Parastoo Sadeghi

Australian National University, Canberra, Australian Capital Territory, Australia

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Publications (151)113.3 Total impact

  • Mingchao Yu, Parastoo Sadeghi, Alex Sprintson
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    ABSTRACT: Random linear network coding (RLNC) is asymptotically throughput optimal in the wireless broadcast of a block of packets from a sender to a set of receivers, but suffers from heavy computational load and packet decoding delay. To mitigate this problem while maintaining good throughput, we partition the packet block into disjoint generations after broadcasting the packets uncoded once and collecting one round of feedback about receivers' packet reception state. We prove the NP-hardness of the optimal partitioning problem by using a hypergraph coloring approach, and develop an efficient heuristic algorithm for its solution. Simulations show that our algorithm outperforms existing solutions.
  • Mingchao Yu, Parastoo Sadeghi, Neda Aboutorab
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    ABSTRACT: We consider broadcasting a block of packets to multiple wireless receivers under random packet erasures using instantly decodable network coding (IDNC). The sender first broadcasts each packet uncoded once, then generates coded packets according to receivers' feedback about their missing packets. We focus on strict IDNC (S-IDNC), where each coded packet includes at most one missing packet of every receiver. But we will also compare it with general IDNC (G-IDNC), where this condition is relaxed. We characterize two fundamental performance limits of S-IDNC: 1) the number of transmissions to complete the broadcast, and 2) the average delay for a receiver to decode a packet. We derive a closed-form expression for the expected minimum number of transmissions in terms of the number of packets and receivers and the erasure probability. We prove that it is NP-hard to minimize the decoding delay of S-IDNC. We also derive achievable upper bounds on the above two performance limits. We show that G-IDNC can outperform S-IDNC %in terms of the number of transmissions without packet erasures, but not necessarily with packet erasures. Next, we design optimal and heuristic S-IDNC transmission schemes and coding algorithms with full/intermittent receiver feedback. We present simulation results to corroborate the developed theory and compare with existing schemes.
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    ABSTRACT: Recent advancements in graph-based analysis and solutions of instantly decodable network coding (IDNC) trigger the interest to extend them to more complicated opportunistic network coding (ONC) scenarios, with limited increase in complexity. In this paper, we design a simple IDNC-like graph model for a specific subclass of ONC, by introducing a more generalized definition of its vertices and the notion of vertex aggregation in order to represent the storage of non-instantly-decodable packets in ONC. Based on this representation, we determine the set of pairwise vertex adjacency conditions that can populate this graph with edges so as to guarantee decodability or aggregation for the vertices of each clique in this graph. We then develop the algorithmic procedures that can be applied on the designed graph model to optimize any performance metric for this ONC subclass. A case study on reducing the completion time shows that the proposed framework improves on the performance of IDNC and gets very close to the optimal performance.
  • Source
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    ABSTRACT: In this paper, we study a real-time scalable video broadcast over wireless networks in instantly decodable network coded (IDNC) systems. Such real-time scalable video has a hard deadline and imposes a decoding order on the video layers.We first derive the upper bound on the probability that the individual completion times of all receivers meet the deadline. Using this probability, we design two prioritized IDNC algorithms, namely the expanding window IDNC (EW-IDNC) algorithm and the non-overlapping window IDNC (NOW-IDNC) algorithm. These algorithms provide a high level of protection to the most important video layer before considering additional video layers in coding decisions. Moreover, in these algorithms, we select an appropriate packet combination over a given number of video layers so that these video layers are decoded by the maximum number of receivers before the deadline. We formulate this packet selection problem as a two-stage maximal clique selection problem over an IDNC graph. Simulation results over a real scalable video stream show that our proposed EW-IDNC and NOW-IDNC algorithms improve the received video quality compared to the existing IDNC algorithms.
