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  • 1.
    Bao, Lei
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Shirazinia, Amirpasha
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Skoglund, Mikael
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Iterative encoder-controller design based on approximate dynamic programming2010Inngår i: IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC, 2010Konferansepaper (Fagfellevurdert)
    Abstract [en]

    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.

  • 2.
    Farokhi, Farhad
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Shirazinia, Amirpasha
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Networked Estimation Using Sparsifying Basis Prediction2013Inngår i: IFAC Proceedings Volumes, 2013, s. 174-181Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We present a framework for networked state estimation, where systems encode their (possibly high dimensional) state vectors using a mutually agreed basis between the system and the estimator (in a remote monitoring unit). The basis sparsifies the state vectors, i.e., it represents them using vectors with few non-zero components, and as a result, the systems might need to transmit only a fraction of the original information to be able to recover the non-zero components of the transformed state vector. Hence, the estimator can recover the state vector of the system from an under-determined linear set of equations. We use a greedy search algorithm to calculate the sparsifying basis. Then, we present an upper bound for the estimation error. Finally, we demonstrate the results on a numerical example.

  • 3.
    Shariati, Nafiseh
    et al.
    K. N. Toosi University of Technology.
    Shirazinia, Amirpasha
    Amirkabir University of Technology.
    An Improvement over PBOA MAC Protocol by Considering Link Quality in MANET2008Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We propose a methodology for improving theperformance of Progressive Back Off Algorithm (PBOA)which is a protocol that performs medium access controljointly with power control in Ad-hoc networks.Our method selects the optimum SNR thresholds based onlink quality. It adjusts the role of nodes’ mobility in network throughput. Simulation results show that the improvedprotocol outperforms PBOA without adaptation taken from link quality.

  • 4.
    Shirazinia, Amirpasha
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Source and Channel Coding for Compressed Sensing and Control2014Doktoravhandling, monografi (Annet vitenskapelig)
    Abstract [en]

    Rapid advances in sensor technologies have fueled massive torrents of data streaming across networks. Such large volume of information, indeed, restricts the operational performance of data processing, causing inefficiency in sensing, computation, communication and control. Hence, classical data processing techniques need to be re-analyzed and re-designed prior to be applied to modern networked data systems. This thesis aims to understand and characterize fundamental principles and interactions in and among sensing, compression, communication, computation and control, involved in networked data systems. In this regard, the thesis investigates four problems. The common theme is the design and analysis of optimized low-delay transmission strategies with affordable complexity for reliable communication of acquired data over networks with the objective of providing high quality of service for users.

    In the first three problems considered in the thesis, an emerging framework for data acquisition, namely, compressed sensing, is used which performs acquisition and compression simultaneously. The first problem considers the design of iterative encoding schemes, based on scalar quantization, for transmission of compressed sensing measurements over rate-limited links. Our approach is based on an analysis-by-synthesis principle, where the motivation is to reflect non-linearity in reconstruction, raised by compressed sensing, via synthesis, on choosing the best quantized value for encoding, via analysis. Our design shows significant reconstruction performance compared to schemes that only consider direct quantization of compressed sensing measurements.

    In the second problem, we investigate the design and analysis of encoding--decoding schemes, based on vector quantization, for transmission of compressed sensing measurements over rate-limited noisy links. In so realizing, we take an approach adapted from joint source-channel coding framework. We show that the performance of the studied system can approach the fundamental theoretical bound by optimizing the encoder-decoder pair. The price, however, is increased complexity at the encoder. To address the encoding complexity of the vector quantizer, we propose to use low-complexity multi-stage vector quantizer whose optimized design shows promising performance.

    In the third problem considered in the thesis, we take one step forward, and study joint source-channel coding schemes, based on vector quantization, for distributed transmission of compressed sensing measurements over noisy rate-limited links. We design optimized distributed coding schemes, and analyze theoretical bounds for such topology. Under certain conditions, our results reveal that the performance of the optimized schemes approaches the analytical bounds.

    In the last problem and in the context of control under communication constraints, we bring the notion of system dynamicity into the picture. Particularly, we study relations among stability in dynamical networked control systems, performance of real-time coding schemes and the coding complexity. For this purpose, we take approaches adapted from separate source-channel coding, and derive theoretical bounds on the performance of two types of coding schemes: dynamic repetition codes, and dynamic Fountain codes. We analytically and numerically show that the dynamic Fountain codes, over binary-input symmetric channels, with belief propagation decoding, are able to provide system stability in a networked control system.

