Spectrum Sensing (SS) is a critical operation in a Cognitive Radio (CR) network to identify spectrum hole thereby preventing licensed users from harmful interference for improving spectrum utilization. However, multipath effects in wireless channel such as multipath fading, shadowing and receiver uncertainty affect the sensing accuracy of CR resulting to high Probability of Missing (PM) that causes interference to Primary User (PU). Maximal Ratio Combining (MRC) technique which was one of the techniques used to solve this problem suffers hardware complexity resulting in high Sensing Time (ST). Therefore, in this paper, modification of MRC technique is carried out to reduce hardware complexity of conventional MRC thereby reducing ST. The modified technique consists of ‘L’ Secondary User (SU) antennas that received the multiple copies of Primary User (PU) signals over Nakagami-m fading channel. The received PU signals are made to passed through separate channel estimator and co-phased to avoid signal cancellation before been summed up. The resultant signa is then made to passed through single RF chain and MF. Output of MF is then used as input to Energy Detector (ED) to obtain the energy of the received signal. The obtained energy is compared with the set threshold to determine the status of spectrum. The modified MRC technique is incorporated with simulation model which consists of PU transmitter that processes the randomly generated data through some signal processing techniques for transmission. Mathematical expression of Probability of False Alarm (PFA) for the modified MRC technique is derived and used to set the thresholds at PFA of 0.01 and 0.05. The modified model is evaluated using PM, Probability of Detection (PD) and PT to determine the performance. The results obtained revealed that modified MRC gives higher PD, lower PM and PT values when compared with conventional MRC.

The worldwide acceptability of wireless communication is due to its portability and flexibility. However, its performance is governed by the multipath propagation effects which make wireless communication modelling challenging. The existing technique being used to solve this propagation effects is based on Probability Density Function (PDF) which is inefficient in addressing diversity over combined Rayleigh and Rician (C_(Ray-Ric)) fading due to its complexity. Therefore, this paper aims to develop an approximated Moment Generating Function (MGF) for spatial diversity combining such as Equal Gain Combining (EGC) and Maximal Ratio Combining (MRC) over C_(Ray-Ric) fading channel. A MGF model in form of Taylor’s series is generated from the expected value of the C_(Ray-Ric) fading channels. The MGF is characterized using Amount of Fading (AF) and Bit Error Rate (BER) in term of Line of Sight (LOS) component ‘k’. The MGF is transformed into EGC and MRC, and were measured in terms of propagation paths (L). These are approximated using the Pade ́ Approximation (PA). The approximates obtained are used in the derivation of BER expression of M-ary Quadrature Amplitude Modulation (MQAM) and M-ary Phase Shift Keying (MPSK) in terms of Signal to Noise Ratio (SNR). The models are evaluated using AF and BER at different values of LOS to determine the performance of the diversity techniques. The results obtained show that as LOS component ‘k’ increases from 0, the Af and BER reduce indicating reduction in fading effects. Therefore, the models developed are effective in predicting the performance of diversity techniques and overcome the multipath effects associated with the wireless communication.

Spectrum sensing is of paramount importance in the Cognitive Radio Network (CRN) due to massive spread of wireless services. However, spectrum sensing in CRN is affected by multipath effects that make detection difficult. Square- Law Combining (SLC) technique, which is one of the methods previously used to address this problem, is associated with hardware complexity that results in long processing time. Hence, this paper aim to modify SLC technique for primary user detection in the CRN. The modified model consists of three Secondary User (SU) antennas which receive the faded signals through the Rayleigh fading channel. The received signals are combined using Switch Combiner (SC) at Radio Frequency (RF) stage. The selected signal passes through only one Energy Detector (ED) before making decision. The modified model is incorporated into simulation model which consists of Primary User (PU) transmitter that processes the randomly generated data through some signal processing techniques for transmission to the SU receiver. Probability of False Alarm (PFA) expression is derived for the modified Square-Law Combiner (mSLC) to set the thresholds at 6.64 and 9.14 for PFA of 0.01 and 0.02, respectively. The modified model is evaluated using Probability of Missing (PM), Probability of Detection (PD) and Processing Time (PT) to determine the performance. The results of the mSLC show that at SNR of 4 dB and PFA of 0.01, the values obtained for PD, PM, PT are 0.6575, 0.3530, 5.5540 s, respectively, as against the conventional SLC of 0.4000, 0.600, 6.2055 s, respectively. At SNR of 4 dB and PFA of 0.02, the values obtained for the mSLC are 0.7600, 0.3457, 6.1945 s for PD, PM and PT, respectively, as against 0.4000, 0.6000, 7.2197 s for conventional SLC. The results show that mSLC gives lower PM, higher PD and lower PT values when compared with conventional SLC.