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S.p. Reveliotis - One of the best experts on this subject based on the ideXlab platform.
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A Polynomial-Complexity deadlock avoidance policy for sequential resource allocation systems with multiple resource acquisitions and flexible routings
Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187), 2000Co-Authors: Jonghun Park, S.p. ReveliotisAbstract:The need for effective and efficient deadlock avoidance policies (DAPs) is ever increasing due to the higher demand for system automation. This paper considers the deadlock avoidance problem for the class of conjunctive/disjunctive (sequential) resource allocation systems (C/D-RAS), in which multiple resource acquisitions and flexible routings are allowed. A new siphon-based characterization of deadlocks arising in C/D-RAS is developed, and subsequently, this characterization facilitates the development of a Polynomial Complexity deadlock avoidance policy for the considered RAS class. The developed policy can be perceived as a generalization of RUN DAP, originally developed for sequential RAS with unit resource allocations and no routing flexibility. The proposed approach is demonstrated by an example.
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Polynomial Complexity deadlock avoidance policies for sequential resource allocation systems
IEEE Transactions on Automatic Control, 1997Co-Authors: S.p. Reveliotis, Mark Lawley, Placid M FerreiraAbstract:The development of efficient deadlock avoidance policies (DAPs) for sequential resource allocation systems (RASs) is a problem of increasing interest in the scientific community, largely because of its relevance to the design of large-scale flexibly automated manufacturing systems. Much of the work on this problem existing in the literature is focused on the so-called single-unit RAS model, which is the simplest model in the considered class of RASs. Furthermore, due to a well-established result stating that, even for single-unit RASs, the computation of the maximally permissive DAP is intractable (NP-hard), many researchers (including our group) have focused on obtaining good suboptimal policies which are computationally tractable (scalable) and provably correct. In the first part of the paper, it is shown, however, that for a large subset (in fact, a majority) of single-unit RASs, the optimal DAP can be obtained in real-time with a computational cost which is a Polynomial function of the system size (i.e., the number of resource types and the distinct route stages of the processes running through the system). The implications of this result for the entire class of single-unit RASs are also explored. With a result on the design of optimal DAPs for single-unit RASs, the second part of the paper concentrates on the development of scalable and provably correct DAPs for the more general case of conjunctive RASs.
Achilleas Anastasopoulos - One of the best experts on this subject based on the ideXlab platform.
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Optimal Joint Detection/Estimation in Fading Channels With Polynomial Complexity
IEEE Transactions on Information Theory, 2007Co-Authors: I. Motedayen-aval, A. Krishnamoorthy, Achilleas AnastasopoulosAbstract:The problem of sequence detection in frequency-nonselective/time-selective fading channels, when channel state information (CSI) is not available at the transmitter and receiver, is considered in this paper. The traditional belief is that exact maximum-likelihood sequence detection (MLSD) of an uncoded sequence over this channel has exponential Complexity in the channel coherence time. Thus, for slowly varying channels, i.e., channels having coherence time on the order of the sequence length, the Complexity appears to be exponential in the sequence length. In the first part of this work, it is shown that exact MLSD can be computed with only Polynomial worst case Complexity in the sequence length regardless of the operating signal-to-noise ratio (SNR) for equal-energy signal constellations. By establishing a relationship between the aforementioned Complexity and the rank of the correlation matrix of the fading process, an understanding of how Complexity of the optimal MLSD receiver varies as the channel dynamics change is provided. In the second part of this paper, the problem of decoding turbo-like codes in frequency-nonselective/time-selective fading channels without receiver CSI is examined. Using arguments similar to the ones used for the MLSD case, it is shown that the exact symbol-by-symbol soft-decision metrics (SbSSDMs) implied by the min-sum algorithm can be evaluated with Polynomial worst case Complexity in the sequence length regardless of SNR for equal-energy signal constellations. Finally, by simplifying some key steps in the Polynomial-Complexity algorithm, a family of fast, approximate algorithms is derived, which yield near-optimal performance
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optimal joint detection estimation in fading channels with Polynomial Complexity