  • Shahriar Etemadi Tajbakhsh, Parastoo Sadeghi
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    ABSTRACT: In this paper, we introduce a system and a set of algorithms for disseminating popular content to a large group of wireless clients spread over a wide area. This area is partitioned into multiple cells and there is a base station in each cell which is able to broadcast to the clients within its radio coverage. Dissemination of information in the proposed system is hybrid in nature: Each base station broadcasts a fraction of information in the form of random linear combinations of data blocks. Then the clients cooperate by exchanging packets to obtain their desired messages while they are moving arbitrarily over the area. In this paper, fundamental trade-offs between the average information delivery completion time at the clients and different parameters of the system such as bandwidth usage by the base stations, average energy consumption by the clients and the popularity of the spread information are studied. Moreover different heuristic algorithms are proposed to control and maintain a balance over these trade-offs. Also, the more complicated case of multiple sessions where each client is interested in an arbitrary subset of sessions is considered and two variants of the basic dissemination algorithm are proposed. The performance of all the proposed algorithms is evaluated via extensive numerical experiments.
    Journal of Communications and Networks 04/2015; 17(2):133-144. DOI:10.1109/JCN.2015.000027 · 0.75 Impact Factor
  • Source
    Mingchao Yu, Alex Sprintson, Parastoo Sadeghi
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    ABSTRACT: We consider a setting in which a sender wishes to broadcast a block of K data packets to a set of wireless receivers, where each of the receivers has a subset of the data packets already available to it (e.g., from prior transmissions) and wants the rest of the packets. Our goal is to find a linear network coding scheme that yields the minimum average packet decoding delay (APDD), i.e., the average time it takes for a receiver to decode a data packet. Our contributions can be summarized as follows. First, we prove that this problem is NP-hard by presenting a reduction from the hypergraph coloring problem. Next, we show that %\alexn{an MDS-based solution or} a random linear network coding (RLNC) provides an approximate solution to this problem with approximation ratio $2$ with high probability. Next, we present a methodology for designing specialized approximation algorithms for this problem that outperform RLNC solutions while maintaining the same throughput. In a special case of practical interest with a small number of wanted packets our solution can achieve an approximation ratio (4-2/K)/3. Finally, we conduct an experimental study that demonstrates the advantages of the presented methodology.
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    Ni Ding, Rodney A. Kennedy, Parastoo Sadeghi
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    ABSTRACT: This paper considers the problem of finding the minimum sum-rate strategy in cooperative data exchange (CDE) systems. In a CDE system, there are a number of geographically close cooperative clients who send packets to help the others recover a packet set. A minimum sum-rate strategy is the strategy that achieves universal recovery (the situation when all the clients recover the whole packet set) with the the minimal sum-rate (the total number of transmissions). We propose an iterative merging (IM) algorithm that recursively merges client sets based on an estimate of the minimum sum-rate and achieves local recovery until the universal recovery is achieved. We prove that the minimum sum-rate and a corresponding strategy can be found by starting the IM algorithm with an initial lower estimate of the minimum sum-rate. We run an experiment to show that the complexity of the IM algorithm is lower than the complexity of existing deterministic algorithms.
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    Ni Ding, Rodney A. Kennedy, Parastoo Sadeghi
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    ABSTRACT: We consider the fairness in cooperative data exchange (CDE) problem among a set of wireless clients. In this system, each client initially obtains a subset of the packets. They exchange packets in order to reconstruct the entire packet set. We study the problem of how to find a transmission strategy that distributes the communication load most evenly in all strategies that have the same sum-rate (the total number of transmissions) and achieve universal recovery (the situation when all clients recover the packet set). We formulate this problem by a discrete minimization problem and prove its $M$-convexity. We show that our results can also be proved by the submodularity of the feasible region shown in previous works and are closely related to the resource allocation problems under submodular constraints. To solve this problem, we propose to use a steepest descent algorithm (SDA) based on $M$-convexity. By varying the number of clients and packets, we compare SDA with a deterministic algorithm (DA) based on submodularity in terms of convergence performance and complexity. The results show that for the problem of finding the fairest and minimum sum-rate strategy for the CDE problem SDA is more efficient than DA when the number of clients is up to five.
