Simultaneous Determination Of Modulation Types And Signal-To-Noise Ratios In Wireless Communication Systems - Almohamad, Tarik Adnan (2019)
Signal parameters determination techniques can offer more reliability, larger bandwidth, and higher security to the modern wireless systems. However, the performance comparison of such determination techniques is not straightforward. This can be attributed to the lack of having benchmarks datasets in the wireless communication research community as compared to other research fields. Hence, there is a need to propose potentially-benchmark datasets that can be a future choice for researchers in the wireless communication domain, motivating the first contribution in this thesis. Most of the up-to-date solutions of signal parameters determination techniques focus on determining only one single parameter for example modulation type and assuming the other parameters e.g. signal-to-noise ratio (SNR) are known rather than on determining multiple signal parameters jointly. Hence, the desire to enable an autonomous capability of simultaneous determination of multiple signal parameters has motivated the second and third contributions that tackle the non-coherent and coherent receivers, respectively. Therefore, the objectives in this thesis are as follows, firstly, to construct three datasets for the aforesaid receivers to be utilized for joint determination of modulation types and signal-to-noise ratios, namely asynchronous amplitudes histograms (AAHs)-based Dataset, two-dimension alasynchronous sampling in-phase-quadrature histograms (2D-ASIQHs)-based Dataset 1 and 2D-ASIQHs-based Dataset 2. Secondly, to develop a scheme that cansimultaneously determine the modulation type and signal-to-noise ratio in non-coherent receivers by using one features’ type (AAHs-based features) under a multipath fading scenario. Lastly, to develop a scheme that can simultaneously determine the modulation type and signal-to-noise ratio in coherent receivers by employing 2D-ASIQHs features under Rician and Rayleigh fading. For datasets formation, the three datasets are developed under multipath fading channels and used to validate the proposed determination schemes in the second and third contributions. The simultaneous determination AAHs-based scheme enables a generic intelligent receiver to recognize various modulations that belong to different categories and reveals that the recognition capability can be extendable further to other more signal types. The scheme can also simultaneously estimate the SNR values accurately. The simultaneous determination 2D-ASIQHs-based scheme tackles the coherent receivers to jointly determine nine modulation types and a wide range of SNRs. The most significant features are extracted using principal component analysis (PCA) and then fed to a support vector machine (SVM) tool for the automatic learning process. In the simulation results, the samples of the datasets reflect 1D-envelope histograms and in-phase-quadrature-based images which comprise various modulation types and SNRs with different combinations of path gains and delays. In term of modulation recognition accuracy and mean SNR estimation error, the proposed AAHs-based scheme attains 99.83% and 0.79 dB, respectively. Similarly, the proposed 2D-ASIQHs-based scheme achieves 99.06% and 1.10 dB, respectively. The obtained results showed that the proposed schemes outperform the existing state-of-the-art work.