الفهرس 
AbstractOnly 14 pages are availabe for public view
 |  | from | 116 |  |  |
| | | from | 116 | | |
Abstract
Spectrum is the life blood of radio frequency (RF) communication. The need for higher data rates is rapidly growing as a result of the transition from voice communication to wireless multimedia applications. It is obvious that current static frequency allocation schemes cannot fulfill these requirements of increasing number of higher data rate devices. As a result, innovative technology trends that can offers new ways of exploiting the available spectrum are needed. Cognitive radio (CR) arises to be a candidate solution to spectral crowding problem. The concept of CR was first proposed by Dr. Joseph Mitola in 1999. Frequency bands are utilized in a dynamic and opportunistic manner by secondary users (〖SU〗_s) that are not heavily occupied by licensed users or primary users (〖PU〗_s). Dynamic spectrum access is the key enabling technology that enables next generation communication networks to utilize the spectrum more efficiently.
The main characteristic of CR system is its ability to sense, learn, and adapt the surrounding RF environments. As a result, it needs to reconfigurable radio resources and intelligent management system. The reconfiguration capability enables the system to adaptively modify the communication parameters without changing any hardware. CR is more likely to use Software Defined Radio (SDR) technology to execute the tasks that are obtained with cognitive capability. The intelligent management system is responsible for making according to the obtained knowledge from sensing. CR network can learn from its decisions and the result of its actions to improve its future decisions and its performance. Recent developments in CR system offer a new challenge in spectrum sensing techniques. The efficiency of spectrum sensing algorithm at low signal-to-noise ratio and small number of samples is considered a distinctive problem. Further, the speed of PU detection is considered the main challenge in real applications. The power of test and accuracy of theoretical threshold are very required for reliable detection.
Single antenna element at receiver is no longer sufficiently efficient especially for practical networks. Multiple antenna assisted CR receiver is investigated to enhance the detection performance. For a known primary user (PU) signal, matched filtering is the common technique used for signal detection over a specific band of spectrum. Therefore, detection performance enhancement of the matched filter detector has gained great attention. In this thesis, a new multiple antenna elements (MAE) and matched filtering (MF) based spectrum sensing technique named as MAE/MF is proposed for detection capability enhancement. Multiple antenna elements utilization improves the received signal to noise ratio (SNR) in proportional to the achieved antenna array gain. The simulation results showed that the proposed MAE/MF technique outperforms the single antenna element based matched filter (SAE/MF) and other existing techniques in the state-of-the-art, especially at extremely low signal to noise ratios and limited number of received signal samples. Based on the promising results of the utilization of the traditional linear antenna arrays in CR receiver, we seek to further performance enhancement of the multiple antenna elements (array) based detectors. This target is achieved by applying digital beamforming for the utilized traditional antenna arrays. Antenna arrays digital beamforming has a great impact on the performance of wireless communication systems especially spectrum sensing (SS) in the cognitive radio (CR) systems. For efficient power handling, larger size antenna arrays of high gains are required at the CR receiver. But, this will increase the number of radio frequency (RF) chains required one per antenna and the complexity of signal processing will be significantly increased. In this thesis, a new signal model for SS system using digital beamforming of antenna arrays for maximum gains is introduced.