solution., QC 20121114

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

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

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 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

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

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

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 propose a LDPC Convolutional Code ensemble together with an expanding-window message-passing decoder that asymptotically have anytime properties when used for streaming transmission on the binary erasure channel. We show analytically that the decoding erasure probability of these codes decays exponentially over decoding delay and determine the corresponding anytime exponents., QC 20130118

We investigate the error floor performance of Luby Transform (LT) codes over the additive white Gaussian noise channel. We first derive a lower bound on the bit error rate for an LT code, which we subsequently use to show that the corresponding error floor is predominantly caused by low-degree variable nodes. Based on this observation, we propose a modified encoding scheme for LT codes that provides a lower error floor with no increase in encoding and decoding complexities. The convergence behavior of the proposed scheme is analyzed using extrinsic information transfer charts, and shown to be similar to the original LT code. Numerical examples demonstrate the improvements of the modified LT code as a stand-alone code and as a component code of a Raptor code., QC 20120206

We consider a base-station broadcasting a set of order-insensitive packets to a user population over packet-erasure channels. To improve efficiency we propose a relay-aided transmission scheme using instantaneously-decodable binary network coding. Our proposed scheme ensures that a coded packet can be immediately decoded at the user side without delay. Moreover, only binary operations are required in the encoding and decoding processes, which decrease the computational complex. We further analyze the performance of the resulting broadcast scheme, and show that significant improvements in transmission efficiency are obtained as compared to previously proposed ARQ and network-coding-based schemes., QC 20120228

We study network coding for wireless networks with finite channel state information (CSI) at intermediate nodes (relays). Based on the CSI of the relay-sink channels, we adapt the network codes at the relays. For a specific network with two sources, four relays and two sinks, the analytic results show that one bit CSI of all relay-sink channels (global CSI) can reduce complexity (field size), and simultaneously decrease the erasure probability. Then, we generalize the results to relay networks with M users, N relays and J sinks. We show that fixed network codes without CSI cannot achieve instantaneous min-cut, i.e., min-cut under current channel state. We also show that with one bit global CSI, we can achieve instantaneous min-cut by adapting the network codes using an alphabet size L, where L is the number of sinks connecting to a relay. Yet, the fixed MDS network codes use an alphabet size L(M-1N-1). For the networks with perfect or imperfect source-relay channels, adaptive network codes with one bit global CSI have lower erasure probability than the codes without CSI. Thus, one bit global CSI can reduce the erasure probability, and simultaneously reduce coding complexity., QC 20120416

In distributed storage systems reliability is achieved through redundant storage nodes distributed in the network. Then a data collector can recover source information even if some nodes fail. To maintain reliability, an autonomous and efficient protocol should be used to reconstruct the failed node. Therepairprocess causes traffic in the network. Recent results in e.g., [1], [2] found the optimal traffic-storage tradeoff, and proposed regenerating codes to achieve the optimality. We investigate the link costs and the impact of network topologies during therepairprocess. We formulate the minimum costrepairproblem in joint and decoupled methods. We investigate the required field size for the joint method. For the decoupled method, we show that the optimization problem is linear for the linear cost. We further show that the cooperation of surviving nodes could efficiently exploit the network topology and reduce therepaircost. The numerical results in tandem, star and grid networks show the benefits of our methods in term of the repair cost., QC 20120208

A class of semi-deterministic relay channels is introduced and it is shown that for channels in the class capacity can be achieved using an instantaneous relaying scheme. Applications to Gaussian channels are then discussed., QC 20120203

In this work, we study the MIMO Gaussian bidirectional broadcast channel (BBC) with common message and characterize the capacity region. Moreover, we show that the transmit covariance matrix optimization problem has the same structure as the corresponding optimization problem of the BBC without common message which leads to the comfortable position to transfer results from one scenario to the other. This problem is motivated by the concept of bidirectional relaying in a three-node network, where a half-duplex relay node establishes a bidirectional communication between two other nodes and thereby adds an own multicast message to the communication., QC 20111219

We determine the rate region of a source coding problem with common reconstruction and action-dependent side information where an action sequence is taken by an encoder over a rate-limited link. We show that the rate region depends only on the sum-rate and the sum-rate distortion and cost function is characterized. The result serves as a fundamental limit in transmission scenarios where the encoder wants to control and monitor the quality of the decoder's reconstruction via the respective uses of action sequences and a common reconstruction constraint., QC 20111117

We study the effect of power adaptation on the outage diversity of Incremental-redundancy automatic-repeat-request (INR-ARQ) transmission over the multi-input multi-output (MIMO) block-fading channel. In particular, we derive the optimal outage diversity achieved by power adaptation in INR-ARQ systems, and show that power adaptation provides significant gains in outage diversity. We also prove that the optimal outage diversity is achievable with random coding schemes., QC 20120216