Energy Consumption Control in Cooperative and Non-Cooperative Cognitive Radio using Variable Spectrum Sensing Sampling

In cognitive radio (CR) network, the concept of energy-efficient design is very important considering the costly energy consumption that may limit its implementation, especially in battery-powered devices. In these networks, significant part of the energy is consumed in the energy detector during spectrum sensing to detect the presence and absence of the primary user (PU). In this paper, we investigated the reduction of energy consumption in two scenarios: the non-cooperative scenario and the cooperative scenario by reducing the number of sensed samples. We also explained the optimisation criteria for improving energy consumption by controlling the number of sensed samples, and the detection probability in both scenarios. The performance of energy detection system was evaluated in AWGN and Rayleigh fading channels. The simulation results show that in non-cooperative scenario at Eb/No of 10 dB, 50% and 46% of the energy consumed in the detection was saved when the number of sensed samples was reduced by 50% with acceptable loss in detection probability of 5% and 12% in AWGN and Rayleigh channel respectively. In cooperative scenario, the result shows that increasing the number of cognitive users (CU) reduced the average energy consumption per sensor and improved the detection probability

COMPLEXITY REDUCTION OF CYCLOSTATIONARY SENSING TECHNIQUE USING IMPROVED HYBRID SENSING METHOD

In cognitive radio system, the spectrum sensing has a major challenge in needing a sensing method, which has a high detection capability with reduced complexity. In this paper, a low-cost hybrid spectrum sensing method with an optimized detection performance based on energy and cyclostationary detectors is proposed. The method is designed such that at high signal-to-noise ratio SNR values, energy detector is used alone to perform the detection. At low SNR values, cyclostationary detector with reduced complexity may be employed to support the accurate detection. The complexity reduction is done in two ways: through reducing the number of sensing samples used in the autocorrelation process in the time domain and through using the Sliding Discrete Fourier Transform (SDFT) instead of the Fast Fourier Transform (FFT). To evaluate the performance, two versions of the proposed hybrid method are implemented, one with the FFT and the other with the SDFT. The proposed method is simulated for cooperative and non-cooperative scenarios and investigated under a multipath fading channel. Obtained results are evaluated by comparing them with other methods including: cyclostationary feature detection (CFD), energy detector and traditional hybrid. The simulation results show that the proposed method with the FFT and the SDFT successfully reduced the complexity by 20% and 40% respectively, when 60 sensing samples are used with an acceptable degradation in the detection performance. For instance, when Eb/N0 is 0 dB , the probability of the detection of Pd is decreased by 20 % and 10% by the proposed method with the FFT and the SDFT respectively, as compared with the hybrid method existing in the literature

Modified Threshold-based Spectrum Sensing Approach for VANETs

The Primary User (PU) signal detection in Cognitive Radio (CR) is crucial and is achieved through spectrum sensing techniques. The Energy Detection method is a commonly used technique, and selecting a proper threshold is essential to enhance the efficiency of the CR system. This research paper demonstrates the maximum achievable throughput and validates a Modified Threshold (MT) approach. The authors consider a scenario with multiple antennas at the receiver, where these antennas are correlated and subjected to mobility effects, and they employ the Energy Detection (ED) for spectrum sensing. The study analyzes the system's performance over a Nakagami-m fading channel, considering available correlations among the antenna elements. To compute important statistical values, the Moment Generating Function (MGF) method is employed. The research employs specialized mathematical functions, such as the Lauricella and confluent hypergeometric functions, to derive closed-form expressions for the Probability of Detection when employing the diversity technique. The results indicate a significant enhancement in the performance of the proposed algorithm when utilizing the modified threshold parameter across a wide range of Signal to Noise Ratio (SNR) values. Additionally, increasing the number of branches in the antenna system further improves detection performance. Interestingly, under high fading parameter conditions (m=4), the detection probability is found to be superior with exponential correlation among the L antenna elements compared to other available correlated branches

IMPROVEMENT OF ENERGY CONSUMPTION IN SPECTRUM SENSING COGNITIVE RADIO NETWORKS USING AN EFFICIENT TWO STAGE SENSING METHOD

Cognitive radio (CR) is a wireless technology developed to improve the usage in the spectrum frequency. Energy consumption is considered as a big problem in this technology, especially during a spectrum sensing. In this paper, we propose an algorithm to improve the energy consumption during the spectrum sensing. The theoretical analysis to calculate the amount of energy consumption, using the proposed method during sensing stage as well as the transmission stage during transmitting a local decision to the fusion center FC, are derived. The proposed algorithm is using energy detection technique to detect the presence or absence of the primary user (PU). The proposed algorithm consists of two stages: the coarse sensing stage and fine sensing stage. In the coarse sensing stage, all the channels in the band are sensed shortly and the channel that have maximum (or minimum) energy is identified to make a dense fine sensing for confirming the presence of the PU signal (or hole). The performance of the proposed algorithm is evaluated in two scenarios: non-cooperative, and cooperative in both the AWGN and Rayleigh fading channels. The simulation results show that the proposed method improves the energy consumption by about 40% at a low SNR values, when compared with the traditional methods based on a single sensing stage and more advanced method based on censoring and sequential censoring algorithms

Implementation of Selected Spectrum Sensing Systems for Cognitive Radio Networks using FPGA Platform, Journal of Telecommunications and Information Technology, 2018, nr 4

The energy efficient spectrum sensing method is very important in cognitive radio (CR), since high power drain may limit its implementation in mobile applications. The spectrum sensing feature consumes more energy than other functional blocks, as it depends on continuous detection of the presence or absence of the primary user (PU). In this paper, we proposed two methods to reduce energy consumption of the spectrum sensing feature. The first is of a single stage variety with a reduced number of sensed samples. The other uses two stages. The first stage performs coarse sensing for many subchannels, and the best subchannel is forwarded for fine sensing in the second stage. The performance of the proposed methods is evaluated in AWGN channel and compared with the existing approach. The proposed methods are simulated using Matlab and ModelSim and are then hardware implemented using the Altera Cyclone II FPGA board. Simulation results show that the proposed methods offer an improvement in energy consumption with an acceptable reduction in the probability of detection. At Eb/N0 Eb/N0 Eb/N0 of 0 dB, the energy consumption is reduced by 50% and 72% in the first and second proposed method, respectively, compared to the traditional method (100% sensing)