10,132 research outputs found

    Throughput sensitivity to antenna pattern and orientation in 802.11n networks

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    Design of a Finger Ring Antenna for Wireless Sensor Networks

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    Body-centric communications have become very active area of research due to ever-growing demand of portability. Advanced applications such as; health monitoring, tele-medicine, identification systems, performance monitoring of athletes, defence systems and personal entertainment are adding to its popularity. In this paper, a novel wearable antenna radiating at 5 GHz for the body-centric wireless sensor networks has been presented. The antenna consists of a conventional microstrip patch mounted on a gold base and could be worn in a finger like a ring. CST Microwave Studio is used for modelling, simulation and optimisation of the antenna. The simulated results show that the proposed antenna has a -10 dB bandwidth of 90.3 MHz with peak gain of 6.9 dBi. Good performance in terms of bandwidth, directivity, gain, return loss and radiation characteristics, along with a miniaturised form factor makes it a very well suited candidate for the body-worn wireless sensor applications

    Indoor wireless communications and applications

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    Chapter 3 addresses challenges in radio link and system design in indoor scenarios. Given the fact that most human activities take place in indoor environments, the need for supporting ubiquitous indoor data connectivity and location/tracking service becomes even more important than in the previous decades. Specific technical challenges addressed in this section are(i), modelling complex indoor radio channels for effective antenna deployment, (ii), potential of millimeter-wave (mm-wave) radios for supporting higher data rates, and (iii), feasible indoor localisation and tracking techniques, which are summarised in three dedicated sections of this chapter

    An Iterative Receiver for OFDM With Sparsity-Based Parametric Channel Estimation

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    In this work we design a receiver that iteratively passes soft information between the channel estimation and data decoding stages. The receiver incorporates sparsity-based parametric channel estimation. State-of-the-art sparsity-based iterative receivers simplify the channel estimation problem by restricting the multipath delays to a grid. Our receiver does not impose such a restriction. As a result it does not suffer from the leakage effect, which destroys sparsity. Communication at near capacity rates in high SNR requires a large modulation order. Due to the close proximity of modulation symbols in such systems, the grid-based approximation is of insufficient accuracy. We show numerically that a state-of-the-art iterative receiver with grid-based sparse channel estimation exhibits a bit-error-rate floor in the high SNR regime. On the contrary, our receiver performs very close to the perfect channel state information bound for all SNR values. We also demonstrate both theoretically and numerically that parametric channel estimation works well in dense channels, i.e., when the number of multipath components is large and each individual component cannot be resolved.Comment: Major revision, accepted for IEEE Transactions on Signal Processin

    Random neural network based cognitive-eNodeB deployment in LTE uplink

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