Ultra-wideband (UWB) multipath channels are assumed to have a sparse structure as the received consecutive pulses arrive with a considerable time delay and can be resolved individually at the receiver. Due to this sparse structure there has been a significant amount of interest in applying the compressive sensing (CS) theory to UWB channel estimation. There are various implementations of the CS theory for the UWB channel estimation based on the assumption that the UWB channels are sparse. However ...

The application of compressive sensing (CS) theory has found great interest in wideband spectrum sensing. Although most studies have considered perfect reconstruction of the primary user signal it is actually more important to assess the presence or absence of the signal. Among CS based methods Bayesian CS (BCS) takes into consideration the prior information of signal coefficients to be estimated which improves signal reconstruction performance. On the other hand the sparsity level of the signal ...

In conventional cooperative detection a fusion center decides on the presence or absence of the primary user by gathering all the information from secondary users and conveys this decision to all users. This approach does not take into account the locations of the secondary users where a user far from the primary user may also have to keep silent. In a recent work there has been a new detection method based on combining received signals from more than two users obtaining decision tables and deciding ...

In this paper a transfer matrix factorization based synthesis algorithm for resistively terminated low-pass LC ladder networks is presented. In the algorithm component value of the extracted element and the reflection factor of the remaining network are well formulated in terms of reflection factor coefficients of the whole network. An example is presented to exhibit the application of the proposed synthesis algorithm.

Filters which are studied in this paper have properties that lie between those of the Butterworth and Chebyshev filters. So it is appropriate to call this kind of filters as transitional Butterworth-Chebyshev filters. In this work different 6th order transitional filters are designed and their responses are compared with each other.

In this paper we propose a novel MIMO transmission scheme called trellis coded spatial modulation (TC-SM) in which the trellis (convolutional) encoder and the spatial modulation (SM) mapper are jointly designed similar to the conventional trellis coded modulation (TCM). A soft decision Viterbi decoder which is fed with the soft information supplied by the optimal SM decoder is used at the receiver. We derive the pairwise error probability (PEP) upper bound for the TC-SM scheme in uncorrelated ...

In this study by combining trellis coding with spatial modulation (SM) a new multiple-input multiple output (MIMO) communication scheme called trellis coded spatial modulation (TC-SM) is proposed. For uncorrelated Rayleigh fading channels code design criteria are given by deriving pairwise error probability (PEP) of this system in which a trellis encoder and SM mapper are jointly designed. These criteria are then used to obtain 4 8 and 16-states TC-SM schemes. It is shown via computer simulations ...

In this paper a new computationally efficient and high performance channel estimation algorithm is proposed for the indoor visible light communication (VLC) sparse channels in the presence of a clipping noise. The clipping noise is modelled as a Gaussian mixture and a first time in the literature the matching pursuit (MP) and the space-alternating expectation-maximization (SAGE) algorithms are combined into the new estimation called the SAGE-MP algorithm for iteratively estimating the sparse channel ...

A GRBF network is designed for VLSI implementation. Building blocks of the network consist mainly of analog circuits: op-amp multiplier multiplying DAC (digital to analog converter) floating resistor summer and exponentiator. Parameters of the network (center width of the Gaussian function and output layer weights) are represented digitally for convenient interfacing. It is shown that individual GRBF units allow independent tuning of center width and amplitude. Several network structures are ...

Neural networks may allow different organisations to extract knowledge from the data they collect about a similar problem domain. Moreover learning algorithms usually benefit from being able to use more training instances. But the parties owning the data are not always keen on sharing it. We propose a way to implement distributed learning to improve the performance of neural networks without sharing the actual data among different organisations. This paper deals with the alternative methods of ...