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Abstract Recent wireless communication system faces a growing demands for broadband and multimedia services and also will be the future wireless system. According to a statistical estimation from Cisco, globe mobile data traffic grew about 2.5-fold every year during 2008 to 2011, and the number of mobile-connected devices, including smartphone, laptop, etc., was estimated to be over 7.1 billion in 2015, which is approximately equal to the world’s population. In order to support the rapid demand growth, numerous research efforts had been done in this active field. With the scarcity of the radio resources such as Bandwidth and Power, etc. Researcher had proposed an intelligent communication system named Cognitive Radio Networks CRNs for efficient optimization of the available radio resources. Exploiting the empty frequency bands of the licensed system improve the spectrum utilization and enable more wireless services and networks to communicate concurrently. The problem of resource allocation, is to intelligently allocate limited power and bandwidth resources among users according to each user requirements in an intelligent and efficient manner which can be achieved through CRNs. It has been discussed heavily from the point of view of power and bit allocation. Through formulating it as an objective problem depending on different criteria and approaches such as spectral efficiency, interference power, fairness, throughput and etc. Aiming to maximize it through optimization methods like evolutionary algorithms, Game theory, heuristics…etc. One of the main basic principles in any wireless communication paradigm is throughput improvement. Many researchers aiming to reaches to this goal through different mechanism like modulation techniques, deploying MIMO antenna System and the power allocation strategies based on different optimization algorithms In this thesis, the problem of maximizing the secondary throughput in downlink CRNs based on power optimization strategies, Multicarrier Modulation (MCM) techniques and MIMO antenna system in CRNs was considered. This maximization problem will occurred under some constraints Abstract _ III like maximum transmit power for secondary network and interference power level at each PU receiver. As the first topic of this research, we aim to maximize the secondary system throughput for downlink Orthogonal Frequency Division Multiplexing (OFDM)-based in Sensing-Based Spectrum Sharing CRNs. Using a heuristic algorithm named Simulated Annealing (SA) for enhancing the transmission power of secondary system in order to improve its performance. Taking into account the constraints of total transmitted power and the aggregated interference introduced on the licensed network. Secondly, an optimal power allocation scheme was proposed using an optimization techniques called Particle Swarm optimization aiming to maximize the minimal throughput among overall secondary users and also the total system throughput in downlink MIMO-based CRNs. While keeping the SUs’ interference on each PU below a given threshold to assure the QoS of PUs, also considering QoS of SUs. Further, the comparison between different optimization techniques based on the complexity, process time and system throughput was discussed. The third topic discussed the deploying of a different Multi-carrier Modulation technique named Generalized Frequency Division Multiplexing (GFDM) for CRNs to solve some of OFDM related problems such as PAPR, Out-Of-Band Radiation and large overhead. In addition, a study for different system parameter was done to evaluate the performance of the new modulation technique. Also, a power loading algorithm was proposed to efficiently improve the system throughput under a predefined power and interference constraints. |