IEEE Transactions on Information Theory, 2007Co-Authors: I Motedayenaval, A. Krishnamoorthy, Achilleas AnastasopoulosAbstract:The problem of sequence detection in frequency-nonselective/time-selective fading channels, when channel state information (CSI) is not available at the transmitter and receiver, is considered in this paper. The traditional belief is that exact maximum-likelihood sequence detection (MLSD) of an uncoded sequence over this channel has exponential Complexity in the channel coherence time. Thus, for slowly varying channels, i.e., channels having coherence time on the order of the sequence length, the Complexity appears to be exponential in the sequence length. In the first part of this work, it is shown that exact MLSD can be computed with only Polynomial worst case Complexity in the sequence length regardless of the operating signal-to-noise ratio (SNR) for equal-energy signal constellations. By establishing a relationship between the aforementioned Complexity and the rank of the correlation matrix of the fading process, an understanding of how Complexity of the optimal MLSD receiver varies as the channel dynamics change is provided. In the second part of this paper, the problem of decoding turbo-like codes in frequency-nonselective/time-selective fading channels without receiver CSI is examined. Using arguments similar to the ones used for the MLSD case, it is shown that the exact symbol-by-symbol soft-decision metrics (SbSSDMs) implied by the min-sum algorithm can be evaluated with Polynomial worst case Complexity in the sequence length regardless of SNR for equal-energy signal constellations. Finally, by simplifying some key steps in the Polynomial-Complexity algorithm, a family of fast, approximate algorithms is derived, which yield near-optimal performance
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Polynomial Complexity noncoherent symbol by symbol detection with application to adaptive iterative decoding of turbo like codes
IEEE Transactions on Communications, 2003Co-Authors: I Motedayenaval, Achilleas AnastasopoulosAbstract:The problem of generating symbol-by-symbol soft decision metrics (SbSSDMs) in the presence of unknown channel parameters is considered. The motivation for this work lies in its application to iterative decoding of high-performance turbo-like codes, transmitted over channels that introduce unknown parameters in addition to Gaussian noise. Traditional methods for the exact evaluation of SbSSDMs involve exponential Complexity in the sequence length. A class of problems is identified for which the SbSSDMs can be exactly evaluated with only Polynomial Complexity with respect to the sequence length. Utilizing the close connection between symbol-by-symbol and sequence detection, it is also shown that for the aforementioned class of problems, detection of an uncoded data sequence in the presence of unknown parameters can be performed with Polynomial Complexity. The applicability of this technique is demonstrated by considering the problem of iterative detection of low-density parity-check codes in the presence of unknown and time-varying carrier-phase offset. Finally, based on the proposed exact schemes, an ultra-fast approximate algorithm for performing joint iterative decoding and phase estimation is derived that is well suited for hardware implementation.
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ICC - Polynomial Complexity ML sequence and symbol-by-symbol detection in fading channels
IEEE International Conference on Communications 2003. ICC '03., 1Co-Authors: I. Motedayen, Achilleas AnastasopoulosAbstract:The related problems of maximum likelihood sequence detection (MLSD) and symbol-by-symbol soft-decision metric (SbSSDM) generation in complex Gaussian flat-fading channels are considered in this paper. Traditional methods for the exact solution of these problems have exponential Complexity with respect to the sequence length. In this paper, it is shown that both these problems can be solved in Polynomial Complexity with respect to the sequence length. Furthermore, motivated by the Polynomial-Complexity exact algorithm, an approximate fast algorithm is also derived. Simulation results for a low-density parity-check (LDPC) code transmitted on the aforementioned channel show that the performance of the approximate algorithm is very close to the exact sum-product algorithm.
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ICC - Polynomial-Complexity, adaptive symbol-by-symbol soft-decision algorithms with application to non-coherent detection of LDPCC
2002 IEEE International Conference on Communications. Conference Proceedings. ICC 2002 (Cat. No.02CH37333), 1Co-Authors: I. Motedayen, Achilleas AnastasopoulosAbstract:Iterative decoding in the presence of unknown channel parameters requires the generation of symbol-by-symbol soft-decision metrics (SbSSDMs), jointly with parameter estimation. Traditional methods for the exact evaluation of these metrics have exponential Complexity with the length of the data sequence. In this paper, a class of problems is identified, for which the exact SbSSDMs can be obtained with only Polynomial Complexity with the data sequence length. The applicability of this technique is demonstrated by considering the problem of iterative detection of low-density parity-check codes in the presence of unknown and time-varying carrier-phase offset.
George N Karystinos - One of the best experts on this subject based on the ideXlab platform.