    The results in the thesis evidently demonstrate that impressive performance gain is feasible by employing tools from communication and information theory to control and sensing. The insights offered through the design and analysis will also reveal fundamental pieces for understanding real-world networked data puzzle.

  • 5.
    Shirazinia, Amirpasha
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Bao, Lei
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Skoglund, Mikael
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Anytime Source Transmission using UEP-LT Channel Coding2011Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper, we study the design of a causal anytime encoding and decoding scheme for transmission of real-time information over a binary symmetric channel. In particular, our scheme combines unequal-error protection (UEP) rateless codes with sequential belief propagation decoding. In order to minimize delay in decoding and reduce distortion, we formulate and solve a linear programming problem. Moreover, degree distributions of the UEP-rateless codes are optimized since the efficiency of rateless codes highly depends on the corresponding degree distribution. The performance of the proposed scheme is demonstrated by using numerical simulations, and will be compared with an existing work.

  • 6.
    Shirazinia, Amirpasha
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Bao, Lei
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Skoglund, Mikael
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Design of UEP-based MSE-minimizing rateless codes for source-channel coding2011Inngår i: 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE , 2011, s. 3144-3147Konferansepaper (Fagfellevurdert)
    Abstract [sv]

    This paper proposes a method to optimize the performance of tandemsource–channel coding with respect to the mean-squared error by exploiting the unequal error protection coding. More specifically,we formulate a combination of linear programming and gridsearch to optimize degree distributions for unequal error protected rateless channel codes. An asymptotic upper bound for the meansquared error of the cascaded system is also derived. By optimizing the corresponding degree distributions of the rateless codes using unequal error protection principles, the proposed scheme has shown promising performance at high resolution region of sourcecoding.

  • 7.
    Shirazinia, Amirpasha
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Bao, Lei
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Skoglund, Mikael
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Distortion Bounds on Anytime Source Transmission Using UEP Channel Coding2011Konferansepaper (Fagfellevurdert)
    Abstract [en]

    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.

  • 8.
    Shirazinia, Amirpasha
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Bao, Lei
    Ericsson research.
    Skoglund, Mikael
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Sufficient conditions for stabilization in feedback control over noisy channels using anytime rateless codes2012Inngår i: 2012 American Control Conference (ACC), IEEE Computer Society, 2012, s. 1254-1259Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We consider the problem of remotely controlling an unstable first-order noiseless linear plant over a discrete symmetric memoryless channel using anytime source-channel coding. We propose a transmission scheme, exploiting unequal error protection (UEP) based on Luby transform (LT) codes under sequential belief propagation (BP) decoding. Sufficient conditions on mean square stability of the linearly controlled closed-loop system are derived for the anytime UEP-LT codes.

  • 9.
    Shirazinia, Amirpasha
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Chatterjee, Saikat
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Skoglund, Mikael
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Analysis-by-Synthesis Quantization for Compressed Sensing Measurements2013Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 61, nr 22, s. 5789-5800Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We consider a resource-limited scenario where a sensor that uses compressed sensing (CS) collects a low number of measurements in order to observe a sparse signal, and the measurements are subsequently quantized at a low bit-rate followed by transmission or storage. For such a scenario, we design new algorithms for source coding with the objective of achieving good reconstruction performance of the sparse signal. Our approach is based on an analysis-by-synthesis principle at the encoder, consisting of two main steps: 1) the synthesis step uses a sparse signal reconstruction technique for measuring the direct effect of quantization of CS measurements on the final sparse signal reconstruction quality, and 2) the analysis step decides appropriate quantized values to maximize the final sparse signal reconstruction quality. Through simulations, we compare the performance of the proposed quantization algorithms vis-a-vis existing quantization schemes.

  • 10.
    Shirazinia, Amirpasha
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Chatterjee, Saikat
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Skoglund, Mikael
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Analysis-by-synthesis-based Quantization of Compressed Sensing Measurements2013Inngår i: 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2013, New York: IEEE , 2013, s. 5810-5814Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We consider a resource-constrained scenario where a compressed sensing- (CS) based sensor has a low number of measurements which are quantized at a low rate followed by transmission or storage. Applying this scenario, we develop a new quantizer design which aims to attain a high-quality reconstruction performance of a sparse source signal based on analysis-by-synthesis framework. Through simulations, we compare the performance of the proposed quantization algorithm vis-a-vis existing quantization methods.

