8,734 research outputs found

    Decentralized Fair Scheduling in Two-Hop Relay-Assisted Cognitive OFDMA Systems

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    In this paper, we consider a two-hop relay-assisted cognitive downlink OFDMA system (named as secondary system) dynamically accessing a spectrum licensed to a primary network, thereby improving the efficiency of spectrum usage. A cluster-based relay-assisted architecture is proposed for the secondary system, where relay stations are employed for minimizing the interference to the users in the primary network and achieving fairness for cell-edge users. Based on this architecture, an asymptotically optimal solution is derived for jointly controlling data rates, transmission power, and subchannel allocation to optimize the average weighted sum goodput where the proportional fair scheduling (PFS) is included as a special case. This solution supports decentralized implementation, requires small communication overhead, and is robust against imperfect channel state information at the transmitter (CSIT) and sensing measurement. The proposed solution achieves significant throughput gains and better user-fairness compared with the existing designs. Finally, we derived a simple and asymptotically optimal scheduling solution as well as the associated closed-form performance under the proportional fair scheduling for a large number of users. The system throughput is shown to be O(N(1qp)(1qpN)lnlnKc)\mathcal{O}\left(N(1-q_p)(1-q_p^N)\ln\ln K_c\right), where KcK_c is the number of users in one cluster, NN is the number of subchannels and qpq_p is the active probability of primary users.Comment: 29 pages, 9 figures, IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSIN

    Queue-Aware Distributive Resource Control for Delay-Sensitive Two-Hop MIMO Cooperative Systems

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    In this paper, we consider a queue-aware distributive resource control algorithm for two-hop MIMO cooperative systems. We shall illustrate that relay buffering is an effective way to reduce the intrinsic half-duplex penalty in cooperative systems. The complex interactions of the queues at the source node and the relays are modeled as an average-cost infinite horizon Markov Decision Process (MDP). The traditional approach solving this MDP problem involves centralized control with huge complexity. To obtain a distributive and low complexity solution, we introduce a linear structure which approximates the value function of the associated Bellman equation by the sum of per-node value functions. We derive a distributive two-stage two-winner auction-based control policy which is a function of the local CSI and local QSI only. Furthermore, to estimate the best fit approximation parameter, we propose a distributive online stochastic learning algorithm using stochastic approximation theory. Finally, we establish technical conditions for almost-sure convergence and show that under heavy traffic, the proposed low complexity distributive control is global optimal.Comment: 30 pages, 7 figure

    Influence of different polishing materials in the material removal of steel samples

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    The quality of injection moulded polymer optic parts depends on the surface finish of the respective mould. In order to improve and control the surface finish of the mould it is important to be able to keep the material removal constant during the polishing process of these moulds. This will provide a tactical material removal therefore allowing a controlled correction of the mould’s surface geometry. The aim of this work is to study the influence of different polishing materials in the material removal rate and its reproducibility during the polishing process of hardened steel. Different polyurethane polishing materials with different fillers were tested. It was observed that the filler material of the polyurethane is crucial in order to obtain constant and reproducible results. Experiments were carried out with an industrial robot and the material removal’s depth value was compared

    Mobility Increases the Data Offloading Ratio in D2D Caching Networks

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    Caching at mobile devices, accompanied by device-to-device (D2D) communications, is one promising technique to accommodate the exponentially increasing mobile data traffic. While most previous works ignored user mobility, there are some recent works taking it into account. However, the duration of user contact times has been ignored, making it difficult to explicitly characterize the effect of mobility. In this paper, we adopt the alternating renewal process to model the duration of both the contact and inter-contact times, and investigate how the caching performance is affected by mobility. The data offloading ratio, i.e., the proportion of requested data that can be delivered via D2D links, is taken as the performance metric. We first approximate the distribution of the communication time for a given user by beta distribution through moment matching. With this approximation, an accurate expression of the data offloading ratio is derived. For the homogeneous case where the average contact and inter-contact times of different user pairs are identical, we prove that the data offloading ratio increases with the user moving speed, assuming that the transmission rate remains the same. Simulation results are provided to show the accuracy of the approximate result, and also validate the effect of user mobility.Comment: 6 pages, 5 figures, accepted to IEEE Int. Conf. Commun. (ICC), Paris, France, May 201
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