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Noncoherent Alamouti Phase-Shift Keying With Full-Rate Encoding and Polynomial-Complexity Maximum-Likelihood Decoding
IEEE Transactions on Wireless Communications, 2017Co-Authors: Panos P. Markopoulos, George N KarystinosAbstract:We consider Alamouti encoding that draws symbols from phase-shift keying and develop a new differential modulation scheme that attains full rate for any constellation order. In contrast to past work, the proposed scheme guarantees that the encoded matrix maintains the characteristics of the initial codebook and, at the same time, attains full rate so that all possible sequences of space-time matrices become valid. Surprisingly, although the validity of all sequences could be thought as a drawback with respect to the cost of noncoherent sequence decoding, in fact it turns out to be an advantage. Based on recent results in the context of quadratic-form maximization over finite alphabets, we exploit the full-rate property of the proposed scheme to develop a Polynomial-Complexity maximum-likelihood noncoherent sequence decoder whose order is solely determined by the number of receive antennas. Numerical studies show the superiority of the proposed scheme in comparison with contemporary alternatives in terms of encoding rate, decoding Complexity, bandwidth efficiency, and throughput.
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ISWCS - Polynomial-Complexity GLRT-optimal noncoherent PNC
2016 International Symposium on Wireless Communication Systems (ISWCS), 2016Co-Authors: M. Gkizeli, George N KarystinosAbstract:Noncoherent two-way relay (TWR) systems with physical-layer network coding (PNC) usually operate with differential or orthogonal modulation. In either case, due to channel-induced memory, the optimal receiver at both the relay and source nodes takes the form of a sequence detector. Such a receiver has exponential (in the sequence length) Complexity, when implemented through an exhaustive search among all possible sequences. Hence, many works in the literature consider single-symbol or short-block noncoherent PNC. In this work, we consider transmission of frequency-shift keying (FSK) signals in a TWR system and present an algorithm that performs generalized-likelihood-ratio-test (GLRT) optimal noncoherent PNC with Polynomial (in the sequence length) Complexity. Although presented in the context of FSK, our developments hold for other orthogonal modulation techniques as well. As a low-cost alternative, we also present a quadratic-Complexity suboptimal detector that attains near-optimal performance. Simulation studies indicate that the proposed GLRT-optimal and suboptimal noncoherent PNC attains near-coherent-PNC performance with affordable Complexity when the sequence length is on the order of 64, offering a 2–4dB gain over conventional noncoherent PNC approaches that can handle only short values of the sequence length.
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ICASSP - Novel full-rate noncoherent alamouti encoding that allows Polynomial-Complexity optimal decoding
2013 IEEE International Conference on Acoustics Speech and Signal Processing, 2013Co-Authors: Panos P. Markopoulos, George N KarystinosAbstract:We consider Alamouti encoding that draws symbols from M-ary phase-shift keying (M-PSK) and develop a new differential modulation scheme that attains full rate for any constellation order. In contrast to past work, the proposed scheme guarantees that the encoded matrix maintains the characteristics of the initial codebook and, at the same time, attains full rate so that all possible sequences of space-time matrices become valid. The latter property is exploited to develop a Polynomial-Complexity maximum-likelihood noncoherent sequence decoder whose order is solely determined by the number of receive antennas. We show that the proposed scheme is superior to contemporary alternatives in terms of encoding rate, decoding Complexity, and performance.
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rank deficient quadratic form maximization over m phase alphabet Polynomial Complexity solvability and algorithmic developments
International Conference on Acoustics Speech and Signal Processing, 2011Co-Authors: Anastasios Kyrillidis, George N KarystinosAbstract:The maximization of a positive (semi)definite complex quadratic form over a finite alphabet is NP-hard and achieved through exhaustive search when the form has full rank. However, if the form is rank-deficient, the optimal solution can be computed with only Polynomial Complexity in the length N of the maximizing vector. In this work, we consider the general case of a rank-D positive (semi)definite complex quadratic form and develop a method that maximizes the form with respect to a M-phase vector with Polynomial Complexity. The proposed method efficiently reduces the size of the feasible set from exponential to Polynomial. We also develop an algorithm that constructs the Polynomial-size candidate set in Polynomial time and observe that it is fully parallelizable and rank-scalable.
