arXiv subjects

Mikael Skoglund

Publications and source records attributed to Mikael Skoglund.

At least 253 records · Page 14Linked to original sources

arXiv2013

Coding for Computing Irreducible Markovian Functions of Sources with Memory

One open problem in source coding is to characterize the limits of representing losslessly a non-identity discrete function of the data encoded independently by the encoders of several correlated sources with memory. This paper investigates this problem under Markovian conditions, namely either the sources or the functions considered are Markovian. We propose using linear mappings over finite rings as encoders. If the function considered admits certain polynomial structure, the linear encoders can make use of this structure to establish "implicit collaboration" and boost the performance. In fact, this approach universally applies to any scenario (arbitrary function) because any discrete function admits a polynomial presentation of required format. There are several useful discoveries in the paper. The first says that linear encoder over non-field ring can be equally optimal for compressing data generated by an irreducible Markov source. Secondly, regarding the previous function-encoding problem, there are infinitely many circumstances where linear encoder over non-field ring strictly outperforms its field counterpart. To be more precise, it is seen that the set of coding rates achieved by linear encoder over certain non-field rings is strictly larger than the one achieved by the field version, regardless which finite field is considered. Therefore, in this sense, linear coding over finite field is not optimal. In addition, for certain scenarios where the sources do not possess the ergodic property, our ring approach is still able to offer a solution.

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arXiv2013

Successive Secret Key Agreement over Generalized Multiple Access and Broadcast Channels

A secret key agreement framework 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. There is a generalized discrete memoryless multiple access channel (GDMMAC) from users 1 and 2 to user 3 where the three users receive outputs from the channel. Furthermore, there is a broadcast channel (BC) from user 3 to users 1 and 2. Secret key sharing is intended where GDMMAC and BC can be successively used. In this framework, an inner bound of the secret key capacity region is derived. Moreover, for a special case where the channel inputs and outputs of the GDMAC and the BC form Markov chains in some order, the secret key capacity region is derived. Also the results are discussed through a binary example.

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arXiv2013

A Two-Phase Maximum-Likelihood Sequence Estimation for Receivers with Partial CSI

The optimality of the conventional maximum likelihood sequence estimation (MLSE), also known as the Viterbi Algorithm (VA), relies on the assumption that the receiver has perfect knowledge of the channel coefficients or channel state information (CSI). However, in practical situations that fail the assumption, the MLSE method becomes suboptimal and then exhaustive checking is the only way to obtain the ML sequence. At this background, considering directly the ML criterion for partial CSI, we propose a two-phase low-complexity MLSE algorithm, in which the first phase performs the conventional MLSE algorithm in order to retain necessary information for the backward VA performed in the second phase. Simulations show that when the training sequence is moderately long in comparison with the entire data block such as 1/3 of the block, the proposed two-phase MLSE can approach the performance of the optimal exhaustive checking. In a normal case, where the training sequence consumes only 0.14 of the bandwidth, our proposed method still outperforms evidently the conventional MLSE.

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arXiv2013

Optimized-Cost Repair in Multi-hop Distributed Storage Systems with Network Coding

In distributed storage systems reliability is achieved through redundancy stored at different nodes in the network. Then a data collector can reconstruct source information even though some nodes fail. To maintain reliability, an autonomous and efficient protocol should be used to repair the failed node. The repair process causes traffic and consequently transmission cost in the network. Recent results found the optimal trafficstorage tradeoff, and proposed regenerating codes to achieve the optimality. We aim at minimizing the transmission cost in the repair process. We consider the network topology in the repair, and accordingly modify information flow graphs. Then we analyze the cut requirement and based on the results, we formulate the minimum-cost as a linear programming problem for linear costs. We show that the solution of the linear problem establishes a fundamental lower bound of the repair-cost. We also show that this bound is achievable for minimum storage regenerating, which uses the optimal-cost minimum-storage regenerating (OCMSR) code. We propose surviving node cooperation which can efficiently reduce the repair cost. Further, the field size for the construction of OCMSR codes is discussed. We show the gain of optimal-cost repair in tandem, star, grid and fully connected networks.

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arXiv2013

On the Design of Channel Estimators for given Signal Estimators and Detectors

The fundamental task of a digital receiver is to decide the transmitted symbols in the best possible way, i.e., with respect to an appropriately defined performance metric. Examples of usual performance metrics are the probability of error and the Mean Square Error (MSE) of a symbol estimator. In a coherent receiver, the symbol decisions are made based on the use of a channel estimate. This paper focuses on examining the optimality of usual estimators such as the minimum variance unbiased (MVU) and the minimum mean square error (MMSE) estimators for these metrics and on proposing better estimators whenever it is necessary. For illustration purposes, this study is performed on a toy channel model, namely a single input single output (SISO) flat fading channel with additive white Gaussian noise (AWGN). In this way, this paper highlights the design dependencies of channel estimators on target performance metrics.

