Nowadays, there has been an increase in wireless technologies, which are used for variety ofrnapplications and services. The need of using wireless services and applications also increased fromrnday to day that brings a higher demand on radio spectrum leading to shortage and congestion. Inrnaddition, the fixed assigning of a radio spectrum to a specific user leads to under-usage of availablernspectrum which brings wastage of spectrum. After several studies, cognitive radio exists tornminimize problems regarding to the limited and wasted spectrum resource. This technology,rncognitive radio searches a free or unused portion of spectrum and enables secondary users to accessrnthat free part of spectrum.rnSpectrum sensing methods are very important in cognitive radio for detecting the availability ofrnunused spectrum and allow secondary users to use the spectrum band in non-interference manner.rnEnergy and matched filter detector are the most common type of transmitter detection techniques torndetect the user. Even though energy detector used most of the time, its performance of detectionrnpoorly decrease and degraded at weak received SNR and noise uncertainty scenario. Beside of this,rnmatched filter detector is an alternative and good sensing algorithm in lower SNR value, since itrnenlarges SNR of the signal received and gives a better performance compared to energy detection.rnThis thesis aims to develop an efficient hybrid detection technique, by combining energy withrnmatched filter detector to enhance energy detector at low SNR value in specific, and improvernspectrum detection performance in general. The performance of proposed hybrid detector withrnconventional energy detector and other hybrid detection technique is analyzed and compared.rnReceivers operating curve (ROC), false alarm probability, detection probability and SNR values arernthe basic performance evaluation matrices. MATLAB software has been used to evaluate thernperformance of detection technique. In simulation result, the detection performance has beenrnevaluated based on the plotting Pd vs Pf, Pd vs SNR, Pmd vs SNR and Pd vs noise uncertainty forrnboth fading and non-fading channel model which are Rayleigh and AWGN channel respectively.rnFrom the result obtained, the proposed hybrid detection performs better than energy detection andrnother hybrid detection under AWGN and Rayleigh fading channel. The proposed hybrid detectionrnenables to reduce the effect of noise uncertainty and fading on detection performance.