Loading...
| Friend's email | |
| Your name | |
| Your email | |
| enter code | |
This page was sent successfuly
- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 42521 (05)
- University: Sharif University of Technology
- Department: Electrical Engineering
- Advisor(s): Nasiri-Kenari, Masoumeh
- Abstract:
- Powerful spectrum sensing and access strategies enable cognitive radios to find transmission opportunity in spectral resources dedicated exclusively to the incumbent/primary users (PUs). One of the key effecting factors on cognitive radio network (CRN) throughput is the spectrum sensing sequence used by each secondary user (SU). In this thesis, modeling, performance evaluation, and throughput maximization of a CRN are investigated. More specifically, firstly we evaluate the performance of sequential method for handovers regarding a SU’s average throughput and consumed energy, and an optimization problem is formulated to maximize the throughput through selecting optimal channel sensing time. Then, a novel method is proposed to improve the throughput by reordering the sensing sequence based on channels’ condition and PUs’ statistical characteristics. In order to avoid the challenges associated with the analytical method including huge computational burden, as a second solution, a systematic neural network-based sensing time optimization approach is also proposed. The proposed adaptive scheme is able to find the optimum value of the channel sensing time without any prior knowledge or assumption about the wireless environment including the PUs’ presence probabilities. The structure, performance, and cooperation of the artificial neural networks used in the proposed method are disclosed in detail, and a set of illustrative simulation results is presented to validate the analytical results as well as the performance of the proposed learning-based optimization scheme. After that, sequential channel sensing problem for single SU is effectively modeled through finite state Markovian processes and then validated through analytical analysis. In order to address multiple SUs, this model is extended to modified p-persistent access (MPPA) and its generalized version. While the introduced analytical framework facilitates performance evaluation process, these algorithms experience a high level of collision among the SUs. To mitigate this problem appropriately, a novel scheme is proposed, which offers higher average throughput for the SUs by statistically distributing their loads among all channels. Advantages and drawbacks of the proposed scheme are discussed. In the final section of this thesis, the SUs’ throughput maximization through finding an appropriate sensing matrix (SM) is investigated. To this end, first the average throughput of the CR network is evaluated for a given SM. Then, an optimization pr the network throughput is formulated in order to find the optimal SM. As the optimum solution is very complicated, to avoid its major challenges, three novel sub optimum solutions for finding an appropriate SM are proposed for various cases including perfect and non-perfect sensing. Despite having less computational complexities as well as lower consumed energies, the proposed solutions perform quite well compared to the optimum solution (the optimum SM). The efficiencies of the proposed SM setting schemes are validated through analytical analysis as well as numerical results
- Keywords:
- Neural Networks ; Sensing Time ; Cognitive Radio ; Queueing Network ; Spectrum Handover
Digital Object List
محتواي پايان نامه
Bookmark