Browsing by Subject "Multi-channel"
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Item Open Access Channel assignment and routing for multi-radio wireless mesh networks(Bilkent University, 2008) Özdemiray, Ahmet MuratWireless Mesh Network is a promising technology since it extends the range of wireless coverage by multi-hop transmission between routers. However, in multihop networks the total throughput decreases with increasing number of nodes and hops. To increase the total throughput, some mesh routers are equipped with multiple radios to use the available bandwidth of multiple non-overlapping channels. However, channel assignment should be done carefully to effectively use this available bandwidth. Moreover, the optimal channel assignment algorithm is NP-hard. In this thesis, we propose a joint channel assignment and routing solution to effectively use the available bandwidth for multi-radio wireless mesh networks with given network topology and traffic profile. Initially, we predict the final routes of the flows and estimate the loads on the links using these path predictions and given traffic profile. Then three different heuristics determine the assignment order of the links. Then the least busy channel among the available channels is assigned to the link. Finally, our routing algorithm routes the flows such that the selected path is the least busy path among the alternatives. We evaluated our channel assignment and routing algorithm using ns-2 simulator which supports multiple channels and multiple radios per node and we compared our results with single channel WMNs, and different algorithms for multi-radio multi-channel WMNs. The results show that our joint algorithm successfully achieves up to 5 times more throughput than single channel WMN with using just 2 radios and 3 channels. Our algorithms also out-performs other compared channel assignment algorithms for multi-radio multi-channel WMNs.Item Open Access Classification of multichannel ECoG related to individual finger movements with redundant spatial projections(IEEE, 2011) Onaran, ibrahim; İnce, N. Fırat; Çetin, A. EnisWe tackle the problem of classifying multichannel electrocorticogram (ECoG) related to individual finger movements for a brain machine interface (BMI). For this particular aim we applied a recently developed hierarchical spatial projection framework of neural activity for feature extraction from ECoG. The algorithm extends the binary common spatial patterns algorithm to multiclass problem by constructing a redundant set of spatial projections that are tuned for paired and group-wise discrimination of finger movements. The groupings were constructed by merging the data of adjacent fingers and contrasting them to the rest, such as the first two fingers (thumb and index) vs. the others (middle, ring and little). We applied this framework to the BCI competition IV ECoG data recorded from three subjects. We observed that the maximum classification accuracy was obtained from the gamma frequency band (65200Hz). For this particular frequency range the average classification accuracy over three subjects was 86.3%. These results indicate that the redundant spatial projection framework can be used successfully in decoding finger movements from ECoG for BMI. © 2011 IEEE.Item Open Access A hybrid SVM/HMM based system for the state detection of individual finger movements from multichannel ECoG signals(IEEE, 2011) Onaran, İbrahim; Ince, N.F.; Çetin, A. Enis; Abosch, A.A hybrid state detection algorithm is presented for the estimation of baseline and movement states which can be used to trigger a free paced neuroprostethic. The hybrid model was constructed by fusing a multiclass Support Vector Machine (SVM) with a Hidden Markov Model (HMM), where the internal hidden state observation probabilities were represented by the discriminative output of the SVM. The proposed method was applied to the multichannel Electrocorticogram (ECoG) recordings of BCI competition IV to identify the baseline and movement states while subjects were executing individual finger movements. The results are compared to regular Gaussian Mixture Model (GMM)-based HMM with the same number of states as SVM-based HMM structure. Our results indicate that the proposed hybrid state estimation method out-performs the standard HMM-based solution in all subjects studied with higher latency. The average latency of the hybrid decoder was approximately 290ms. © 2011 IEEE.Item Open Access Multichannel optical diode with unidirectional diffraction relevant total transmission(Optical Society of American (OSA), 2012) Serebryannikov, A.E.; Cakmak, A.O.; Özbay, EkmelWe will show that broadband unidirectional optical transmission with a total transmission maximum inside the band can be obtained for linearly polarized incident waves in the nonsymmetric photonic crystal gratings made of isotropic linear materials at a fixed nonzero or zero angle of incidence. Being based on the merging of diffraction and dispersion effects, the basic physical mechanism studied exploits the transmission channels associated with higher orders, for which asymmetry in the coupling conditions at the two grating interfaces appears when spatial inversion symmetry is broken. Total transmission in one direction and zero transmission in the opposite direction can be obtained due to hybridization of Fabry-Perot type resonances with a diffraction anomaly that yields a diode-like operation regime. Single-beam deflection and two-beam splitting can be obtained, for which transmission can be (nearly) total, if the corrugated side is illuminated. In contrast to the previous studies, it is also shown that unidirectional transmission can appear only at a fixed frequency and only due to diffractions, when total transmission occurs at the noncorrugated-side illumination, being in agreement with the Lorentz Lemma. © 2012 Optical Society of America.Item Open Access Tree-based channel assignment schemes for multi-channel wireless sensor networks(John Wiley & Sons Ltd., 2016) Terzi, C.; Korpeoglu, I.Many sensor node platforms used for establishing wireless sensor networks (WSNs) can support multiple radio channels for wireless communication. Therefore, rather than using a single radio channel for whole network, multiple channels can be utilized in a sensor network simultaneously to decrease overall network interference, which may help increase the aggregate network throughput and decrease packet collisions and delays. This method, however, requires appropriate schemes to be used for assigning channels to nodes for multi-channel communication in the network. Because data generated by sensor nodes are usually delivered to the sink node using routing trees, a tree-based channel assignment scheme is a natural approach for assigning channels in a WSN. We present two fast tree-based channel assignment schemes (called bottom up channel assignment and neighbor count-based channel assignment) for multi-channel WSNs. We also propose a new interference metric that is used by our algorithms in making decisions. We validated and evaluated our proposed schemes via extensive simulation experiments. Our simulation results show that our algorithms can decrease interference in a network, thereby increasing performance, and that our algorithms are good alternatives for static channel assignment in WSNs.Item Open Access Tree-based channel assignment schemes for multi-channel wireless sensor networks(Bilkent University, 2012) Terzi, ÇağlarA lot of sensor node platforms used for establishing wireless sensor networks (WSNs) can support multiple radio channels for wireless communication. Therefore, rather than using a radio single channel and sharing it for the whole network, multiple channels can be utilized in a sensor network simultaneously to decrease the overall interference in the network, which may help increasing the aggregate throughout in the network and decrease packet collisions and delay. This requires, however, appropriate channel assignment schemes to be used for assigning channels to the nodes for multi-channel communication in the network. Since, data generated by sensor nodes are usually carried to one or more sinks in the network using routing trees, tree-based channel assignment schemes are a natural approach for assigning channels in a WSN. We present two fast tree-based channel assignment schemes (called BUCA and NCCA) for multi-channel WSNs. We also propose a new network interference metric that is used in our algorithms while making decisions. We evaluate our proposed schemes by extensive simulation experiments and compare them with another well-known tree-based protocol from the literature. The results show that our proposed algorithms can provide better performance, up to 40% performance increase in some cases, compared to the other method. We also discuss in which cases the performance improvement can be achieved.