  • 11.
    Shirazinia, Amirpasha
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Chatterjee, Saikat
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Skoglund, Mikael
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Channel-optimized Vector Quantizer Design for Compressed Sensing Measurements2013Inngår i: 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2013, New York: IEEE , 2013, s. 4648-4652Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We consider vector-quantized (VQ) transmission of compressed sensing (CS) measurements over noisy channels. Adopting mean-square error (MSE) criterion to measure the distortion between a sparse vector and its reconstruction, we derive channel-optimized quantization principles for encoding CS measurement vector and reconstructing sparse source vector. The resulting necessary optimal conditions are used to develop an algorithm for training channel-optimized vector quantization (COVQ) of CS measurements by taking the end-to-end distortion measure into account.

  • 12.
    Shirazinia, Amirpasha
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Chatterjee, Saikat
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Skoglund, Mikael
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Distributed Quantization for Compressed Sensing2014Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We study distributed coding of compressed sensing (CS) measurements using vector quantizer (VQ). We develop a distributed framework for realizing optimized quantizer that enables encoding CS measurements of correlated sparse sources followed by joint decoding at a fusion center. The optimality of VQ encoder-decoder pairs is addressed by minimizing the sum of mean-square errors between the sparse sources and their reconstruction vectors at the fusion center. We derive a lower-bound on the end-to-end performance of the studied distributed system, and propose a practical encoder-decoder design through an iterative algorithm.

  • 13.
    Shirazinia, Amirpasha
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Chatterjee, Saikat
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Skoglund, Mikael
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Joint Source-Channel Vector Quantization for Compressed Sensing2014Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 62, nr 14, s. 3667-3681Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We study joint source-channel coding (JSCC) of compressed sensing (CS) measurements using vector quantizer (VQ). We develop a framework for realizing optimum JSCC schemes that enable encoding and transmitting CS measurements of a sparse source over discrete memoryless channels, and decoding the sparse source signal. For this purpose, the optimal design of encoder-decoder pair of a VQ is considered, where the optimality is addressed by minimizing end-to-end mean square error (MSE). We derive a theoretical lower bound on the MSE performance and propose a practical encoder-decoder design through an iterative algorithm. The resulting coding scheme is referred to as channel-optimized VQ for CS, coined COVQ-CS. In order to address the encoding complexity issue of the COVQ-CS, we propose to use a structured quantizer, namely low-complexity multistage VQ (MSVQ). We derive new encoding and decoding conditions for the MSVQ and then propose a practical encoder-decoder design algorithm referred to as channel-optimized MSVQ for CS, coined COMSVQ-CS. Through simulation studies, we compare the proposed schemes vis-a-vis relevant quantizers.

  • 14.
    Shirazinia, Amirpasha
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Chatterjee, Saikat
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Skoglund, Mikael
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Performance Bounds for Vector Quantized Compressive Sensing2012Inngår i: 2012 International Symposium on Information Theory and Its Applications, ISITA 2012, IEICE , 2012, s. 289-293Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper, we endeavor for predicting the performance of quantized compressive sensing under the use of sparse reconstruction estimators. We assume that a high rate vector quantizer is used to encode the noisy compressive sensing measurement vector. Exploiting a block sparse source model, we use Gaussian mixture density for modeling the distribution of the source. This allows us to formulate an optimal rate allocation problem for the vector quantizer. Considering noisy CS quantized measurements, we analyze upper- and lower-bounds on reconstruction error performance guarantee of two estimators - convex relaxation based basis pursuit de-noising estimator and an oracle-assisted least-squares estimator.

  • 15.
    Shirazinia, Amirpasha
    et al.
    Amirkabir University of Technology (Tehran Polytechnic).
    Safavi Homami, Seyed Mostafa
    Amirkabir University of Technology (Tehran Polytechnic).
    Shariati, Nafiseh
    K.N.Toosi University of Technology.
    On the Performance of Matching MMPP to SRD and LRD Traffic Using Algorithm LAMBDA2008Inngår i: 3RD INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES: FROM THEORY TO APPLICATIONS, VOLS 1-5, 2008, s. 2164-2169Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Markov-modulated Poisson process (MMPP) is one of the popular non-self-similar schemes for modeling network traffic. They are used for modeling both short-range dependent (SRD) and long-range dependent (LRD) traffic. The paper verifies Algorithm LAMBDA for fitting MMPP to synthetic traffic and evaluates the accuracy of the fitted MMPP model. We provide evidence that, for self-similar traffic, the performance highly depends on Hurst parameter. In some cases, the algorithm exhibits some inaccuracy in mean queuing delays. We try to modify it by a simple change in order to make the algorithm adaptive, and consequently, make the results more realistic.

1 - 15 of 15
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