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arXiv2013

Decentralized Minimum-Cost Repair for Distributed Storage Systems

There have been emerging lots of applications for distributed storage systems e.g., those in wireless sensor networks or cloud storage. Since storage nodes in wireless sensor networks have limited battery, it is valuable to find a repair scheme with optimal transmission costs (e.g., energy). The optimal-cost repair has been recently investigated in a centralized way. However a centralized control mechanism may not be available or is very expensive. For the scenarios, it is interesting to study optimal-cost repair in a decentralized setup. We formulate the optimal-cost repair as convex optimization problems for the network with convex transmission costs. Then we use primal and dual decomposition approaches to decouple the problem into subproblems to be solved locally. Thus, each surviving node, collaborating with other nodes, can minimize its transmission cost such that the global cost is minimized. We further study the optimality and convergence of the algorithms. Finally, we discuss the code construction and determine the field size for finding feasible network codes in our approaches.

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arXiv2012

Degrees of Freedom of Multi-hop MIMO Broadcast Networks with Delayed CSIT

We study the sum degrees of freedom (DoF) of a class of multi-layer relay-aided MIMO broadcast networks with delayed channel state information at transmitters (CSIT). In the assumed network a K-antenna source intends to communicate to K single-antenna destinations, with the help of N-2 layers of K full-duplex single-antenna relays. We consider two practical delayed CSIT feedback scenarios. If the source can obtain the CSI feedback signals from all layers, we prove the optimal sum DoF of the network to be K/(1+1/2+...+1/K). If the CSI feedback is only within each hop, we show that when K=2 the optimal sum DoF is 4/3, and when K >= 3 the sum DoF 3/2 is achievable. Our results reveal that the sum DoF performance in the considered class of N-layer MIMO broadcast networks with delayed CSIT may depend not on N, the number of layers in the network, but only on K, the number of antennas/terminals in each layer.

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arXiv2012

Analysis of Sparse Representations Using Bi-Orthogonal Dictionaries

The sparse representation problem of recovering an N dimensional sparse vector x from M < N linear observations y = Dx given dictionary D is considered. The standard approach is to let the elements of the dictionary be independent and identically distributed (IID) zero-mean Gaussian and minimize the l1-norm of x under the constraint y = Dx. In this paper, the performance of l1-reconstruction is analyzed, when the dictionary is bi-orthogonal D = [O1 O2], where O1,O2 are independent and drawn uniformly according to the Haar measure on the group of orthogonal M x M matrices. By an application of the replica method, we obtain the critical conditions under which perfect l1-recovery is possible with bi-orthogonal dictionaries.

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arXiv2012

Iterative Source-Channel Coding Approach to Witsenhausen's Counterexample

In 1968, Witsenhausen introduced his famous counterexample where he showed that even in the simple linear quadratic static team decision problem, complex nonlinear decisions could outperform any given linear decision. This problem has served as a benchmark problem for decades where researchers try to achieve the optimal solution. This paper introduces a systematic iterative source--channel coding approach to solve problems of the Witsenhausen Counterexample-character. The advantage of the presented approach is its simplicity. Also, no assumptions are made about the shape of the space of policies. The minimal cost obtained using the introduced method is 0.16692462, which is the lowest known to date.

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arXiv2012

Analysis of MMSE Estimation for Compressive Sensing of Block Sparse Signals

Minimum mean square error (MMSE) estimation of block sparse signals from noisy linear measurements is considered. Unlike in the standard compressive sensing setup where the non-zero entries of the signal are independently and uniformly distributed across the vector of interest, the information bearing components appear here in large mutually dependent clusters. Using the replica method from statistical physics, we derive a simple closed-form solution for the MMSE obtained by the optimum estimator. We show that the MMSE is a version of the Tse-Hanly formula with system load and MSE scaled by parameters that depend on the sparsity pattern of the source. It turns out that this is equal to the MSE obtained by a genie-aided MMSE estimator which is informed in advance about the exact locations of the non-zero blocks. The asymptotic results obtained by the non-rigorous replica method are found to have an excellent agreement with finite sized numerical simulations.

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arXiv2012

Secret Key Agreement Using Correlated Sources over the Generalized Multiple Access Channel

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.

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arXiv2012

Zero-Delay Joint Source-Channel Coding for a Bivariate Gaussian on a Gaussian MAC

In this paper, delay-free, low complexity, joint source-channel coding (JSCC) for transmission of two correlated Gaussian memoryless sources over a Gaussian Multiple Access Channel (GMAC) is considered. The main contributions of the paper are two distributed JSCC schemes: one discrete scheme based on nested scalar quantization, and one hybrid discrete-analog scheme based on a scalar quantizer and a linear continuous mapping. The proposed schemes show promising performance which improve with increasing correlation and are robust against variations in noise level. Both schemes exhibit a constant gap to the performance upper bound when the channel signal-to-noise ratio gets large.

