A novel pulse shaping filter satisfying the Nyquist-I criterion was derived and implemented to reduce the peak-to-average power ratio (PAPR) over a Single Carrier Frequency Division Multiple Access (SC-FDMA) scheme. The new filter reduces the PAPR, while maintaining the same excess bandwidth and the zero intersymbol interference condition. The novel filter contains a new design parameter β to minimize PAPR, which is independent from the roll-off factor ?. The minimum PAPR of the SC-FDMA scheme is linked to the value given to the parameter β for a specific roll-off factor ?. Several simulations showed that PAPR is reduced greatly compared to that of the raised cosine filter, which is widely used in wireless communications. The performance of the proposed pulse shaping filter, regarding PAPR, is also compared with those of other conventional filters, demonstrating that the new filter has a superior performance.

PAPR Reduction in Single Carrier FDMA Uplink by Pulse Shaping Using a β-α Filter

Different learning algorithms have different accuracies. The no free lunch theorem asserts that no single learning algorithm always achieves the best performance in any domain. They can be combined to attain higher accuracy. Data fusion is the process of fusing multiple records representing the same real-world object into a single, consistent, and clean representation. Fusion of data for improving prediction accuracy and reliability is an important problem in machine learning.

Combining Multiple Learners: Data Fusion and Emsemble Learning

The ever-growing need for high data rate, bandwidth efficiency, reliability, less complexity and less power consumption in our communication systems is on the increase. Modern techniques have to be developed and put in place to meet these requirements. Research has shown, that compared to conventional Single input Single output (SISO) systems, Multipleinput Single output (MISO), and Multiple-input multiple-output (MIMO) can actually increase the data rate of a communication system, without actually requiring more transmit power or bandwidth. This paper aims at the investigation of the existing channel estimation techniques. Based on the pilot arrangement, the block type and comb type are compared, employing the Least Square estimation (L.S) and Minimum Mean Squared Error (MMSE) estimators. Pilots occupy bandwidth, minimizing the number of pilots used to estimate the channel, in order to allow for more bandwidth utilization for data transmission, without compromising the accuracy of the estimates is taken into consideration. Various channel interpolation techniques and pilot-data insertion ratio are investigated, simulated and compared, to determine the best performance technique with less complexity and minimum power consumption. As performance measures, the Mean squared error (MSE) and Bit error rate (BER) as a function of Signal to noise power ratio (SNR) of the different channel estimation techniques are plotted, in order to identify the technique with the most optimal performance. The complexity and energy efficiency of the techniques are also investigated. The system modelling and simulations are carried out using Matlab simulation package. The MIMO gives the optimum performance, followed by the MISO and SISO. This is as a result of the diversity and multiplexing gain experienced in the multiple antenna techniques using the STBC.

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Comparative Analysis of Channel Estimation Techniques in SISO, MISO and MIMO Systems

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Multi-Frequency Image Fusion Based on MIMO UWB OFDM Synthetic Aperture Radar

Generally vehicular ad hoc networks (VANETs) carry information public in nature, which benefits most of the vehicular nodes involved. Therefore broadcasting data becomes a natural choice for disseminating data in VANETs. Broadcasting also offers advantages of simplicity and flexibility, by virtue of not requiring knowledge of the actual network topology. Further-more, so-called delay-based vehicular broadcast mechanisms have been proven efficient in reducing redundant packet transmissions in dense networks. However, packet losses due to the imperfect wireless medium, medium access, and high mobility decrease this efficiency dramatically, re-introducing needless transmissions. In this paper, we propose a Delay-based Opportunistic Network Coding protocol called `DONC', which combines delay-based techniques with opportunistic network coding, in order to successfully cancel this detrimental effect of losses: DONC improves dissemination of broadcast data in loss-prone VANETs and reduces packet retransmissions. We simulate DONC protocol in ns2 and compare it with classical delay-based VANET broadcast mechanisms. Results prove that DONC protocol outperforms other delay-based mechanisms, specially in the scenario of lossy VANETs.

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DONC: Delay-based Opportunistic Network Coding Protocol

: The feasibility for producing ELF signals in the earth ionospheric waveguide, by downconverting H.F. pump power in the ionospheric plasma has been investigated. We have found that: (i) Interaction regions of horizontal width approx. 100km, localized inside an ionospheric density gradient, can deplete the pump for pump powers above a threshold value. Minimum threshold is achieved for pumps propagating almost perpendicular to the density gradient (very oblique incidence) at 100 km altitude. The threshold power required is between 3-10 MW of H.F. (ii) The conversion efficiency from H.F. to ELF in the ionosphere could reach values of the order of 0.01. (iii) The scheme can operate either as an ELF generator if we use an H.F. pump with power 3-10 MW and a lower H.F. sideband with power 100 kw, or as an amplifier of ELF signals from weak ground transmitters (such as the Wisconsin test facility), or from weak space or balloon based antennas. A variation of the scheme can operate as a broadband ELF generator for jamming purposes. (Author)

D. Papadopoulos

Papers

Wireless Communication Systems.