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.
Spectrum Hole Detection (SHD) is a major operation in a Cognitive Radio (CR) network to identify empty spectrum for maximum utilization. However, SHD is often affected by multipath effects resulting in interference. The existing techniques used to address these problems are faced by poor detection rate, long sensing time and bandwidth inefficiency. Hence, this paper proposes a cluster-based Energy-Efficient Multiple Antenna Cooperative Spectrum Sensing (EEMACSS) for SHD in CR networks using Energy Detector (ED) with a modified combiner. Multiple secondary users are used to carry out local sensing using ED in multiple antenna configurations. The local sensing results are combined at the cluster head using majority fusion rule to determine the sensing results at each cluster. The sensing results from individual cluster are combined to determine the global sensing result using OR fusion rule. The proposed EEMACSS is evaluated using Probability of Detection (PD), Sensing Time (ST) and Spectral Efficiency (SE) by comparing with existing techniques. The results reveal that the proposed technique shows better performance.
Wireless communication system has found worldwide acceptability in providing acceptable services due to its portability, flexibility and ease of usage. However, the system is characterized by severe multipath propagation effects that degrade its performance. Selection Combiner (SC) as one of the techniques being used to address this problem is associated with poor performance due to fixed constellation of the modulation scheme. Hence, in this paper, an Adaptive Selection Combiner (ASC) using Constellation Adaptation Algorithm (CAA) with an expression over Log-normal fading channel is proposed. ASC is developed using conventional SC (CSC) and CAA. Ten thousand randomly generated bits are modulated using each of Phase Shift Keying (PSK) and Quadrature Amplitude Modulation (QAM) schemes. The modulated signals at varying paths are scanned by CSC to choose a path with the highest Signal to Noise Ratio (SNR). The output of SC which is a function of Channel State Information (CSI) acquired is used to determine the channel gain. The constellation size is then adjusted based on the value of channel gain through CAA. The proposed adaptive technique is simulated using MATLAB software and evaluated using Bit Error Rate (BER) to determine its performance. The results obtained show that ASC gives lower BER values than CSC due to the self-adjustment of the constellation size. Therefore, the proposed ASC can be deployed to improve the performance of wireless communication systems.
Accurate detection of White Space (WS) is of paramount importance in a Cognitive Radio Network (CRN) to prevent authorized users from harmful interference. However, channel impairment such as multipath fading and shadowing affects accurate detection of WS resulting in interference. The Existing Feature Detection (EFD) technique used to address the problem is faced with computational complexity and synchronization resulting in long sensing time, bandwidth inefficiency, energy constrain and poor detection rate. Hence, this paper proposes autocorrelation based multiple antenna with energy harvesting for WS detection in a CRN using Radio Frequency (RF) energy harvesting and autocorrelation of the received signal with a modified Equal Gain Combiner (mEGC). Antenna Switching (AS) RF energy harvesting with mEGC are used to harvest energy and information from the received PU signal in a multiple antenna configuration. Autocorrelation is then obtained and compared with the set threshold of zero to determine the presence or absence of WS. The proposed technique is evaluated using Spectral Efficiency (SE), Probability of Detection (PD) and Sensing Time (ST) by comparing with EFD technique. The results obtained revealed that the proposed technique shows better performance than EFD.
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 (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 fading channel. A MGF model in form of Taylor"s series is generated from the expected value of the 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 Pad ́ 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.
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