Current Issue : January - March Volume : 2014 Issue Number : 1 Articles : 4 Articles
Due to interference between co-located wireless networks, obtaining accurate channel assessment becomes\r\nincreasingly important for wireless network configuration. This information is used, among others, for cognitive radio\r\nsolutions and for intelligent channel selection in wireless networks. Solutions such as spectrum analyzers are capable\r\nof scanning a wide spectrum range, but are not dedicated for channel occupation assessment because they are\r\nextremely costly and not able to perform continuous recording for a time period longer than a few seconds. On the\r\nother hand, low-cost solutions lack the flexibility and required performance in terms of configuration and sensing\r\nefficiency. To remedy the situation, this paper presents an alternative for channel assessment on top of a commercial\r\nsoftware-defined radio platform. Although there exist software solutions for performing spectrum sensing on such\r\nplatforms, to the best of our knowledge, continuous spectrum sensing and long-term recording remain challenging.\r\nWe propose a pioneering solution that is capable of seamless spectrum sensing over a wide spectrum band and\r\nguarantees sufficient flexibility in terms of configurations. The proposed solution is validated experimentally. We\r\ndemonstrate two advantages of seamless spectrum sensing: the capability of accurate channel occupancy\r\nmeasurement and detecting transient signals such as Bluetooth....
Long-term monitoring of an environment is a fundamental requirement for most wireless sensor networks. Owing to\r\nthe fact that the sensor nodes have limited energy budget, prolonging their lifetime is essential in order to permit\r\nlong-term monitoring. Furthermore, many applications require sensor nodes to obtain an accurate estimation of a\r\npoint-source signal (for example, an animal call or seismic activity). Commonly, multiple sensor nodes simultaneously\r\nsample and then cooperate to estimate the event signal. The selection of cooperation nodes is important to reduce\r\nthe estimation error while conserving the networkââ?¬â?¢s energy. In this paper, we present a novel method for sensor data\r\nacquisition and signal estimation, which considers estimation accuracy, energy conservation, and energy balance. The\r\nmethod, using a concept of ââ?¬Ë?virtual clusters,ââ?¬â?¢ forms groups of sensor nodes with the same spatial and temporal\r\nproperties. Two algorithms are used to provide functionality. The ââ?¬Ë?distributed formationââ?¬â?¢ algorithm automatically\r\nforms and classifies the virtual clusters. The ââ?¬Ë?round robin sample schemeââ?¬â?¢ schedules the virtual clusters to sample the\r\nevent signals in turn. The estimation error and the energy consumption of the method, when used with a generalized\r\nsensing model, are evaluated through analysis and simulation. The results show that this method can achieve an\r\nimproved signal estimation while reducing and balancing energy consumption....
According to the ongoing IEEE 802.11ac amendment, the wireless network is about to embrace the\r\ngigabit-per-second raw data rate. Compared with previous IEEE standards, this significant performance improvement\r\ncan be attributed to the novel physical and medium access control (MAC) features, such as multi-user multiple-input\r\nmultiple-output transmissions, the frame aggregation, and the channel bonding. In this paper, we first briefly survey\r\nthe main features of IEEE 802.11ac, and then, we evaluate these new features in a fully connected wireless mesh\r\nnetwork using an analytic model and simulations. More specifically, the performance of the MAC scheme defined by\r\nIEEE 802.11ac, which employs the explicit compressed feedback (ECFB) mechanism for the channel sounding, is\r\nevaluated. In addition, we propose an extended request-to-send/clear-to-send scheme that integrates the ECFB\r\noperation to compare with the IEEE 802.11ac-defined one in saturated conditions. The comparison of the two MAC\r\nschemes is conducted through three spatial stream allocation algorithms. A simple but accurate analytical model is\r\nderived for the two MAC schemes, the results of which are validated with simulations. The observations of the results\r\nnot only reveal the importance of spatial stream allocations but also provide insight into how the newly introduced\r\nfeatures could affect the performance of IEEE 802.11ac-based wireless mesh networks....
In this paper, a reduced complexity Log-MAP algorithm based on a non-recursive approximation of the max*\r\noperator is presented and studied for turbo trellis-coded modulation (TTCM) systems. In the algorithm, denoted as\r\nAvN Log-MAP, the max* operation is generalized and performed on n = 2 arguments. The approximation is derived\r\nfrom the Jensen inequality. The non-recursive form of the max* calculations allows to achieve significant reduction in\r\nthe decoding effort in comparison to the conventional Log-MAP algorithm. Bit-error rate performance simulation\r\nresults for serial and parallel TTCM schemes in the additive white Gaussian noise and uncorrelated Rayleigh fading\r\nchannels show that the AvN Log-MAP algorithm performs close to the Log-MAP. Performance and complexity\r\ncomparisons of the AvN Log-MAP algorithm against the Log-MAP and several relevant reduced complexity turbo\r\ndecoding algorithms proposed in the literature reveal, that it offers favorable low computational effort for the price of\r\nsmall performance degradation....
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