Spectral Emission Mask Shaping for OFDM in Cognitive Radios

Orthogonal frequency division multiplexing (OFDM) is characterized by spectral efficiency. It enables flexible and agile spectrum allocation. But still it lags as it suffers from spectral leakage in the form of large side lobes. It leads to inter-channel interference if not handled carefully.in proposed system spectral emission mask system is implemented to combat spectral leakage and ultimately avoiding adjacent channel interference. A spectral mask, also known as a channel mask or transmission mask is a mathematically-defined set of lines applied to the levels of radio (or optical) transmissions. The spectral mask is generally intended to reduce adjacent-channel interference by limiting excessive radiation at frequencies beyond the necessary bandwidth. The proposed system is implemented over MATLAB platform using script language.

Comparative Analysis of Spectral Emission Mask Shaping for OFDM

In this paper orthogonal frequency division multiplexing (OFDM) is characterized by spectral efficiency. Here we use quadrature Amplitude Modulation (QAM) it is used to improved spectral efficiency. For digital modulations designing new spectrally efficient pulse shapes. When established through an additive white Gaussian noise (AWGN) channel the pulses designed for finite period and give zero inter symbol interference. In proposed system spectral emission mask system is implemented to conflict spectral leakage and ultimately avoiding adjacent channel interference. A spectral mask also known as a transmission mask or channel mask. It is a mathematically-defined set of lines applied to the levels of radio transmissions. The spectral mask is generally proposed to reduce adjacent-channel interference by preventive excessive radiation at frequencies at 20MHz bandwidth. The proposed system is implemented over MATLAB platform using script language.

Accelerating and Improving Simulation Performance in Communication Systems Modelling through Parallel Computing and Clustering

Existing 5G communication systems suffer from two major problems: the need for better spectrum efficiency and lesser adjacent channel interference. Thus, development of novel waveform techniques to overcome these problems is a major topic of research amongst scholars and it requires carrying out Monte Carlo simulations in MATLAB© (by MathWorks) to measure the Bit Error Rate (BER) of these communication models. As most of these simulations require millions of computations, they take a significantly long time to run (for example, days) as they run on single-core machines and carry out the computations serially. The main objective of this research is to reimplement current scripts using various parallel computing techniques in MATLAB to study which one is the best suited for this particular type of simulations while also scaling these scripts onto a multi-core cluster to further improve the execution time.