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ICASSP - Rank-deficient quadratic-form maximization over M-phase alphabet: Polynomial-Complexity solvability and algorithmic developments
2011 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2011Co-Authors: Anastasios Kyrillidis, George N KarystinosAbstract:The maximization of a positive (semi)definite complex quadratic form over a finite alphabet is NP-hard and achieved through exhaustive search when the form has full rank. However, if the form is rank-deficient, the optimal solution can be computed with only Polynomial Complexity in the length N of the maximizing vector. In this work, we consider the general case of a rank-D positive (semi)definite complex quadratic form and develop a method that maximizes the form with respect to a M-phase vector with Polynomial Complexity. The proposed method efficiently reduces the size of the feasible set from exponential to Polynomial. We also develop an algorithm that constructs the Polynomial-size candidate set in Polynomial time and observe that it is fully parallelizable and rank-scalable.
Anthony Ephremides - One of the best experts on this subject based on the ideXlab platform.
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Polynomial Complexity minimum time scheduling in a class of wireless networks
IEEE Transactions on Control of Network Systems, 2016Co-Authors: Vangelis Angelakis, Anthony Ephremides, Di YuanAbstract:We consider a wireless network with a set of transmitter-receiver pairs, or links, that share a common channel, and address the problem of emptying finite traffic volume from the transmitters in minimum time. This, so-called, minimum-time scheduling problem has proven to be $\mathcal{NP}$ -hard in general. In this paper, we study a class of minimum-time scheduling problems in which the link rates have a particular structure. We show that global optimality can be reached in Polynomial time and derive optimality conditions. Then, we consider a more general case in which we apply the same approach and obtain an approximation as well as lower and upper bounds to the optimal solution. Simulation results confirm and validate our approach.
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Polynomial Complexity minimum time scheduling in a class of wireless networks
arXiv: Networking and Internet Architecture, 2014Co-Authors: Vangelis Angelakis, Anthony Ephremides, Di YuanAbstract:We consider a wireless network with a set of transmitter-receiver pairs, or links, that share a common channel, and address the problem of emptying finite traffic volume from the transmitters in minimum time. This, so called, minimum-time scheduling problem has been proved to be NP-hard in general. In this paper, we study a class of minimum-time scheduling problems in which the link rates have a particular structure consistent with the assumed environment and topology. We show that global optimality can be reached in Polynomial time and derive optimality conditions. Then we consider a more general case in which we apply the same approach and thus obtain approximation as well as lower and upper bounds to the optimal solution. Simulation results confirm and validate our approach.
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solving a class of optimum multiuser detection problems with Polynomial Complexity
IEEE Transactions on Information Theory, 1998Co-Authors: C. Sankaran, Anthony EphremidesAbstract:We identify a class of optimum multiuser detection problems which can be solved with Polynomial Complexity in the number of users. The identification is based on transforming a quadratic 0-1 programming problem into an equivalent problem in graph theory. For a synchronous direct sequence code-division multiple access (CDMA) system, the result translates to designing a set of pseudorandom codes with the property that the cross correlation between every pair of codes in the set over one symbol period is nonpositive. We give two sets of codes with good correlation properties that fall within this class. Finally, we derive a bound on the cardinality of a signal set in an n-dimensional space, having the property that the cross correlation between every pair of signals in the set is nonpositive.
Placid M Ferreira - One of the best experts on this subject based on the ideXlab platform.
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Polynomial Complexity deadlock avoidance policies for sequential resource allocation systems
IEEE Transactions on Automatic Control, 1997Co-Authors: S.p. Reveliotis, Mark Lawley, Placid M FerreiraAbstract:The development of efficient deadlock avoidance policies (DAPs) for sequential resource allocation systems (RASs) is a problem of increasing interest in the scientific community, largely because of its relevance to the design of large-scale flexibly automated manufacturing systems. Much of the work on this problem existing in the literature is focused on the so-called single-unit RAS model, which is the simplest model in the considered class of RASs. Furthermore, due to a well-established result stating that, even for single-unit RASs, the computation of the maximally permissive DAP is intractable (NP-hard), many researchers (including our group) have focused on obtaining good suboptimal policies which are computationally tractable (scalable) and provably correct. In the first part of the paper, it is shown, however, that for a large subset (in fact, a majority) of single-unit RASs, the optimal DAP can be obtained in real-time with a computational cost which is a Polynomial function of the system size (i.e., the number of resource types and the distinct route stages of the processes running through the system). The implications of this result for the entire class of single-unit RASs are also explored. With a result on the design of optimal DAPs for single-unit RASs, the second part of the paper concentrates on the development of scalable and provably correct DAPs for the more general case of conjunctive RASs.