  • Source
    Ni Ding, Rodney A. Kennedy, Parastoo Sadeghi
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    ABSTRACT: This paper considers how to accurately estimate the minimum sum-rate so as to reduce the complexity of solving cooperative data exchange (CDE) problems. The CDE system contains a number of geographically close clients who send packets to help the others recover an entire packet set. The minimum sum-rate is the minimum value of total number of transmissions that achieves universal recovery (the situation when all the clients recover the whole packet set). Based on a necessary and sufficient condition for a supermodular base polyhedron to be nonempty, we show that the minimum sum-rate for a CDE system can be determined by a maximization over all possible partitions of the client set. Due to the high complexity of solving this maximization problem, we propose a deterministic algorithm to approximate a lower bound on the minimum sum-rate. We show by experiments that this lower bound is much tighter than those lower bounds derived in the existing literature. We also show that the deterministic algorithm prevents from repetitively running the existing algorithms for solving CDE problems so that the overall complexity can be reduced accordingly.
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    Shama N Islam, Salman Durrani, Parastoo Sadeghi
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    ABSTRACT: In this paper, we formulate and study the optimum power allocation problem in an amplify and forward (AF) multi-way relay network (MWRN). We derive closed-form analytical expressions for the optimum power allocation coefficients for the data power and the pilot power of the users and the relay to maximize the sum rate. We assume that only long term statistical channel state information (CSI) (i.e., channel variance) are available to each user and the relay. Our results show that to achieve the same sum rate, optimum power allocation requires 7 − 9 dB less transmit power compared to equal power allocation depending on users' channel conditions. In addition, we show that for optimum power allocation, the reduction in the sum rate due to channel estimation errors, becomes less compared to the case of equal power allocation. Index Terms—multi-way relay network, amplify and forward, power allocation, sum rate, channel state information.
    IEEE ICSPCS, Gold Coast, Australia; 12/2014
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    ABSTRACT: This paper studies the problem of broadcasting layered video streams over heterogeneous single-hop wireless networks using feedback-free random linear network coding (RLNC). We combine RLNC with unequal error protection (UEP) and our main purpose is twofold. First, to systematically investigate the benefits of UEP+RLNC layered approach in servicing users with different reception capabilities. Second, to study the effect of not using feedback, by comparing feedback-free schemes with idealistic full-feedback schemes. To these ends, we study `expected percentage of decoded frames' as a key content-independent performance metric and propose a general framework for calculation of this metric, which can highlight the effect of key system, video and channel parameters. We study the effect of number of layers and propose a scheme that selects the optimum number of layers adaptively to achieve the highest performance. Assessing the proposed schemes with real H.264 test streams, the trade-offs among the users' performances are discussed and the gain of adaptive selection of number of layers to improve the trade-offs is shown. Furthermore, it is observed that the performance gap between the proposed feedback-free scheme and the idealistic scheme is very small and the adaptive selection of number of video layers further closes the gap.
  • Source
    Mingchao Yu, Parastoo Sadeghi, Neda Aboutorab
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    ABSTRACT: Deterministic linear network coding (DLNC) is an important family of network coding techniques for wireless packet broadcast. In this paper, we show that DLNC is strongly related to and can be effectively studied using matroid theory without bridging index coding. We prove the equivalence between the DLNC solution and matrix matroid. We use this equivalence to study the performance limits of DLNC in terms of the number of transmissions and its dependence on the finite field size. Specifically, we derive the sufficient and necessary condition for the existence of perfect DLNC solutions and prove that such solutions may not exist over certain finite fields. We then show that identifying perfect solutions over any finite field is still an open problem in general. To fill this gap, we develop a heuristic algorithm which employs graphic matroids to find perfect DLNC solutions over any finite field. Numerical results show that its performance in terms of minimum number of transmissions is close to the lower bound, and is better than random linear network coding when the field size is not so large.
