31 research outputs found

    Wireless Cloud Architecture Based on Thin Clients and Ontologies

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    Recently, several researchers have discovered the need for radios to use description techniques for the objects in the wireless realm. The concept of RF field-programmable analog array (FPAA) was also proposed recently and the lack of hardware abstractions was identified as a problem. We propose a hardware abstraction for RF FPAAs, which enables an open RF-digital interface. We advance the concept of wireless thin clients. These clients are connected to the cloud using the open RF-digital interface. We describe the architecture of a comprehensive wireless ontology

    Wireless communication standards: a study of IEEE 80211 80215 and 80216

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    Wireless communication standards

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    Hands-On Open Access Broadband Wireless Technology Lab Mapping Course Outcomes to Lab Experiments

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    The unprecedented growth in wireless communication is offering opportunities and challenges for educators. Thanks to technology advances and job opportunities, more and more students are interested in wireless communications courses. However, bridging the gap between classroom and real-world experience remains a challenge. Advanced undergraduate communications courses typically focus more on theory. Some courses are given online, and lack hands-on experiments. Driven by feedback from industry and students, we propose practical laboratory experiments that attempt to bridge the gap between classroom and real world. The laboratory exercises take advantage of the infrastructure of deployed wireless networks and allow students to measure, and analyze data, as well as to interact. The proposed labs can be used even in online courses. This paper describes the experiments proposed, the procedures and typical results. The experiments are tied to course objective

    An Open RF-Digital Interface for Software-Defined Radios

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    Improved low-complexity zero-padded OFDM receivers

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    The recently suggested Generalized Prefix–Orthogonal Frequency Division Multiplexing (GP–OFDM) uses an optimal non-zero guard interval (GI). A GI consisting of all zeros is also known, and the technique is referred to as Zero Padding (ZP–OFDM). ZP–OFDM performs very well, but suffers from a complexity problem. This paper provides two improved and low-complexity receiver designs for ZP–OFDM, which make the convolutions between the transmitted signal and the channel skew-cyclic. The channel matrix becomes ϕ-circulant. Both designs require a one-dimensional optimization. The first new design requires the result of the optimization to be available at the transmitter. The second new design eliminates completely the feedback to the transmitter. Simulation results indicate that proposed ZP–OFDM receivers have significant performance advantages compared with existing ZP–OFDM receivers such as ZP–OFDM–OLA and ZP–OFDM–FAST. The performance advantages are maintained in the presence of channel estimation errors and error-correction coding

    Improved low-complexity zero-padded OFDM receivers

    No full text
    The recently suggested Generalized Prefix-Orthogonal Frequency Division Multiplexing (GP-OFDM) uses an optimal non-zero guard interval (GI). A GI consisting of all zeros is also known, and the technique is referred to as Zero Padding (ZP-OFDM). ZP-OFDM performs very well, but suffers from a complexity problem. This paper provides two improved and low-complexity receiver designs for ZP-OFDM, which make the convolutions between the transmitted signal and the channel skew-cyclic. The channel matrix becomes phi-circulant. Both designs require a one-dimensional optimization. The first new design requires the result of the optimization to be available at the transmitter. The second new design eliminates completely the feedback to the transmitter. Simulation results indicate that proposed ZP-OFDM receivers have significant performance advantages compared with existing ZP-OFDM receivers such as ZP-OFDM-OLA and ZP-OFDM-FAST. The performance advantages are maintained in the presence of channel estimation errors and error-correction coding. (C) 2016 Elsevier Inc. All rights reserved
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