Study of Modulation Schemes over a Multipath Fading Channels

Communications systems concerted over wireless channels depend on the environment. Communications system can be more reliable and efficient by properly analyzing wireless channels. Today's most important features are a high data rate and reliable performance to exploiting viable networks during this new information age. The channel is not time-invariant in wireless communication, so the received signal exhibits amplitude, phase, and angle variations due to multipath fading. Increasing data rates and reducing bandwidth make Orthogonal Frequency Division Multiplexing (OFDM) an important component of wireless communication systems. The OFDM technique uses many carriers very efficiently. With this scheme, interference is robustly reduced, and fading scenarios are easily accommodated. Analyzing digital modulation schemes requires evaluating link performance with fading channels. The paper compares channel performance over varying fading environments using a variety of modulation schemes. We study the BER and SNR properties of the AWGN, Rician fading and Rayleigh fading channels modulated with BPSK, QPSK, and M-ary QAM.

Variational Sparse Bayesian Learning for Estimation of Gaussian Mixture Distributed Wireless Channels

In this paper, variational sparse Bayesian learning is utilized to estimate the multipath parameters for wireless channels. Due to its flexibility to fit any probability density function (PDF), the Gaussian mixture model (GMM) is introduced to represent the complicated fading phenomena in various communication scenarios. First, the expectation-maximization (EM) algorithm is applied to the parameter initialization. Then, the variational update scheme is proposed and implemented for the channel parameters’ posterior PDF approximation. Finally, in order to prevent the derived channel model from overfitting, an effective pruning criterion is designed to eliminate the virtual multipath components. The numerical results show that the proposed method outperforms the variational Bayesian scheme with Gaussian prior in terms of root mean squared error (RMSE) and selection accuracy of model order.

Injection-lock and reconfigurable charge-domain sampling mixers/filters for data communications over wireless channels.

This thesis provides a theoretical and experimental study of injection locking and reconfigurable charge-domain sampling mixers and filters for data communications over wireless channels. On injection-locking, the intrinsic relation between the characteristics of injection signals such as sinusoidal or square, single-tone or multi-tone, the type of oscillators under injection such as harmonic oscillators (passive or active LC oscillators) or non-harmonic oscillators (ring or relaxation oscillators), and the lock range of the oscillators under injection was investigated. For the very first time, we discovered the intrinsic relation between the lock range and the phase of multiple injections of harmonic oscillators. In addition, we obtained the closed-form expression of the lock range of harmonic oscillators with square-wave injections. Moreover, we obtained the distinct characteristics of the lock range of harmonic and non-harmonic oscillators and that of different types of non-harmonic oscillators. These theoretical findings were not known before and were validated using simulation results. On reconfigurable charge-domain sampling mixers and filters for software-defined radio, a novel quadrature charge-domain down-conversion sampling mixer with embedded finite-impulse-response (FIR), infinite-impulse-response (IIR), and 4-path bandpass filters was developed. An in-depth investigation of the principles of periodic impulse sampling, periodic windowed sampling, and periodic N-path windowed sampling was presented and a detailed mathematical treatment of charge-domain windowed samplers with built-in sinc, FIR and IIR filters was provided. The proposed quadrature charge-domain sampler with embedded FIR, IIR, and 4-path band-pass filters was implemented in IBM 130 nm 1.2V CMOS technology and its performance was validated both using simulation results and on-wafer measurement.