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    ABSTRACT: Coding techniques may be useful for data center data survivability as well as for reducing traffic congestion. We present a queued cross-bar network (QCN) method that can be used for traffic analysis of both replication/uncoded and coded storage systems. We develop a framework for generating QCN rate regions (RRs) by analyzing their conflict graph stable set polytopes (SSPs). In doing so, we apply recent results from graph theory on the characterization of particular graph SSPs. We characterize the SSP of QCN conflict graphs under a variety of traffic patterns, allowing for their efficient RR computation. For uncoded systems, we show how to compute RRs and find rate optimal scheduling algorithms. For coded storage, we develop a RR upper bound, for which we provide an intuitive interpretation. We show that the coded storage RR upper bound is achievable in certain coded systems in which drives store sufficient coded information, as well in certain dynamic coding systems. Numerical illustrations show that coded storage can result in gains in RR volume of approximately 50%, averaged across traffic patterns.
  • Shama N. Islam, Parastoo Sadeghi, Salman Durrani
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    ABSTRACT: In this paper, we propose a novel user pairing scheme to reduce the error propagation in an amplify and forward (AF) based multi-way relay network (MWRN). We consider a user pairing scheme, where, a common user is chosen based on its average channel gain to form pairs with every other user in the MWRN. We show that choosing the common user as the user with the minimum average channel gain reduces the contribution of the interference components from the common user's signal in the extracted signals of other users. This leads to better bit error rate (BER) performance for all other users. For the common user, the BER improves at high SNR but it degrades at low SNR. The results show that the proposed pairing scheme outperforms the existing pairing scheme in terms of average BER of different users at high SNR.
    2014 IEEE Statistical Signal Processing Workshop (SSP); 06/2014
  • Parastoo Sadeghi, Rodney A. Kennedy, Zubair Khalid
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    ABSTRACT: In this paper we consider the zero-forcing (ZF) and minimum mean square error (MMSE) criteria for signal recovery using linear operators as equalizers for signals observed on the 2-sphere that are subject to linear distortions and noise. The distortions considered are bounded operators and can include convolutions, rotations, spatial and spectral truncations, projections or combinations of these. Likewise the signal and noise are very general being modeled as anisotropic stochastic processes on the 2-sphere. In both the distortion model and signal model the findings in this paper are significantly more general than results that can be found in the literature. The MMSE equalizer is shown to reduce to the ZF equalizer when the distortion operator has an inverse and there is an absence of noise. The ability of the MMSE to recover a Mars topography map signal from a projection operator, which fails to have a ZF solution, is given as an illustration.
    2014 IEEE Statistical Signal Processing Workshop (SSP); 06/2014
  • Amy Fu, Parastoo Sadeghi
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    ABSTRACT: In random linear network coding, rate control is an important strategy for limiting the decoding delay of a system. In broadcast systems where the channel rate is either unknown or varies over time, we demonstrate that a target delay can be achieved using the queue threshold scheme that we introduce. At throughputs approaching the channel rate, the queue threshold rate control scheme is shown to achieve improved throughput delay performance compared with existing schemes. We demonstrate that it is possible to modify this rate control scheme to greatly reduce the amount of feedback required, in exchange for a slight degradation of the throughput delay performance. Furthermore, this rate control scheme is shown to perform reasonably well, even under lossy and delayed feedback.
    ICC 2014 - 2014 IEEE International Conference on Communications; 06/2014
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    ABSTRACT: This paper introduces an adaptive, multi-resolution windowing technique that can be used in conjunction with the spatially localized spherical harmonic transform (SLSHT) to process signals on the 2-sphere in the spatio-spectral domain. In contrast with the standard formulation, which uses a fixed window, the new windowing technique is able to respond locally to the signal under analysis, that is, be adaptive, and also is formulated to depend on the spectral degree to give it a multi-resolution character. We further enhance its simultaneous spatial and spectral localization by basing the window on a parametric band-limited Slepian maximum spatial concentration eigenfunction. The criterion for window design is to maximize the energy concentration in each spectral component in the spatio-spectral domain. A computationally efficient method is also developed to implement the adaptive window design. An example is also provided to demonstrate the superiority of the new adaptive, multiresolution window technique.
