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  • 1.
    Adjiashvili, David
    et al.
    ETH, Switzerland.
    Bosio, Sandro
    ETH, Switzerland.
    Li, Yuan
    Lund University, Sweden.
    Yuan, Di
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, The Institute of Technology.
    Exact and Approximation Algorithms for Optimal Equipment Selection in Deploying In-Building Distributed Antenna Systems2015In: IEEE Transactions on Mobile Computing, ISSN 1536-1233, E-ISSN 1558-0660, Vol. 14, no 4, p. 702-713Article in journal (Refereed)
    Abstract [en]

    We consider a combinatorial optimization problemin passive In-Building Distributed Antenna Systems (IB-DAS) deployment for indoor mobile broadband service. These systems have a tree topology, in which a central base station is connected to a number of antennas located at tree leaves via cables represented by the tree edges. Each inner node corresponds to a power equipment, of which the available types differ in the number of output ports and/or by power gain at the ports. This paper focuses on the equipment selection problemthat amounts to, for a given passive DAS tree topology, selecting a power equipment type for each inner node and assigning the outgoing edges of the node to the equipment ports. The performance metric is the power deviation at the antennas from the target values. We consider as objective function the minimization of either the total or the largest power deviation over all antennas. Our contributions are the development of exact pseudo-polynomial time algorithms and (additive) fully-polynomial time approximation schemes for both objectives. Numerical results are provided to illustrate the algorithms. We also extend some results to account for equipment cost.

  • 2.
    Curescu, C.
    et al.
    Ericsson Research, Torshamnsgatan 23, Kista, 164 83 Stockholm, Sweden.
    Nadjm-Tehrani, Simin
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, RTSLAB - Real-Time Systems Laboratory.
    A bidding algorithm for optimized utility-based resource allocation in ad hoc networks2008In: IEEE Transactions on Mobile Computing, ISSN 1536-1233, E-ISSN 1558-0660, Vol. 7, no 12, p. 1397-1414Article in journal (Refereed)
    Abstract [en]

    This paper proposes a scheme for bandwidth allocation in wireless ad hoc networks. The quality-of-service (QoS) levels for each end-to-end flow are expressed using a resource-utility function, and our algorithms aim to maximize aggregated utility. The shared channel is modeled as a bandwidth resource defined by maximal cliques of mutual interfering links. We propose a novel resource allocation algorithm that employs an auction mechanism in which flows are bidding for resources. The bids depend both on the flow's utility function and the intrinsically derived shadow prices. We then combine the admission control scheme with a utility-aware on-demand shortest path routing algorithm where shadow prices are used as a natural distance metric. As a baseline for evaluation, we show that the problem can be formulated as a linear programming (LP) problem. Thus, we can compare the performance of our distributed scheme to the centralized LP solution, registering results very close to the optimum. Next, we isolate the performance of price-based routing and show its advantages in hotspot scenarios, and also propose an asynchronous version that is more feasible for ad hoc environments. Further experimental evaluation compares our scheme with the state of the art derived from Kelly's utility maximization framework and shows that our approach exhibits superior performance for networks with increased mobility or less frequent allocations. © 2008 IEEE.

  • 3.
    He, Qing
    et al.
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Yuan, Di
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Ephremides, Anthony
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering. Department of Electrical and Computer Engineering, University of Maryland, USA.
    Maximum Link Activation with Cooperative Transmission and Interference Cancellation in Wireless Networks2017In: IEEE Transactions on Mobile Computing, ISSN 1536-1233, E-ISSN 1558-0660, Vol. 16, no 2, p. 408-421Article in journal (Refereed)
    Abstract [en]

    We address the maximum link activation problem in wireless networks with new features, namely when the transmitters can perform cooperative transmission, and the receivers are able to perform successive interference cancellation. In this new problem setting, which transmitters should transmit and to whom, as well as the optimal cancellation patterns at the receivers, are strongly intertwined. We present contributions along three lines. First, we provide a thorough tractability analysis, proving the NP-hardness as well as identifying tractable cases. Second, for benchmarking purposes, we deploy integer linear programming for achieving global optimum using off-theshelf optimization methods. Third, to overcome the scalability issue of integer programming, we design a sub-optimal but efficient optimization algorithm for the problem in its general form, by embedding maximum-weighted bipartite matching into local search. Numerical results are presented for performance evaluation, to validate the benefit of cooperative transmission and interference cancellation for maximum link activation and to demonstrate the effectiveness of the proposed algorithm.

  • 4.
    Yuan, Di
    et al.
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, The Institute of Technology.
    Haugland, Dag
    University of Bergen, Norway .
    Dual Decomposition for Computational Optimization of Minimum-Power Shared Broadcast Tree in Wireless Networks2012In: IEEE Transactions on Mobile Computing, ISSN 1536-1233, E-ISSN 1558-0660, Vol. 11, no 12, p. 2008-2019Article in journal (Refereed)
    Abstract [en]

    We consider the problem of constructing a shared broadcast tree (SBT) in wireless networks, such that the total power required for supporting broadcast initiated by all source nodes is minimal. In the well-studied minimum-energy broadcast (MEB) problem, the optimal tree varies by source. In contrast, SBT is source-independent, thus substantially reducing the overhead for information storage and processing. The SBT problem also differs from the range assignment problem (RAP), because the power for message forwarding in SBT, although being source-independent, depends on from which tree neighbor the message is received. We approach SBT from a computational optimization standpoint, and present a dual decomposition method applied to an optimization model that embeds multiple directed trees into a shared tree. For the dual decomposition method, some of the constraints in the model are preferably formulated implicitly. The dual decomposition scheme is coupled with a fast local search algorithm. We report computational results demonstrating the effectiveness of the proposed approach. In average, the performance gap to global optimality is less than three percent.

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