In this paper, a combination of Space-Time Block Coded Spatial Modulation with Hybrid Analog-Digital Beamforming (STBC-SM-HBF) for Millimeter-wave (mmWave) communications is proposed in order to take advantage of the merits of Spatial Modulation (SM), Space-Time Block Codes (STBC), Analog Beamforming (ABF), and digital precoding techniques while avoiding their drawbacks. This proposed system benefits from the multiplexing gain of SM, from the transmit diversity gain of STBC, and from the Signal-to-Noise Ratio (SNR) gain of the beamformer. The simulation results demonstrate that the Zero Forcing (ZF) and the Minimum Mean Square Error (MMSE) precoded STBC-SM systems have better Bit Error Rate (BER) performance than the precoded SM systems. Moreover, the precoded SM shows a performance degradation compared to STBC-SM system. Furthermore, the BER is significantly improved by employing an array of ABF. In addition, it is demonstrated that a minimum of 2 antenna elements in the proposed scheme of STBC-SM-HBF are required to obtain better BER than that of the conventional SM and STBC-SM systems under the same spectral efficiency of 2 bits/s/Hz.
Taissir Y. Elganimi, Ali A. Elghariani(5-2018)

Abstract Wireless local area networks (WLANs) have been rapidly developed in recent years. It is used for various applications. VoWLAN, which transmits VoIP data over WLANs, shows its amazing attraction and constitutes one of the most flourishing applications nowadays in WLANs. One of Wireless Local Area Networks (WLAN) main drawbacks, when compared to wired networks, is that WLANs are less predictable and efficient. Wireless physical medium is harder to be controlled than physical wire. WLAN medium is also unlicensed, and thus susceptible to interferences produced by other devices. Therefore, great effort is being done in order to obtain Quality of Service (QoS) in real-time voice communications using WLANs. This topic has opened plenty of new research lines to upgrade current WLAN standards. In this thesis, a study is carried out for the behavior of new Medium Access Control (MAC) protocols defined in IEEE 802.11e draft standard Enhanced Distributed coordination function EDCF as well as for its subsequent modified versions. The Adaptive Enhanced Distributed coordination function AEDCF, designed to support QoS when providing voice communication services between stations in WLAN. Also presents experimental results obtained from simulations, and compare our results with simulations made using IEEE 802.11 standard MAC. The simulation work was done using NS-2 simulator, with the addition of specific modules for 802.11e. A performance comparison is carried out between the modified MAC scheme and IEEE standard MAC scheme, using Experimental simulation models. It is found that the adaptive technique method not only increases the medium utilization ratio and lowers the collision rate by more than 50%, but also enhances vii the overall throughput by around 20% compared with the basic IEEE 802.11DCF technique.
حسين ابراهيم ازويه (2010)

In this paper, a customized Auto-Encoder Complex Valued Convolutional Neural Network (AE-CV-CNN) that has been developed in a prior work is applied to Single Symbol Generalized Spatial Modulation (SS-GSM) scheme with new extracted features. The achieved reductions in the computational complexity at the receiver is at least 63.64% for M-PSK schemes compared to the complexity of Maximum Likelihood (ML) detection algorithm. This Fast detection algorithm is based on a proposed Low Complexity ML (LC-ML) detector that affords a complexity reduction of at least 40.91%. With these proposed algorithms, the complexity is reduced as the spatial constellation size increases. Furthermore, in comparison to other sub optimal detection algorithms, the computational complexity in terms of real valued multiplications of the AE-CV-CNN applied to LC-ML is independent of the spatial spectrum efficiency which means that the total spectrum efficiency increases with larger spatial constellation size at no additional complexity.
Akram A. Marseet , Taissir Y. Elganimi(10-2019)