    2014 IEEE Statistical Signal Processing Workshop (SSP); 06/2014
  • Rodney A. Kennedy, Zubair Khalid, Parastoo Sadeghi
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    ABSTRACT: In this paper we show that the spatially localized spherical harmonic transform (SLSHT), which represents a signal on the 2-sphere in the spatio-spectral domain, can be efficiently computed using new kernel-based formulations. In addition to the standard spatio-spectral domain, we show there are three other related transforms that provide alternative representations in the spatio-spatial, spectro-spatial and spectro-spectral domains. We provide inversion results that extend available results for the SLSHT. We show that for signals on the 2-sphere band-limited to degree L, the computational complexity using our class of kernel-based SLSHT transforms is O(L4) and outperforms the previous best known fast methods, which have complexity O(L5).
    ICASSP 2014 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP); 05/2014
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    Mohammad S. Karim, Parastoo Sadeghi, Neda Aboutorab
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    ABSTRACT: In this paper, we study in-order packet delivery in instantly decodable network coded systems for wireless broadcast networks.We are interested in particular applications, in which the successful delivery of a packet depends on the correct reception of this packet and all its preceding packets. We formulate the problem of minimizing the number of undelivered packets to all receivers over all transmissions until completion as a stochastic shortest path (SSP) problem. Although finding the optimal packet selection policy using SSP is computationally intractable, we employ this formulation to draw guidelines for the packet selection policies that can efficiently reduce the number of undelivered packets to all receivers over all transmissions until completion. According to these guidelines, we design a simple heuristic packet selection algorithm. In addition, we extend this heuristic to erasure channels with memory and introduce another layered algorithm. Simulation results illustrate that our proposed algorithms provide quicker delivery of the packets to the receivers compared to the existing algorithms in the literature.
  • Neda Aboutorab, Parastoo Sadeghi, Sameh Sorour
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    ABSTRACT: This paper studies the complicated interplay of the completion time (as a measure of throughput) and the decoding delay performance in instantly decodable network coded (IDNC) systems over wireless broadcast erasure channels with memory. We propose two new algorithms that enable a tradeoff for an improved balance between completion time and decoding delay of broadcasting a block of packets. We first formulate the IDNC packet selection problem that improves the balance between completion time and decoding delay as a statistical shortest path (SSP) problem. However, since finding such packet selection policy using the SSP technique is computationally complex, we employ its geometric structure to find some guidelines and use them to propose two efficient heuristic packet selection algorithms for broadcast erasure channels with a wide range of memory conditions. It is shown that each one of the two proposed algorithms is superior for a specific range of memory conditions. Furthermore, we show that the proposed algorithms achieve an improved fairness in terms of the decoding delay across all receivers.
    IEEE Transactions on Communications 04/2014; 62(4):1296-1309. DOI:10.1109/TCOMM.2014.021614.130172 · 1.98 Impact Factor

Publication Stats

957 Citations
113.30 Total Impact Points

Institutions

  • 2006–2015
    • Australian National University
      • College of Engineering & Computer Science
      Canberra, Australian Capital Territory, Australia
  • 2012
    • University of Canberra
      Canberra, Australian Capital Territory, Australia
  • 2011–2012
    • ACT, Inc.
      Iowa City, Iowa, United States
  • 2010
    • Texas A&M University
      • Department of Electrical and Computer Engineering
      College Station, Texas, United States
  • 2009
    • Sharif University of Technology
      • Department of Electrical Engineering
      Tehrān, Ostan-e Tehran, Iran
  • 2003–2005
    • University of New South Wales
      • School of Electrical Engineering and Telecommunications
      Kensington, New South Wales, Australia