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arXiv2012

Coding With Action-dependent Side Information and Additional Reconstruction Requirements

Constrained lossy source coding and channel coding with side information problems which extend the classic Wyner-Ziv and Gel'fand-Pinsker problems are considered. Inspired by applications in sensor networking and control, we first consider lossy source coding with two-sided partial side information where the quality/availability of the side information can be influenced by a cost-constrained action sequence. A decoder reconstructs a source sequence subject to the distortion constraint, and at the same time, an encoder is additionally required to be able to estimate the decoder's reconstruction. Next, we consider the channel coding "dual" where the channel state is assumed to depend on the action sequence, and the decoder is required to decode both the transmitted message and channel input reliably. Implications on the fundamental limits of communication in discrete memoryless systems due to the additional reconstruction constraints are investigated. Single-letter expressions for the rate-distortion-cost function and channel capacity for the respective source and channel coding problems are derived. The dual relation between the two problems is discussed. Additionally, based on the two-stage coding structure and the additional reconstruction constraint of the channel coding problem, we discuss and give an interpretation of the two-stage coding condition which appears in the channel capacity expression. Besides the rate constraint on the message, this condition is a necessary and sufficient condition for reliable transmission of the channel input sequence over the channel in our "two-stage" communication problem. It is also shown in one example that there exists a case where the two-stage coding condition can be active in computing the capacity, and it thus can actively restrict the set of capacity achieving input distributions.

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arXiv2011

Performance Analysis and Design of Two Edge Type LDPC Codes for the BEC Wiretap Channel

We consider transmission over a wiretap channel where both the main channel and the wiretapper's channel are Binary Erasure Channels (BEC). We propose a code construction method using two edge type LDPC codes based on the coset encoding scheme. Using a standard LDPC ensemble with a given threshold over the BEC, we give a construction for a two edge type LDPC ensemble with the same threshold. If the given standard LDPC ensemble has degree two variable nodes, our construction gives rise to degree one variable nodes in the code used over the main channel. This results in zero threshold over the main channel. In order to circumvent this problem, we numerically optimize the degree distribution of the two edge type LDPC ensemble. We find that the resulting ensembles are able to perform close to the boundary of the rate-equivocation region of the wiretap channel. There are two performance criteria for a coding scheme used over a wiretap channel: reliability and secrecy. The reliability measure corresponds to the probability of decoding error for the intended receiver. This can be easily measured using density evolution recursion. However, it is more challenging to characterize secrecy, corresponding to the equivocation of the message for the wiretapper. Méasson, Montanari, and Urbanke have shown how the equivocation can be measured for a broad range of standard LDPC ensembles for transmission over the BEC under the point-to-point setup. By generalizing the method of Méasson, Montanari, and Urbanke to two edge type LDPC ensembles, we show how the equivocation for the wiretapper can be computed. We find that relatively simple constructions give very good secrecy performance and are close to the secrecy capacity. However finding explicit sequences of two edge type LDPC ensembles which achieve secrecy capacity is a more difficult problem. We pose it as an interesting open problem.

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arXiv2011

Projection-Based and Look Ahead Strategies for Atom Selection

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

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arXiv2011

Rate-Equivocation Optimal Spatially Coupled LDPC Codes for the BEC Wiretap Channel

We consider transmission over a wiretap channel where both the main channel and the wiretapper's channel are Binary Erasure Channels (BEC). We use convolutional LDPC ensembles based on the coset encoding scheme. More precisely, we consider regular two edge type convolutional LDPC ensembles. We show that such a construction achieves the whole rate-equivocation region of the BEC wiretap channel. Convolutional LDPC ensemble were introduced by Felström and Zigangirov and are known to have excellent thresholds. Recently, Kudekar, Richardson, and Urbanke proved that the phenomenon of "Spatial Coupling" converts MAP threshold into BP threshold for transmission over the BEC. The phenomenon of spatial coupling has been observed to hold for general binary memoryless symmetric channels. Hence, we conjecture that our construction is a universal rate-equivocation achieving construction when the main channel and wiretapper's channel are binary memoryless symmetric channels, and the wiretapper's channel is degraded with respect to the main channel.

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arXiv2011

Bilayer LDPC Convolutional Codes for Half-Duplex Relay Channels

In this paper we present regular bilayer LDPC convolutional codes for half-duplex relay channels. For the binary erasure relay channel, we prove that the proposed code construction achieves the capacities for the source-relay link and the source-destination link provided that the channel conditions are known when designing the code. Meanwhile, this code enables the highest transmission rate with decode-and-forward relaying. In addition, its regular degree distributions can easily be computed from the channel parameters, which significantly simplifies the code optimization. Numerical results are provided for both binary erasure channels (BEC) and AWGN channels. In BECs, we can observe that the gaps between the decoding thresholds and the Shannon limits are impressively small. In AWGN channels, the bilayer LDPC convolutional code clearly outperforms its block code counterpart in terms of bit error rate.

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arXiv2010

Nested Polar Codes for Wiretap and Relay Channels

We show that polar codes asymptotically achieve the whole capacity-equivocation region for the wiretap channel when the wiretapper's channel is degraded with respect to the main channel, and the weak secrecy notion is used. Our coding scheme also achieves the capacity of the physically degraded receiver-orthogonal relay channel. We show simulation results for moderate block length for the binary erasure wiretap channel, comparing polar codes and two edge type LDPC codes.

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