الفهرس 
Chapter 1: IntroductionOnly 14 pages are availabe for public view
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Abstract
Index modulation (IM) refers to a family of modulation techniques that rely on the activation states of some resources/building blocks for information embedding. Spatial modulation (SM) is a type of IM that utilizes antenna indices as a resource block for information embedding. SM enhances the system performance with reasonable system complexity. The vital limitation of SM is the requirement of a large number of transmitting antennas to increase the rate of transmission. Consequently, the receiver complexity and average processing time increase.
Recently, the mid-symbol duration antenna transition (MAT) technique was proposed to get rid of the shortcomings of the SM technique. This MAT approach allows active antenna transition in the middle of the symbol duration to further reduce the number of utilized transmitter antennas (TAs). Therefore, MAT reduces the receiver processing time and improves average bit error rate (ABER) performance compared to the SM technique while achieving the same SE.
Due to the promising advantages of the MAT technique, this thesis firstly gives attention to the mathematical analysis of the MAT system to provide a closed-form for the ABER performance upper bound over correlated and uncorrelated generalised flat fading channels. The validity of the derived ABER upper bound is proved by contrasting it with the Monte-Carlo simulated ABER performance. Results show that the analytically driven ABER upper bound is tightly congruent with the Monte-Carlo simulated ABER at high SNR values and slightly loose for small SNR values. Moreover, the MAT receiving process is mathematically analyzed to find a closed-form for the MAT receiver complexity. The obtained comparison results prove that MAT reduces the receiver complexity compared to SM, Generalized SM (GSM), and Variable Generalized SM (VGSM) techniques.
Thereafter, this thesis proposes two approaches for solving SM limitations concerning reducing the number of TAs while improving the rate of transmission.
The first proposed approach relies on double antennas transition (DAT) through information symbol transmission-duration. The second proposed approach is based on splitting Mid-symbol antenna Transition (MAT) spatial domain to the In-phase and Quadrature-phase dimensions (QMAT).
For each proposed approach a closed-form for the ABER performance upper bound over correlated and uncorrelated generalised fading is obtained through mathematical analysis. The validity of the derived ABER upper bound is proved by contrasting it with the simulated ABER performance. Results show that the analytically driven ABER upper bound is tightly congruent with the Monte-Carlo simulated ABER at high SNR values and slightly loose for small SNR values for both proposed approaches.
Moreover, the comparison studies show that the 1ST proposed DAT approach introduces more reduction in the number of transmitting antennas as compared to SM, GSM, VGSM, and MAT, at the same SE. Furthermore, the 2nd proposed quadrature mid-symbol antenna transition (QMAT) approach introduces more reduction in the number of transmitting antennas as compared to SM, quadrature SM (QSM), MAT, at the same SE.
The obtained ABER versus signal to noise ratio (SNR in dB) simulation results show that the 1ST proposed DAT approach improves ABER performance of SM and MAT at the same SE, and the same system configuration, over different fading channels. Besides, the 2nd proposed QMAT approach improves ABER performance of SM, QSM, and MAT at same SE, and the same system configuration, over different fading channels, e.g., Rayleigh, Rician, Nakagami-m fading channels.
Mathematical analysis of both proposed approaches receiving process led to a closed-form for these approaches’ receiver complexity. The obtained closed-forms show that the 1ST proposed DAT approach significantly reduces receiver complexity compared to SM, GSM, VGSM, and MAT. Moreover, the 2nd proposed QMAT approach significantly reduces receiver complexity compared to SM, QSM, and MAT.