1,156,712 research outputs found

    Summary of the active microwave users workshop

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    A coordinated microwave applications development program was initiated to improve the capability to: (1) identify, monitor, and assess the earth's resources; and (2) monitor the earth's environment and predict significant changes. The program consists of the scientific, technical, and programmatic activities required to develop microwave remote sensing into an operational tool for systematic earth observations

    Active microwave users working group program planning

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    A detailed programmatic and technical development plan for active microwave technology was examined in each of four user activities: (1) vegetation; (2) water resources and geologic applications, and (4) oceanographic applications. Major application areas were identified, and the impact of each application area in terms of social and economic gains were evaluated. The present state of knowledge of the applicability of active microwave remote sensing to each application area was summarized and its role relative to other remote sensing devices was examined. The analysis and data acquisition techniques needed to resolve the effects of interference factors were reviewed to establish an operational capability in each application area. Flow charts of accomplished and required activities in each application area that lead to operational capability were structured

    Slow transitions, slow mixing and starvation in dense random-access networks

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    We consider dense wireless random-access networks, modeled as systems of particles with hard-core interaction. The particles represent the network users that try to become active after an exponential back-off time, and stay active for an exponential transmission time. Due to wireless interference, active users prevent other nearby users from simultaneous activity, which we describe as hard-core interaction on a conflict graph. We show that dense networks with aggressive back-off schemes lead to extremely slow transitions between dominant states, and inevitably cause long mixing times and starvation effects.Comment: 29 pages, 5 figure

    Predicting Social Links for New Users across Aligned Heterogeneous Social Networks

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    Online social networks have gained great success in recent years and many of them involve multiple kinds of nodes and complex relationships. Among these relationships, social links among users are of great importance. Many existing link prediction methods focus on predicting social links that will appear in the future among all users based upon a snapshot of the social network. In real-world social networks, many new users are joining in the service every day. Predicting links for new users are more important. Different from conventional link prediction problems, link prediction for new users are more challenging due to the following reasons: (1) differences in information distributions between new users and the existing active users (i.e., old users); (2) lack of information from the new users in the network. We propose a link prediction method called SCAN-PS (Supervised Cross Aligned Networks link prediction with Personalized Sampling), to solve the link prediction problem for new users with information transferred from both the existing active users in the target network and other source networks through aligned accounts. We proposed a within-target-network personalized sampling method to process the existing active users' information in order to accommodate the differences in information distributions before the intra-network knowledge transfer. SCAN-PS can also exploit information in other source networks, where the user accounts are aligned with the target network. In this way, SCAN-PS could solve the cold start problem when information of these new users is total absent in the target network.Comment: 11 pages, 10 figures, 4 table

    Area Spectral Efficiency Analysis and Energy Consumption Minimization in Multi-Antenna Poisson Distributed Networks

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    This paper aims at answering two fundamental questions: how area spectral efficiency (ASE) behaves with different system parameters; how to design an energy-efficient network. Based on stochastic geometry, we obtain the expression and a tight lower-bound for ASE of Poisson distributed networks considering multi-user MIMO (MU-MIMO) transmission. With the help of the lower-bound, some interesting results are observed. These results are validated via numerical results for the original expression. We find that ASE can be viewed as a concave function with respect to the number of antennas and active users. For the purpose of maximizing ASE, we demonstrate that the optimal number of active users is a fixed portion of the number of antennas. With optimal number of active users, we observe that ASE increases linearly with the number of antennas. Another work of this paper is joint optimization of the base station (BS) density, the number of antennas and active users to minimize the network energy consumption. It is discovered that the optimal combination of the number of antennas and active users is the solution that maximizes the energy-efficiency. Besides the optimal algorithm, we propose a suboptimal algorithm to reduce the computational complexity, which can achieve near optimal performance.Comment: Submitted to IEEE Transactions on Wireless Communications, Major Revisio

    Asymptotic Error Free Partitioning over Noisy Boolean Multiaccess Channels

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    In this paper, we consider the problem of partitioning active users in a manner that facilitates multi-access without collision. The setting is of a noisy, synchronous, Boolean, multi-access channel where KK active users (out of a total of NN users) seek to access. A solution to the partition problem places each of the NN users in one of KK groups (or blocks) such that no two active nodes are in the same block. We consider a simple, but non-trivial and illustrative case of K=2K=2 active users and study the number of steps TT used to solve the partition problem. By random coding and a suboptimal decoding scheme, we show that for any T(C1+ξ1)logNT\geq (C_1 +\xi_1)\log N, where C1C_1 and ξ1\xi_1 are positive constants (independent of NN), and ξ1\xi_1 can be arbitrary small, the partition problem can be solved with error probability Pe(N)0P_e^{(N)} \to 0, for large NN. Under the same scheme, we also bound TT from the other direction, establishing that, for any T(C2ξ2)logNT \leq (C_2 - \xi_2) \log N, the error probability Pe(N)1P_e^{(N)} \to 1 for large NN; again C2C_2 and ξ2\xi_2 are constants and ξ2\xi_2 can be arbitrarily small. These bounds on the number of steps are lower than the tight achievable lower-bound in terms of T(Cg+ξ)logNT \geq (C_g +\xi)\log N for group testing (in which all active users are identified, rather than just partitioned). Thus, partitioning may prove to be a more efficient approach for multi-access than group testing.Comment: This paper was submitted in June 2014 to IEEE Transactions on Information Theory, and is under review no
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